JP4659304B2 - Data creation device for calculating energy consumption of houses - Google Patents

Description

【００４１】
建物内の各部屋に関してそれぞれ前述の式が用いられるので、問題は各部屋の室温に関する連立方程式となる。この連立方程式をＳＯＲ法などにより解くことで、各部屋の室温が計算される。
計算対象時刻に空調が行われている部屋においては、室温設定条件に従って室温が決定され、計算対象時刻に室温を保つために必要な熱量、すなわち空調熱負荷が計算される。ただし空調機の容量をこの空調熱負荷が上回っている場合は、空調機容量分のみが処理されたとして室温が再度計算される。計算対象時刻に空調が行われていない部屋においては、室温（自然室温）が計算される。
【００４２】
分類部４４０について説明を加えると、分類部４４０は、消費エネルギー計算部４３０にて計算された空調用エネルギー消費量を基本データとして分類条件（計算条件に相当する）に基づいて分類処理する。具体的には、空調用エネルギー消費量の時間変動（例えば、１５分間隔で1日中）の基本データを、分類条件にてラベリングする。つまり、分類条件は、建物特性（住戸プラン及び配置条件を含む）、空調条件（設定温度、空調使用時間を含む）、日特性（平日及び休日を含む）、及び、地域特性を含む。
【００４３】
記録用プログラム部１００について説明を加えると、記録用プログラム部１００は、電気・厨房用ガス・給湯関係の基本データ整理部３００の分類部３４０にて分類された各基本データ、及び、空調関係の基本データ整理部４００の分類部４４０にて分類された各基本データを、データベース部Ｂに分類条件毎に分類した状態で記録する。
【００４４】
つまり、分類部３４０，４４０にて分類処理するエネルギー消費関連実測データには、実測データそのもの、実測データを実測データ前処理部３１０にて処理したデータ、並びに、実測データを使用条件抽出部４１０及び消費エネルギー計算部４３０にて処理したデータが含まれる。
【００４５】
次に、データ作成用プログラム部Ｐ１全体の処理手順について、図５ないし図９の夫々にて示すフローチャートに基づいて説明する。
図５に示すように、データ入力部２００にて、厨房用ガス関連実測データ、給湯関連実測データ、電気関連実測データ及び空調関連実測データ夫々を各別に入力処理し、厨房用ガス関連実測データ、給湯関連実測データ及び電気関連実測データの夫々が入力されたときは、電気・厨房用ガス・給湯関係の基本データ整理部３００により入力データを分類条件毎に分類処理する基本データ整理処理を実行し、分類処理された基本データを記録用プログラム部１００にてデータベース部Ｂに分類条件毎に記録する記録処理を実行し、空調関連実測データが入力されたときは、空調関係の基本データ整理部４００により入力データを分類条件毎に分類する基本データ整理処理を実行して、分類処理された基本データを記録用プログラム部１００にてデータベース部Ｂに分類条件毎に記録する記録処理を実行する。
【００４６】
図６に示すように、厨房用ガス関連実測データの基本データ整理処理は、実測データ前処理部３１０にて、ガス消費実測データから厨房用ガス消費量を分離する前処理を実行し、続いて、在宅特性類推部３２０にて、ガス消費実測データに基づいて在宅特性を類推し、続いて、消費特性類推部３３０にて、ガス消費実測データに基づいてエネルギー消費特性を類推し、続いて、ガス消費実測データと共に入力された測定日に基づいて日特性を求める日特性導出処理を実行し、続いて、分類部３４０にて、厨房用ガス消費量を基本データとして、在宅特性、エネルギー消費特性、入居者特性及び日特性に基づいて分類する分類処理を実行する。
【００４７】
図７に示すように、給湯関連実測データの基本データ整理処理は、実測データ前処理部３１０にて、毎時刻の給水の実測データ及び給湯装置からの給湯の実測データに基づいて湯消費量及び湯熱量を求める前処理を実行し、続いて、在宅特性類推部３２０にて、ガス消費実測データに基づいて在宅特性を類推し、続いて、消費特性類推部３３０にて、前記湯消費量に基づいてエネルギー消費特性を類推し、続いて、前記実測データと共に入力された測定日に基づいて日特性を求める日特性導出処理を実行し、続いて、分類部３４０にて、湯消費量及び湯熱量を基本データとして、在宅特性、エネルギー消費特性、入居者特性及び日特性に基づいて分類処理する。
【００４８】
図８に示すように、電気関連実測データの基本データ整理処理は、在宅特性類推部３２０にて、ガス消費実測データに基づいて在宅特性を類推し、続いて、消費特性類推部３３０にて、電力消費量のデータに基づいてエネルギー消費特性を類推し、続いて、前記実測データと共に入力された測定日に基づいて日特性を求める日特性導出処理を実行し、続いて、分類部３４０にて、電力消費量のデータそのものを基本データとして、在宅特性、エネルギー消費特性、入居者特性及び日特性に基づいて分類処理する。
【００４９】
図９に示すように、空調関連実測データの基本データ整理処理は、使用条件抽出部４１０にて、暖房冷房の消費エネルギーの時間経過に伴う実測データ及び空調の設定温度等を含む空調関連実測データから空調を行う時間帯及び設定温度を含む空調条件を抽出する空調条件抽出処理を実行する。
続いて、一般的建物条件を読み出し、続いて、計算条件整理部４２０にて、計算対象住戸プラン、住戸配置条件、空調の使用時間帯パターン（平日）、空調の使用時間帯パターン（休日）、空調の設定温度、計算対象地域及び計算対象年度の組合わせにより計算条件を整理する計算条件整理処理を実行する。
続いて、計算対象の地域・日時の気象条件を読み出しながら、消費エネルギー計算部４３０にて、計算対象の日の１日の空調機器の消費エネルギーを計算する消費エネルギ−計算処理を実行し、１日分の計算が終了すると、次の計算対象の日の１日分の空調機器の消費エネルギーを計算することを計算対象期間が終了するまで繰り返し、計算対象期間の計算が終了すると、分類部４４０にて、各計算条件を分類条件として分類する分類処理を実行する。
上記の空調関連実測データの基本データ整理処理は、全対象地域及び全計算条件の組み合わせについて実行する。
【００５０】
次に、エネルギー消費量演算装置ＣＥについて説明を加える。
図２及び図１４に示すように、エネルギー消費量演算装置ＣＥの各種処理を実行する消費エネルギー積算用プログラム部Ｐ２は、条件入力部５００、住戸特性割り当て部６００、用途別消費エネルギー積算部７００、計算結果整理部８００及び出力部９００とから構成してある。
【００５１】
条件入力部５００は、キーボード３やマウス４を通じて入力される特性条件を入力処理するように構成し、住戸特性割り当て部６００は条件入力部５００にて入力処理された特性条件を計算対象の集合住宅の各住戸に割り当てるように構成し、用途別消費エネルギー積算部７００は、住戸特性割り当て部６００にて住戸毎に割り当てられた特性条件に基づいて、エネルギー用途（エネルギーの種類に相当する）別にデータベース部Ｂから住戸毎に特性条件にあう基本データを選択して住戸毎に積み上げて、設定期間内に消費するエネルギー消費量を求め、更に、求めた各住戸のエネルギー消費量をエネルギー用途別に全住戸分積算して集合住宅の全エネルギー消費量を求めるように構成し、計算結果整理部８００は、用途別消費エネルギー積算部７００にて求められたエネルギー用途別の全エネルギー消費量を有用なように種々に整理するように構成し、出力部９００は、計算結果整理部８００にて整理されたデータをディスプレイ６やプリンタ７に出力するように構成してある。
【００５２】
図１５に基づいて、条件入力部５００について説明を加える。条件入力部５００は、入力者の負担を軽減するために、必須条件入力部５１０と詳細条件入力部５２０とから構成してある。
必須条件入力部５１０は、個々の集合住宅毎に積算に不可欠で容易に調べることができる特性条件の入力処理を実行する。入力者はすべての特性条件を必ず入力する必要がある。
詳細条件入力部５２０は、住民の在宅状況やエネルギー消費特性などの、重要であるが入力者が必ずしも容易には調べることができない条件の入力処理を実行する。
【００５３】
必須条件入力部５１０は、計算対象年度を入力する計算対象年入力部５１１、計算対象地域を入力する計算地域入力部５１２、計算対象集合住宅の住戸数を入力する住戸数入力部５１３、計算対象集合住宅における実際に住民が入居している住戸の割合を入力する入居率入力部５１４、計算対象の集合住宅における各住戸の住戸プラン（床面積）・主方位・階からなる住戸条件の組み合わせについて、各組み合わせに対応する住戸数を入力する住戸条件入力部５１５、入居が予想される住民の家族特性を各家族特性別に集合住宅の入居全戸数に対する比率にて入力する家族特性入力部５１６とから構成してある。
【００５４】
詳細条件入力部５２０は、入居住戸の日々の在宅特性を入力する在宅特性入力部５２１、各住戸の暖房特性（年間を通しての使用期間、平日休日の各使用時間帯及び設定温度）を入力する暖房条件入力部５２２、各住戸の冷房特性（年間を通しての使用期間、平日休日の各使用時間帯及び設定温度）を入力する冷房条件入力部５２３、給湯用及び空調用以外の電気エネルギー消費におけるエネルギー消費特性を入力する電気条件入力部５２４、給湯におけるエネルギー消費特性を入力する給湯条件入力部５２５、厨房用ガスにおけるエネルギー消費特性を入力する厨房ガス条件入力部５２６とから構成してある。
【００５５】
条件入力部５００は、図２６に示す如き基本入力画面をディスプレイ６に表示し、この入力用基本画面により、各入力処理を実行する。
計算対象年入力部５１１、計算地域入力部５１２、住戸数入力部５１３及び入居率入力部５１４は、それぞれこの基本入力画面にてデータの入力処理を実行する。
【００５６】
住戸条件入力部５１５は、基本入力画面において「住戸配置の設定」ボタンがクリックされると、住戸条件入力画面（図示省略）をディスプレイ６に表示して、住戸プラン（床面積）、主方位・階の配置条件からなる各住戸条件組み合わせの住戸数の入力処理を実行する。つまり、住戸条件入力部５１５により、各住戸に特性条件を割り当てる住戸特性割り当て条件として、住戸プラン及び配置条件の割り当て条件が入力される。
【００５７】
家族特性入力部５１６は、基本入力画面において「入居住戸家族構成」ボタンがクリックされると、家族構成入力画面（図示省略）をディスプレイ６に表示して、「単身者」、「夫婦＋子供で妻が専業主婦」、「夫婦＋子供で共働き」及び「高齢者家族」等の各家族特性に対応する住戸数を入居全戸数に対する比率にて入力する処理を実行する。つまり、家族特性入力部５１６により、住戸特性割り当て条件として、「単身者」、「夫婦＋子供で妻が専業主婦」、「夫婦＋子供で共働き」及び「高齢者家族」等の家族特性からなる家族特性の割り当て条件が入力される。
【００５８】
在宅特性入力部５２１は、前記家族構成入力画面において「在宅状況の設定」ボタンがクリックされると、在宅状況入力画面（図示省略）をディスプレイ６に表示して、平日、休日夫々について、「終日在室」、「日中に短時間外出」、「日中に長時間外出」、「午後不在」、「午前中不在」及び「終日不在」のＡ〜Ｆの６パターンの各パターンに対応する住戸数を入居全戸数に対する比率にて入力する処理を実行する。つまり、在宅特性入力部５２１により、住戸特性割り当て条件として、平日及び休日の夫々についてＡ〜Ｆの６パターンからなる在宅特性の割り当て条件が入力される。
【００５９】
暖房条件入力部５２２は、基本入力画面において「暖房関係」ボタンがクリックされると、暖房使用状況入力画面（図示省略）をディスプレイ６に表示して、年間を通しての暖房の使用期間を入力すると共に、平日及び休日それぞれについて各使用時間帯に対応する住戸数、各設定温度に対応する住戸数を入居全戸数に対する比率にて入力する処理を実行する。つまり、暖房条件入力部５２２により、住戸特性割り当て条件として、平日休日の各使用時間帯及び設定温度からなる暖房条件（空調条件に相当する）の割り当て条件が入力される。
冷房条件入力部５２３は、基本入力画面において「冷房関係」ボタンがクリックされると、冷房使用状況入力画面（図示省略）をディスプレイ６に表示して、年間を通しての冷房の使用期間を入力すると共に、平日及び休日それぞれについて各使用時間帯に対応する住戸数、各設定温度に対応する住戸数を入居全戸数に対する比率にて入力する処理を実行する。つまり、冷房条件入力部５２３により、住戸特性割り当て条件として、平日休日の各使用時間帯及び設定温度からなる冷房条件（空調条件に相当する）の割り当て条件が入力される。
【００６０】
電気条件入力部５２４は、基本入力画面において「電気関係」ボタンがクリックされると、電気関係エネルギー消費特性入力画面（図示省略）をディスプレイ６に表示して、「多消費型」、「準多消費型」、「標準型」及び「節約型」の夫々の電気関係エネルギー消費特性に対応する住戸数を入居全戸数に対する比率にて入力する処理を実行する。つまり、電気条件入力部５２４により、住戸特性割り当て条件として、「多消費型」、「準多消費型」、「標準型」及び「節約型」からなる電気エネルギー消費特性の割り当て条件が入力される。
【００６１】
給湯条件入力部５２５は、基本入力画面において「給湯関係」ボタンがクリックされると、給湯関係エネルギー消費特性入力画面（図示省略）をディスプレイ６に表示して、「多消費型」、「標準型」及び「節約型」の夫々のエネルギー消費特性に対応する住戸数を入居全戸数に対する比率にて入力する処理を実行する。つまり、給湯条件入力部５２５により、住戸特性割り当て条件として、「多消費型」、「標準型」及び「節約型」からなる給湯エネルギー消費特性の割り当て条件が入力される。
【００６２】
厨房ガス条件入力部５２６は、基本入力画面において「厨房関係」ボタンがクリックされると、厨房関係エネルギー消費特性入力画面（図示省略）をディスプレイ６に表示して、「多消費型」、「標準型」及び「節約型」の夫々のエネルギー消費特性に対応する住戸数を入居全戸数に対する比率にて入力する処理を実行する。つまり、厨房ガス条件入力部５２６により、住戸特性割り当て条件として、「多消費型」、「標準型」及び「節約型」からなる厨房ガス消費特性の割り当て条件が入力される。
【００６３】
住戸特性割り当て部６００について説明を加える。住戸特性割り当て部６００は、条件入力部５００にて入力された住戸特性割り当て条件に基づき、各住戸について、住戸プラン、配置条件、家族特性、在宅特性、暖房条件、冷房条件、電気エネルギー消費特性、給湯エネルギー消費特性及び厨房ガス消費特性の各割り当て条件を割り当てる。条件入力部５００では、入力を簡便にするため、各項目に対する割り当て条件は各型にあてはまる住戸の入居全個数に対する割合で入力されており、この住戸特性割り当て部６００では、この割合から個々の住戸１戸１戸に対して１つの型をモンテカルロ法により割り当てる。図２７に割り当て例の一例を示す。
【００６４】
モンテカルロ法は、計算機を用いて乱数を発生させることである確率に従って１つの特性値（パラメーター）を割り当てるものであり、周知であるので詳細な説明は省略して、以下に簡単に説明するに止める。
Ｐ₁・Ｐ₂〜Ｐ_n：特性に関する型１〜ｎの夫々の発生確率（０〜１）（特性割り当て条件）
Ｒａｎ：一様分布乱数（０〜１の間の任意の数をとる）とすると、このとき、１≦ｋ≦ｎとなるｋの中で、下記の数４に示す数式が成立するものがこの住戸に割り当てられる型となる（ｋ型）。
【００６５】
【数４】

【００６６】
図１６に基づいて、用途別消費エネルギー積算部７００について説明を加える。用途別消費エネルギー積算部７００は、計算対象日の年月日より日特性としての季節と曜日を決定すると共に、その日の天候に関する日特性としての気象条件をデータベース部Ｂから読み込む日特性生成部７１０、入居各住戸の在宅特性および日特性にしたがってモンテカルロ法により在宅状況を決定する在宅状況生成部７２０、電気に関する消費エネルギーを積算する電気積算部７３０、給湯に関する消費エネルギーを積算する給湯積算部７４０、厨房ガスに関する消費エネルギーを積算する厨房ガス積算部７５０、暖房に関する消費エネルギーを積算する暖房積算部７６０及び冷房に関する消費エネルギーを積算する冷房積算部７７０から構成してある。
【００６７】
図１７に示すように、電気積算部７３０は、計算対象日における計算対象住戸に関して、まず条件選択部７３１で曜日・季節・天候からなる日特性と在宅特性と電気エネルギー消費特性の各特性条件を整理し、そのすべての特性条件に適合する基本データをデータベース部Ｂの中の電気関係から選択する。なお、特性条件に適合する基本データが複数ある場合には、ランダム選択部７３２にてモンテカルロ法に基づいてランダムに１つの基本データを選択する。基本データには電力消費量の時刻変動が記録されており、この変動が電気消費量積算部７３３にて全住戸分にわたって積み上げられる。
これにより、すべての住戸に影響を与える日特性を全住戸にわたりそろえた上で、在宅特性とエネルギー消費特性を考慮しつつ、日々のランダム性を考慮しつつ消費電力の時刻変動を積み上げることが可能となる。
【００６８】
図１８に示すように、給湯積算部７４０は、計算対象日における計算対象住戸に関して、まず条件選択部７４１で曜日・季節・天候からなる日特性と在宅特性と給湯エネルギー消費特性の各特性条件を整理し、そのすべての特性条件に適合する基本データをデータベース部Ｂの中の給湯関係から選択する。なお、特性条件に適合する基本データが複数ある場合には、ランダム選択部７４２にてモンテカルロ法に基づいてランダムに１つの基本データを選択する。基本データは、湯消費量と湯熱量の時刻変動が記録されているので、この湯消費量と湯熱量を、給水温度計算部７４３にて計算した給水温度に基づいて、給湯熱負荷計算部７４４にて実際の消費エネルギーである給湯熱負荷を計算して、この給湯熱負荷の時刻変動が給湯消費エネルギー積算部７４５にて全住戸分にわたって積み上げられる。
【００６９】
尚、給水温度計算部７４３は、外気温度からの給水温度の推定式に基づいて給水温度を推定する。外気温度からの給水温度の推定式については、「給湯設備設計用基本データの検討・整備に関する研究委員会」空気調和・衛生工学会などからすでに提案が行われている。推定式に関してはいくつかの形があるが、本実施形態では、当日の外気温度のみを説明変数とする下記の数５に示す線形単回帰式を用いる。
【００７０】
【数５】
Ｔ_water＝ａ_i×Ｔ_air＋ｂ_i
【００７１】
但し、Ｔ_Water：推定給水温度
Ｔ_air：計算対象地域の計算日の外気温度
ａ_i，ｂ_i：地域Ｉにおける係数（東京では、ａ_i＝０．８５１６，ｂ_i＝２．４７３）
【００７２】
但し、集合住宅においてはプラント内部でいったん貯水槽に貯水することが多いため、給水温度が通年高めになる傾向がある。そのため、本実施形態ではプラントの通年での温度上昇補正係数Ｃ_plantを加えて、以下の数６に示す数式を用いる。
【００７３】
【数６】
Ｔ_water＝ａ_i×Ｔ_air＋ｂ_i＋Ｃ_plant
【００７４】
又、給湯熱負荷計算部７４４は、以下の数７に示す数式により、給湯熱負荷を計算する。
【００７５】
【数７】
Ｈ_load＝Ｈ_yu−（Ｖ_yu×Ｔ_water）×４．２
【００７６】
但し、Ｈ_load：給湯熱負荷[ｋＪ]
Ｈ_yu：湯の熱量（ｋＪ）
Ｖ_yu：湯の消費量（Ｌ）
【００７７】
図１９に示すように、厨房ガス積算部７５０は、計算対象日における計算対象住戸に関して、まず条件選択部７５１で曜日・季節・天候からなる日特性と在宅特性と厨房ガス消費特性の各特性条件を整理し、そのすべての特性条件に適合する基本データをデータベース部Ｂの中の厨房ガス関係から選択する。なお、特性条件に適合する基本データが複数ある場合には、ランダム選択部７５２にてモンテカルロ法に基づいてランダムに１つの基本データを選択する。基本データには厨房ガス消費量の時刻変動が記録されており、この厨房ガス消費量の時刻変動が厨房ガス消費量積算部７５３にて全住戸分にわたって積み上げられる。
【００７８】
暖房積算部７６０及び冷房積算部７７０は同様であるので、図２０に基づいてまとめて説明する。
計算対象日が条件入力部５００で入力された空調期間内であるか否かが判断され、計算期間でなければ計算は翌日に移る。次に計算対象住戸における在宅特性から、不在日であればその日には空調用消費エネルギーが発生しなかったとして次の住戸に計算が移る。計算対象日が空調期間中で計算対象住戸が不在でなければ、空調用消費エネルギーが発生したとして条件選択部７６１，７７１において基本データの選択が行われる。空調条件（空調使用時間帯、設定室温）、住戸プラン、配置条件、計算対象集合住宅の立地する地域を条件として、その条件の組み合わせに適合する基本データをデータベースＢの空調関係から選択する。他用途と異なり、一つの条件組み合わせに適合する基本データは１つのみである。
基本データには、計算対象日におけるある条件組み合わせ下での空調関係消費エネルギーの計算結果が時刻変動の形で記録されている。選択された基本データは空調消費エネルギー積算部７６２，７７２にて、計算対象日における全住戸分に当たって積み上げられる。
【００７９】
図２１に基づいて、計算結果整理部８００について説明を加える。計算結果整理部８００は、前述の用途別消費エネルギー積算部７００の各積算部７３０，７４０，７５０，７６０，７７０にて計算された集合住宅における消費エネルギーの時刻変動（本実施形態では15分間隔）を要約して、有用な計算結果として整理する。
用途別消費エネルギー積算部７００の積算結果は、計算期間中の各日における計算対象集合住宅内全住戸合計の消費エネルギーの時刻変動という形をとる。
そこで、積算整理部８１０により各日の積算結果を全用途の消費エネルギーの時刻変動の形として整理する。
又、合計平均処理部８２０により、その月平均の時刻変動や日合計値等の合計値・平均値を整理する。
統計値処理部８３０により、設計時に必要となる平均値やピーク値などの統計値を整理する。
【００８０】
出力部９００は、用途別消費エネルギー積算部７００の各積算部７３０，７４０，７５０，７６０，７７０にて計算された集合住宅における消費エネルギーの時刻変動、積算整理部８１０にて計算された全用途の消費エネルギーの時刻変動、合計平均処理部８２０にて計算された月平均の時刻変動や日合計値等の合計値・平均値、並びに、統計値処理部８３０にて計算された平均値やピーク値などの統計値を、ディスプレイ６やプリンタ７に出力する。
図２８は、全用途の消費エネルギーの時刻変動の出力例を示し、図２９は、消費電力の日合計値の変化及び分布、並びに、消費電力のピーク値の出力例を示す。
【００８１】
次に、消費エネルギー積算用プログラム部Ｐ２全体の処理手順について、図２２ないし図２５の夫々にて示すフローチャートに基づいて説明する。
図２２に示すように、条件入力部５００にて、キーボード３やマウス４を通じて入力される特性条件を入力処理する特性条件入力処理を実行し、住戸特性割り当て部６００にて、条件入力部５００にて入力された住戸特性割り当て条件に基づき、各住戸について、住戸プラン、配置条件、家族特性、在宅特性、暖房条件、冷房条件、電気エネルギー消費特性、給湯エネルギー消費特性及び厨房ガス消費特性の各割り当て条件を割り当てる住戸特性割り当て処理を実行し、用途別消費エネルギー積算部７００にて、電気、給湯、厨房ガス、暖房及び冷房の用途別に消費エネルギーを積算する用途別消費エネルギー積算処理を実行し、計算結果整理部８００にて、用途別の消費エネルギー積算結果を整理する計算結果整理処理を実行し、出力部９００にて、用途別消費エネルギー積算部７００や計算結果整理部８００の計算結果をディスプレイ６やプリンタ７に出力する出力処理を実行する。
【００８２】
図２３に示すように、特性条件入力処理は、図２６に示す如き基本入力画面に基づいて必須の特性条件を入力する必須条件入力処理、及び、必須条件以外の特性条件を入力する詳細条件入力処理を実行し、図２６に示す如き基本入力画面における「計算開始」ボタンがクリックされると、必須条件が全て入力されているか否かを判別して、必須条件が全て入力されているときはリターンし、入力されていないときは、残りの必須条件が入力されるのを待つ。
【００８３】
図２４に示すように、住戸特性割り当て処理は、住戸プラン、配置条件、家族特性、在宅特性、暖房条件、冷房条件、電気エネルギー消費特性、給湯エネルギー消費特性及び厨房ガス消費特性の各割り当て条件のうち、特性条件入力処理にて入力された特性条件を、計算対象の集合住宅の全住戸について割り当てる処理を実行する。但し、空き住戸については、割り当てない。
【００８４】
図２５に示すように、用途別消費エネルギー積算処理は、日特性生成部７１０にて、データベース部Ｂから計算対象日の年月日より日特性としての季節と曜日を決定すると共に日特性としてのその日の天候に関する気象条件を読み込む日特性生成処理を実行し、在宅状況生成部７２０にて、入居各住戸の在宅特性および日特性にしたがってモンテカルロ法により在宅状況を決定する在宅状況生成処理を実行し、電気積算部７３０、給湯積算部７４０、厨房ガス積算部７５０暖房積算部７６０及び冷房積算部７７０にて、電気、給湯、厨房用ガス、暖房及び冷房の各用途別に１日の消費エネルギーを積算する処理を全入居住戸について終了するまで繰り返し、全入居住戸について終了すると、計算対象期間すべての計算が終了していなければ、次の日に移り、再び日特性生成処理から１日の消費エネルギー積算のループを繰り返し、計算対象期間が終了すれば、用途別消費エネルギー積算処理を終了する。
【００８５】
上記のように構成したエネルギー消費シミュレーションシステムにおいて、住宅のエネルギー消費関連の実測データであるエネルギー消費関連実測データを入力する入力手段Ｉは、キーボード３、演算処理部１、及び、データ作成用プログラム部Ｐ１のデータ入力部２００にて構成してある。
又、入力手段Ｉに入力されたエネルギー消費関連実測データを予め定められている分類条件に基づいて分類する分類手段Ｃは、演算処理部１、及び、データ作成用プログラム部Ｐ１の分類部３４０，４４０にて構成してある。
又、分類手段Ｃにて分類されたエネルギー消費関連実測データを分類条件毎に記録する記憶手段Ｒは、演算処理部１、記録用プログラム部１００、及び、記憶部２にて構成してある。
又、在宅特性を類推する在宅特性類推手段Ｈは，演算処理部１、及び、データ作成用プログラム部Ｐ１の在宅特性類推部３２０にて構成してある。
又、エネルギー消費特性を類推する消費特性類推手段Ｓは、演算処理部１、及び、データ作成用プログラム部Ｐ１の消費特性類推部３３０にて構成してある。
又、前処理手段Ｔは、演算処理部１、及び、データ作成用プログラム部Ｐ１の実測データ前処理部３１０にて構成してある。
又、入力手段Ｉに入力された空調用エネルギー消費関連の実測データから空調使用時間帯及び設定室温を求める使用条件抽出手段Ａは、演算処理部１、及び、データ作成用プログラム部Ｐ１の使用条件抽出部４１０にて構成してある。
又、その使用条件抽出手段Ａにて求められた空調使用時間帯及び設定室温に基づいて、所定の熱負荷計算プログラムにより空調用エネルギー消費量を求める消費エネルギー計算手段Ｋは、演算処理部１、及び、データ作成用プログラム部Ｐ１の消費エネルギー計算部４３０にて構成してある。
【００８６】
〔別実施形態〕
次に別実施形態を説明する。
（イ） 本発明の住宅のエネルギー消費量演算用データ作成装置ＤＥにて複数のエネルギー用途（エネルギーの種類に相当する）のエネルギー消費関連実測データを処理するに当たって、エネルギー用途は上記の実施形態において例示した用途に限定されるものではなく、上記の実施形態において例示した用途から一部を省略したり、あるいは、風呂用ガス用途等、新たな用途を追加しても良い。
あるいは、１種類のエネルギー用途のエネルギー消費関連実測データを処理するように構成しても良い。
あるいは、ガス全体の消費量と電気全体の消費量の２つのデータを処理するように構成しても良い。
【００８７】
（ロ） 特性条件及び分類条件の夫々は、上記の実施形態において例示したものに限定されるものではなく、上記の実施形態において例示したものから一部を省略しても良く、その場合、特性条件及び分類条件夫々は１種類になっても良く、あるいは、所得層、職業、立地（都心、郊外）等の新たなものを追加しても良い。
【００８８】
（ハ） 上記の実施形態において、前処理手段Ｔを省略して、厨房用ガス関連実測データとして厨房用ガス消費量の実測データを、及び、給湯関連実測データとして給湯熱負荷の実測データを入力して、それらの入力データそのものを、分類手段Ｃにて分類条件毎に分類するように構成しても良い。
【００８９】
（ニ） 上記の実施形態においては、本発明を集合住宅のエネルギー消費量予測のためのデータ作成用に適用する場合について例示したが、戸建て住宅のエネルギー消費量予測のためのデータ作成用にも適用することが可能である。
【００９０】
（ホ） エネルギー消費量演算用データ作成装置ＤＥの各種処理を実行するデータ作成用プログラム部Ｐ１及び記録用プログラム部１００や、エネルギー消費量演算装置ＣＥの各種処理を実行する消費エネルギー積算用プログラム部Ｐ２は、演算処理部１により、インターネット等のウェブを介してダウンロードして記憶部２に記録するように構成しても良い。
【００９１】
（ヘ） 上記の実施形態においては、本発明による住宅のエネルギー消費量演算用データ作成装置ＤＥを、集合住宅用のエネルギー消費量演算装置ＣＥを共に備えた集合住宅用エネルギー消費量シミュレーションシステムにて提供する場合について例示したが、住宅のエネルギー消費量演算用データ作成装置ＤＥ単独で供給することができる。
【図面の簡単な説明】
【図１】 実施形態に係る住宅のエネルギー消費量演算用データ作成装置を備えた集合住宅用エネルギー消費シミュレーションシステムのブロック図
【図２】 集合住宅用エネルギー消費シミュレーションシステムのプログラムの構成を説明する図
【図３】 電気・厨房用ガス・給湯関係の基本データ整理部の構成を説明する図
【図４】 空調関係の基本データ整理部の構成を説明する図
【図５】 データ作成用プログラム部のフローチャートを示す図
【図６】 厨房用ガス関連実測データの基本データ整理処理のフローチャートを示す図
【図７】 給湯関連実測データの基本データ整理処理のフローチャートを示す図
【図８】 電気関連実測データの基本データ整理処理のフローチャートを示す図
【図９】 空調関連実測データの基本データ整理処理のフローチャートを示す図
【図１０】 厨房用前処理を説明する図
【図１１】 給湯用前処理を説明する図
【図１２】 在宅特性の類推を説明する図
【図１３】 エネルギー消費特性の類推を説明する図
【図１４】 消費エネルギー積算用プログラム部の構成を説明する図
【図１５】 条件入力部の構成を示す図
【図１６】 用途別消費エネルギー積算部の構成を説明する図
【図１７】 電気積算部の構成を説明する図
【図１８】 給湯積算部の構成を説明する図
【図１９】 厨房ガス積算部の構成を説明する図
【図２０】 暖房積算部及び冷房積算部の構成を説明する図
【図２１】 計算結果整理部の構成を説明する図
【図２２】 消費エネルギー積算用プログラム部のフローチャートを示す図
【図２３】 特性条件入力処理のフローチャートを示す図
【図２４】 住戸特性割り当て処理のフローチャートを示す図
【図２５】 用途別消費エネルギー積算処理のフローチャートを示す図
【図２６】 基本入力画面を示す図
【図２７】 割り当て例を示す表示画面の図
【図２８】 計算結果の出力例を示す図
【図２９】 計算結果の出力例を示す図
【符号の説明】
Ａ 使用条件抽出手段
Ｃ 分類手段
Ｉ 入力手段
Ｈ 在宅特性類推手段
Ｋ 消費エネルギー計算手段
Ｒ 記憶手段
Ｓ 消費特性類推手段
Ｔ 前処理手段[0001]
BACKGROUND OF THE INVENTION
  The present invention provides a data creation device for calculating energy consumption of a house.In placeRelated.
[0002]
[Prior art]
  In designing the heat source of detached houses and apartment houses and in-house equipment design, the energy consumption of the house is evaluated, but the data creation device for calculating the energy consumption of the house according to the present invention is The data used when predicting the energy consumption of a house is created.
  As a data creation device for calculating energy consumption of a house, input means for inputting actual energy consumption data obtained by actually measuring energy consumption of each energy consuming device installed in the house, and energy input by the input means It is conceivable to provide storage means for storing consumption actual measurement data.
  And when predicting the energy consumption of the house, by reading the energy consumption actual measurement data corresponding to each energy consuming device installed in the prediction target house from the storage means, by adding each read data, The energy consumption of a house will be calculated.
[0003]
[Problems to be solved by the invention]
  By the way, the energy consumption in a house is affected by a characteristic condition representing the characteristic of energy consumption (hereinafter sometimes simply referred to as a characteristic condition).
  As the characteristic condition, for example, there is a home characteristic indicating a home situation of the residents, and a home having a long home time tends to consume more energy than a home having a short home time.
  In addition, as a characteristic condition, there is an energy consumption characteristic indicating the degree of energy consumption of a house.
  Therefore, when predicting the energy consumption of a house, each house to be predicted has characteristic conditions specific to each house, so the energy consumption is predicted in a state that matches the characteristic conditions specific to the house to be predicted. There is a need to.
[0004]
  However, conventionally, the energy consumption actual measurement data obtained by actually measuring the energy consumption of each energy consuming device is merely stored in the storage means. Therefore, the energy consumption actual measurement data stored in the storage means is I do not know whether the data is in a house with such a characteristic condition.
  Therefore, in the past, when estimating the energy consumption of a house, it is not known what characteristic conditions the data used to predict the energy consumption is for a house. The consumption cannot be determined in a state that matches the characteristic condition of the energy consumption prediction target house, and thus the energy consumption cannot be predicted in a state that is suitable for the prediction target apartment house.
[0005]
  The present invention has been made in view of such circumstances, and the purpose thereof is data for calculating energy consumption of a house capable of creating data that can predict energy consumption in a state suitable for the house to be predicted. CreationPlaceIt is to provide.
[0006]
[Means for Solving the Problems]
  [Invention of Claim 1]
  The characteristic configuration of the data creation device for calculating energy consumption of a house according to claim 1 is:
  An input means for inputting energy consumption-related measured data, which is measured data related to energy consumption of a house,
  Classification means for classifying the energy consumption related actual measurement data input to the input means based on a predetermined classification condition; and
  Storage means is provided for recording the energy consumption related actual measurement data classified by the classification means for each classification condition.,
A plurality of types of energy consumption related actual measurement data are input to the input means,
The classification means is configured to classify each of the plurality of types of energy consumption-related actual measurement data input to the input means based on classification conditions predetermined for each type,
The storage means is configured to record each type of energy consumption related actual measurement data classified by the classification means for each classification condition,
The classifying means includes actual measurement data related to kitchen gas consumption, actual measurement data related to energy consumption for hot water supply, and measurement data related to energy consumption for hot water supply among the plurality of types of actual measurement data related to energy consumption input to the input means. And each of the measured data of power consumption other than for air conditioning are configured to be classified for each of the classification conditions including home characteristics, energy consumption characteristics, family characteristics, and daily characteristics,
Home property analogy means for analogizing the home property is provided,
The home characteristic analogy means determines the presence or absence of energy consumption for kitchen or hot water supply based on the actual measurement data related to gas consumption for kitchen or the actual consumption data related to energy consumption for hot water supply. When there is energy consumption, it is configured so that it can be inferred that it is at home, and when it is not, it is absent.
  According to the housing energy consumption calculation data creation device according to claim 1, when the energy consumption-related actual measurement data that is the actual energy consumption-related measurement data of the house is input by the input means, the classification means inputs the input means. The input energy consumption related actual measurement data is classified based on a predetermined classification condition, and the energy consumption related actual measurement data classified by the classification means is recorded for each classification condition by the storage means.
  The energy consumption-related actual measurement data includes actual energy consumption data in each house, information on characteristic conditions obtained by a questionnaire survey on the house from which the actual measurement data was measured, and the like.
  That is, the classification condition is set in advance corresponding to the characteristic condition. Then, the energy consumption related actual measurement data is input by the input means, and the energy consumption related actual measurement data input to the input means by the classification means is converted into the energy consumption related actual measurement data based on a predetermined classification condition. The data is classified in association with the measured characteristic condition corresponding to the house, and the energy consumption related actual measurement data classified by the classification means is recorded for each classification condition by the storage means.
  Therefore, when predicting the energy consumption of a house, the energy consumption related actual measurement data classified under the classification condition corresponding to the characteristic condition of the house to be predicted is read from the storage means, and based on the read data The energy consumption of the house will be calculated, but the energy consumption of the house is matched to the prediction target house by determining the energy consumption of the house in a state matching the characteristic condition of the target house. It becomes what can be obtained in the state.
  By the way, when predicting the energy consumption of a detached house, we will read the energy consumption related measured data corresponding to the classification condition corresponding to the characteristic condition of the detached house, and obtain the energy consumption, and When predicting the total energy consumption of an apartment house, calculate the energy consumption of each house in the apartment house by reading the energy consumption-related measured data corresponding to the characteristic conditions of each house, and integrating the calculated energy consumption of each house By doing so, the total energy consumption of the apartment will be calculated, but the energy consumption-related measured data corresponding to the characteristic conditions of the house is used for both the detached house and the apartment house. Since the consumption is calculated, that is, the energy consumption of the house is predicted, the energy of the house It becomes that can be obtained in a state where costs quantity conforming to the prediction target housing.
  In order to make it possible to determine the energy consumption of a house in a state suitable for the house to be predicted, energy consumption-related actual measurement data, action schedules for each resident of the house, equipment used, frequency of use, etc. When you ask for the energy consumption of the houseRow ofIt may be possible to read actual data related to energy consumption based on conditions such as dynamic schedule, equipment used, frequency of use, etc., but the conditions such as action schedule, equipment used, frequency of use etc. for each resident of the house It is quite cumbersome to input, especially when predicting the energy consumption of apartment buildings, it is quite difficult to enter conditions such as the action schedule, equipment used, frequency of use, etc. It becomes complicated. On the other hand, the invention of claim 1 classifies the energy consumption related data in correspondence with the characteristic conditions of each house, and the characteristic conditions of each house are more than various conditions for each resident. For example, the number of input items can be reduced, making it possible to make conditions difficult to input. Therefore, when predicting the energy consumption of an apartment house, enter the characteristic conditions for all the houses. Even so, it can be less time-consuming than entering various conditions for each resident, and it is easier to use to predict the energy consumption of an apartment house..
Then, a plurality of types of energy consumption-related actual measurement data are input from the input means, and each of the plurality of types of energy consumption-related actual measurement data input to the input means is determined in advance corresponding to each type by the classification means. Each type of energy consumption related actual measurement data classified by the classification means and recorded by the classification means is recorded for each classification condition. In other words, for example, energy consumption-related actual measurement for each energy application (corresponding to the type of energy) such as electricity (other than hot water supply, heating and cooling, hereinafter also referred to as general electricity), kitchen, hot water supply, heating and cooling. Since each of the data is classified and recorded in the storage means based on a predetermined classification condition corresponding to each energy use, the energy consumption of the house for each energy use is estimated for the target house. It can be determined in accordance with the characteristic conditions.
Therefore, it has become possible to create data that can predict the energy consumption for each energy application in a state suitable for the house to be predicted. This effect is referred to as the first housing compatibility effect.
Further, actual measurement data related to kitchen gas consumption, actual measurement data related to energy consumption for hot water supply, and actual measurement of power consumption other than for kitchen use, hot water supply and air conditioning (hereinafter sometimes referred to as general power consumption). Each of the data is classified by the classification means based on classification conditions including at-home characteristics, energy consumption characteristics, family characteristics, and daily characteristics, and recorded in the storage means.
In other words, with regard to energy consumption related to kitchen gas consumption, hot water supply energy consumption and general power consumption, the characteristics of staying at home (indicating length of staying at home), energy consumption characteristics (indicating the amount of energy consumption), occupancy It is relatively susceptible to characteristic conditions such as personal characteristics (indicating family structure, etc.) and day characteristics (indicating weekdays, holidays, seasons, weather, etc.). Therefore, the actual measurement data related to kitchen gas consumption, the actual measurement data related to energy consumption for hot water supply, and the actual measurement data of general power consumption are classified based on classification conditions including home characteristics, energy consumption characteristics, family characteristics, and daily characteristics. Thus, by storing the data in the storage means, the energy consumption related to kitchen gas consumption, energy consumption related to hot water supply, and general power consumption related to the home characteristics, energy consumption characteristics, family characteristics in the target housing In addition, according to the characteristic conditions including the daily characteristics, it can be obtained in a state that is more realistic.
Therefore, it has become possible to create data that can predict energy consumption amounts related to kitchen gas consumption, hot water supply energy consumption, and general power consumption in a state that is more suitable for the house to be predicted. This effect is referred to as a second housing compatibility effect.
Then, the home characteristic analogy means discriminates the presence or absence of energy consumption for kitchen or hot water supply based on the actual measurement data related to gas consumption for kitchen or the actual consumption data related to energy consumption for hot water supply. The home characteristics can be obtained by analogy with home when there is consumption and absence when there is no consumption.
In other words, energy consumption for kitchen use or hot water supply usually does not occur unless there are residents living in the house. Therefore, it is possible to analogize home characteristics based on energy consumption for kitchens or hot water supply.
Therefore, there is no need to bother obtaining information relating to the at-home characteristics of the house from which the actual measurement data was obtained as the actual energy consumption measurement data.
That is, it is not necessary to bother obtaining information related to at-home characteristics as energy consumption-related actual measurement data, and the work of creating data for predicting the energy consumption of a house can be simplified.
[0007]
[Invention of Claim 2]
  The characteristic configuration of the data creation device for calculating energy consumption of a house according to claim 2 is:
An input means for inputting energy consumption-related measured data, which is measured data related to energy consumption of a house,
Classification means for classifying the energy consumption related actual measurement data input to the input means based on a predetermined classification condition; and
Storage means for recording the energy consumption related actual measurement data classified by the classification means for each classification condition is provided,
  A plurality of types of energy consumption related actual measurement data are input to the input means,
  The classification means is configured to classify each of the plurality of types of energy consumption-related actual measurement data input to the input means based on classification conditions predetermined for each type,
  The storage means is configured to record each type of energy consumption related actual measurement data classified by the classification means for each classification condition.,
The classifying means includes actual measurement data related to kitchen gas consumption, actual measurement data related to energy consumption for hot water supply, and measurement data related to energy consumption for hot water supply among the plurality of types of actual measurement data related to energy consumption input to the input means. And each of the measured data of power consumption other than for air conditioning are configured to be classified for each of the classification conditions including home characteristics, energy consumption characteristics, family characteristics, and daily characteristics,
Consumption characteristic analogy means for analogizing the energy consumption characteristic is provided,
The consumption characteristic analogy means is based on the measured data related to the consumption of gas for the kitchen, the measured data related to the energy consumption for hot water supply, and the measured data of the power consumption, respectively, Analogize the energy consumption characteristics of each power consumptionThat is to be configured.
  According to the data creation device for calculating energy consumption of a house according to claim 2,In addition to obtaining the above-mentioned first housing conformity effect and second housing conformity effect, consumption characteristic analogy means can be used to measure actual measurement data related to gas consumption for kitchens, actual measurement data related to energy consumption for hot water supply, and general power consumption. Based on the actual measurement data, the energy consumption characteristics of the kitchen gas consumption, the hot water supply energy consumption, and the power consumption are estimated according to the amount of each consumption.
In other words, based on the actual measurement data related to kitchen gas consumption, the actual consumption data related to energy consumption for hot water supply, and the actual measurement data of general power consumption itself, the energy consumption characteristics of each of gas consumption for kitchen, energy consumption for hot water supply, and general power consumption Therefore, it is not necessary to bother obtaining information related to the energy consumption characteristics of the house from which the measured data was obtained as the energy consumption-related measured data.
Accordingly, there is no need to bother acquiring information related to energy consumption characteristics as energy consumption-related actual measurement data, and the work of creating data for predicting the energy consumption of a house can be simplified.
[0008]
[Invention of Claim 3]
  The characteristic configuration of the data creation device for calculating energy consumption of a house according to claim 3 is:An input means for inputting energy consumption-related measured data, which is measured data related to energy consumption of a house,
Classification means for classifying the energy consumption related actual measurement data input to the input means based on a predetermined classification condition; and
Storage means for recording the energy consumption related actual measurement data classified by the classification means for each classification condition is provided,
A plurality of types of energy consumption related actual measurement data are input to the input means,
The classification means is configured to classify each of the plurality of types of energy consumption-related actual measurement data input to the input means based on classification conditions predetermined for each type,
The storage means is configured to record each type of energy consumption related actual measurement data classified by the classification means for each classification condition,
  The classifying means includes actual measurement data related to gas consumption for kitchen use, actual measurement data related to energy consumption for hot water supply, and measurement data related to energy consumption for hot water supply among the plurality of types of actual measurement data related to energy consumption input to the input means. And the measured data of power consumption other than for air conditioning are classified according to the classification conditions including home characteristics, energy consumption characteristics, family characteristics, and daily characteristics.,
Gas consumption actual measurement data indicating the relationship between gas consumption and time is input to the input means as the energy consumption related actual measurement data,
Pre-processing means for performing pre-processing for separating the gas consumption for kitchen from the gas consumption actual measurement data input to the input means is provided,
The classification means is configured to classify the gas consumption for the kitchen separated for the kitchen by the preprocessing means based on the classification conditions as actual measurement data related to the gas consumption for the kitchen,
The pre-processing means is
In the gas consumption actual measurement data, a data portion in a gas consumption time zone shorter than a set time is provisionally determined as a kitchen gas consumption amount, and a data portion in a gas consumption time zone longer than the set time is temporarily determined as a heating temporary determination data portion Tentatively determined as
Subsequently, when the time of the data portion tentatively determined as the kitchen gas consumption corresponds to the kitchen work time, the data portion is determined as the kitchen gas consumption and does not correspond to the kitchen work time Determines the data portion as heating gas consumption, and
In the data obtained by determining the minimum gas consumption amount in the heating temporary determination data portion from the heating temporary determination data portion and subtracting the minimum gas consumption amount from the temporary heating determination data portion, the gas shorter than the set time The data portion of the consumption time zone is determined as the kitchen gas consumption, and when there is a data portion of the gas consumption time zone that is longer than the set time, the minimum gas consumption in the data portion is determined from the data portion and The operation of determining the data portion of the gas consumption time zone shorter than the set time in the obtained data as the gas consumption for the kitchen by reducing the minimum gas consumption, and all the gas consumption time zones are shorter than the set time. Repeat untilIt is in the configuration.
  According to the data creation device for calculating energy consumption of a house according to claim 3,In addition to being able to obtain the first housing conformity effect and the second housing conformity effect described above, the gas consumption actual measurement data indicating the relationship between gas consumption and time is input to the input means as energy consumption related actual measurement data. The processing means determines the kitchen gas consumption based on the actual gas consumption data input to the input means, and the classification means determines that the kitchen gas consumption determined by the preprocessing means is related to the kitchen gas consumption. The measured data is classified based on the classification condition.
In other words, kitchen gas consumption has characteristics such as shorter gas use time, large fluctuations in gas consumption, and concentration of gas consumption time compared to gas consumption for heating. Based on this feature, the gas consumption for kitchen can be obtained by separating the gas consumption for kitchen from the actual gas consumption data as follows.
That is, the set time is set to a predetermined threshold value between the gas consumption time for kitchen and the gas consumption time for heating.
Then, in the gas consumption actual measurement data, the data portion in the gas consumption time zone shorter than the set time is provisionally determined as the kitchen gas consumption amount, and the data portion in the gas consumption time zone longer than the set time is temporarily determined as the heating temporary determination data portion. Is temporarily determined.
Subsequently, when the time of the data portion tentatively determined as the kitchen gas consumption corresponds to the kitchen work time, the data portion is determined as the kitchen gas consumption and does not correspond to the kitchen work time Determines the data portion as the heating gas consumption.
Subsequently, the minimum gas consumption in the temporary determination data portion for heating is determined from the temporary determination data portion for heating, and the gas consumption shorter than the set time in the data obtained by subtracting the minimum gas consumption from the temporary determination data portion for heating is used. If the data part in the time zone is determined as the gas consumption for the kitchen and there is a data part in the gas consumption time period that is longer than the set time, the minimum gas consumption in the data part is determined from the data part and the minimum gas consumption is determined. Decrease consumption, repeat the operation of determining the data portion of the gas consumption time zone shorter than the set time as the kitchen gas consumption in the obtained data until all the gas consumption time zones are shorter than the set time, The data portion of the gas consumption time period shorter than the set time is determined as the kitchen gas consumption.
By the way, the gas consumption of the section where the gas consumption is the smallest among the sections where the change of the gas consumption becomes substantially constant in the section of the set gas consumption or more set corresponding to the minimum input of the gas equipment, The minimum gas consumption is determined.
In this case, the gas consumption for the kitchen and the heating can be obtained based on the actual gas consumption data obtained by measuring the gas consumption for the kitchen and the heating in one place. There is no need to measure consumption separately.
In other words, because it is possible to determine the gas consumption for the kitchen based on the gas consumption actual measurement data obtained by collectively measuring the gas consumption for each of the kitchen and the heating in one place, for predicting the energy consumption of the house The work of creating data can be simplified.
[0009]
[Invention of Claim 4]
  The characteristic configuration of the data creation device for calculating energy consumption of a house according to claim 4 is:
An input means for inputting energy consumption-related measured data, which is measured data related to energy consumption of a house,
Classification means for classifying the energy consumption related actual measurement data input to the input means based on a predetermined classification condition; and
Storage means for recording the energy consumption related actual measurement data classified by the classification means for each classification condition is provided,
A plurality of types of energy consumption related actual measurement data are input to the input means,
The classification means is configured to classify each of the plurality of types of energy consumption-related actual measurement data input to the input means based on classification conditions predetermined for each type,
The storage means is configured to record each type of energy consumption related actual measurement data classified by the classification means for each classification condition,
The classifying means includes actual measurement data related to kitchen gas consumption, actual measurement data related to energy consumption for hot water supply, and measurement data related to energy consumption for hot water supply among the plurality of types of actual measurement data related to energy consumption input to the input means. And each of the measured data of power consumption other than for air conditioning are configured to be classified for each of the classification conditions including home characteristics, energy consumption characteristics, family characteristics, and daily characteristics,
As the measured data related to energy consumption for hot water supply, the amount of hot water supplied from the hot water supply device and the hot water supply temperature, and the amount of water supplied and the water supply temperature to be mixed with the hot water from the hot water supply device are input to the input means. And
Based on the measured amount of hot water supplied to the input means, the hot water supply temperature, the amount of water supplied, and the actual measured data of the water supply temperature, the amount of hot water supplied and the amount of water supplied are determined as hot water consumption, and Pretreatment means is provided for performing a pretreatment for obtaining a hot water heat amount by adding a product of the hot water supply amount and the hot water supply temperature and a product of the water supply amount and the water supply temperature,
The classification means classifies the hot water consumption and the hot water amount obtained by the preprocessing means for each classification condition.It is in the configuration.
  According to the data creation device for calculating energy consumption of a house according to claim 4,In addition to obtaining the first housing conformity effect and the second housing conformity effect described above, the measured data related to energy consumption for air conditioning is classified by the classification means for each classification condition including building characteristics, daily characteristics, and regional characteristics. And recorded in the storage means.
That is, the energy consumption related to air conditioning is relatively susceptible to characteristic conditions such as building conditions, air conditioning conditions (indicating air conditioning usage time zone, set temperature, etc.), daily characteristics and regional characteristics. Therefore, by classifying measured data related to energy consumption for air conditioning based on classification conditions including building conditions, air conditioning conditions, daily characteristics, and regional characteristics, and recording them in the storage means, the energy consumption related to air conditioning Can be obtained in a state that is more realistic in accordance with the characteristic conditions including the building conditions, the air conditioning conditions, the daily characteristics, and the regional characteristics in the house to be predicted.
Therefore, it has become possible to create data that can predict the energy consumption related to air conditioning in a state that is more suitable for the house to be predicted.
The input means inputs the hot water supply amount and hot water supply temperature from the hot water supply device and the water supply amount and water supply temperature of the water supplied to be mixed with the hot water from the hot water supply device as the actual measurement data related to the energy consumption for hot water supply. Based on the measured hot water amount, hot water supply temperature, water supply amount, and water supply temperature input to the input means, the processing means obtains the hot water consumption and the water supply amount as hot water consumption, and A pretreatment is performed to obtain a hot water heat amount obtained by adding the product of the hot water supply temperature and the product of the water supply amount and the water supply temperature, and the hot water consumption and hot water amount obtained by the pretreatment means are determined by the classification means. It is classified for each classification condition.
In other words, conventionally, the energy consumption of hot water has been handled in the form of either “hot water heat load (heat amount: J)” or “hot water consumption (volume: L)”. Because it is affected by temperature and the temperature of the water supply that varies depending on the region / season, when predicting the energy consumption for hot water supply based on “hot water heat load” or “hot water consumption”, The energy consumption could not be predicted in a state suitable for the house.
Therefore, as actual measurement data related to energy consumption for hot water supply, “hot water consumption (volume: L)” and “hot water heat (heat: J)” obtained by preprocessing as described above are recorded in the storage means. Then, based on the water supply temperature and hot water supply temperature of the prediction target house, it can be converted into a form such as a hot water supply heat load, so it is possible to predict the energy consumption for hot water supply in a state suitable for the prediction target house It can be done.
Therefore, it has become possible to create data capable of predicting the energy consumption for hot water supply in a state that is more suitable for the house to be predicted.
[0010]
[Invention of Claim 5]
  The characteristic configuration of the data creation device for calculating energy consumption of a house according to claim 5 is:
An input means for inputting energy consumption-related measured data, which is measured data related to energy consumption of a house,
Classification means for classifying the energy consumption related actual measurement data input to the input means based on a predetermined classification condition; and
Storage means for recording the energy consumption related actual measurement data classified by the classification means for each classification condition is provided,
A plurality of types of energy consumption related actual measurement data are input to the input means,
The classification means is configured to classify each of the plurality of types of energy consumption-related actual measurement data input to the input means based on classification conditions predetermined for each type,
The storage means is configured to record each type of energy consumption related actual measurement data classified by the classification means for each classification condition,
The classification means includes, for each of the classification conditions including building characteristics, daily characteristics, and regional characteristics, air conditioning energy consumption-related measured data among the plurality of types of energy consumption-related measured data input to the input means. Configured to classify,
Use condition extraction means for obtaining an air conditioning use time zone and a set room temperature from the measured data related to energy consumption for air conditioning input to the input means;
Energy consumption calculating means for determining the energy consumption for air conditioning by a predetermined heat load calculation program based on the air conditioning usage time zone and the set room temperature obtained by the use condition extracting means is provided,
The classification means classifies the energy consumption for air conditioning obtained by the energy consumption calculation means based on the classification conditions.That is to be configured.
  According to the data creation device for calculating energy consumption of a house according to claim 5,In addition to obtaining the above-mentioned first housing conformity effect, the air conditioning energy consumption-related measured data is classified by the classification means for each classification condition including building characteristics, daily characteristics, and regional characteristics, and stored in the storage means. To be recorded.
That is, the energy consumption related to air conditioning is relatively susceptible to characteristic conditions such as building conditions, air conditioning conditions (indicating air conditioning usage time zone, set temperature, etc.), daily characteristics and regional characteristics. Therefore, by classifying measured data related to energy consumption for air conditioning based on classification conditions including building conditions, air conditioning conditions, daily characteristics, and regional characteristics, and recording them in the storage means, the energy consumption related to air conditioning Can be obtained in a state that is more realistic in accordance with the characteristic conditions including the building conditions, the air conditioning conditions, the daily characteristics, and the regional characteristics in the house to be predicted.
Then, the use condition extraction means obtains the air conditioning use time zone and the set room temperature from the air conditioning energy consumption-related actual measurement data input to the input means, and the consumption energy calculation means obtains the use condition extraction means. Based on the air conditioning usage time zone and the set room temperature, the energy consumption for air conditioning is obtained by a predetermined heat load calculation program, and the energy consumption for air conditioning obtained by the energy consumption calculating means is classified by the classification means for each classification condition. Based on the classification.
In other words, the amount of energy consumed for air conditioning depends on the main orientation of the house, the arrangement condition of the wife or the middle, the characteristic conditions related to the building conditions such as the floor, the wall specifications, the housing area, the characteristic conditions related to the weather conditions, etc. It is easily affected by many kinds of characteristic conditions.
On the other hand, in order to predict the amount of energy consumed for air conditioning in a state that is suitable for various types of forecasted houses, it is necessary to obtain measured data under a number of conditions that combine a variety of characteristic conditions. The work takes a lot of time and effort.
Therefore, the air conditioning usage time zone and the set room temperature are obtained as actual measurement data from the actual measurement data related to energy consumption for air conditioning, and the existing general building conditions are obtained, and the air conditioning usage time zone and the set room temperature obtained as the actual measurement data are obtained. A large number of calculation conditions based on combinations of building conditions and weather conditions obtained in advance are set. Then, when building conditions and weather conditions are given, air conditioning for each of the calculation conditions is performed by a predetermined heat load calculation program that can determine the energy consumption for air conditioning necessary to keep the temperature inside the building constant. Energy consumption for air conditioning in a state suitable for each house for houses with various characteristic conditions by determining the energy consumption for use and recording the storage conditions for each classification condition as the above-mentioned calculation conditions. Can be sought.
Therefore, it is possible to reduce the effort required to obtain actual measurement data related to energy consumption for air conditioning, and to simplify the work of creating data for predicting the energy consumption of a house. .
[0011]
DETAILED DESCRIPTION OF THE INVENTION
  Hereinafter, the case where the embodiment of the present invention is applied for data creation for predicting energy consumption of an apartment will be described with reference to the drawings.
  FIG. 1 shows an energy consumption simulation system for collective housing (hereinafter, referred to simply as an energy consumption calculation data creation device) (hereinafter, simply referred to as an energy consumption calculation data creation device) according to the present invention. The energy consumption simulation system includes an energy consumption calculation device CE (hereinafter referred to as an energy consumption calculation device CE) in addition to the energy consumption calculation data creation device DE. May be simply referred to as an energy consumption calculation device).
[0012]
  As shown in FIG. 1, the energy consumption simulation system includes an arithmetic processing unit 1 configured using a microcomputer, a storage unit 2 built in the arithmetic processing unit 1 for recording various information, and a keyboard 3 for inputting various information. And a mouse 4, a reading unit 5 that reads information from the information recording medium M, a display 6 that outputs various information, a printer 7, and the like as main components. As the information recording medium M, there are various types such as FD, CD, DVD, MO, etc., but the reading unit 5 is provided corresponding to the type (for example, CD) of the information recording medium M.
[0013]
  The storage unit 2 includes a data creation program unit P1 that executes various processes of the energy consumption calculation data creation device DE, a consumption energy integration program unit P2 that executes various processes of the energy consumption calculation device CE, and A program comprising a recording program unit 100 that records information processed by the data creation program unit P1 as a database unit B in the storage unit 2 is recorded. The arithmetic processing unit 1 is recorded in the storage unit 2 The information input from the keyboard 3 and mouse 4, the information read by the reading unit 5 and the information recorded in the storage unit 2 are variously processed by the program, and the processing result is stored in the database unit B. Or output to the display 6 or the printer 7.
[0014]
  Each program of the data creation program unit P1, the energy consumption integration program unit P2, and the recording program unit 100 is provided by being recorded in the information recording medium M, and the program is read by the reading unit 5 to store the program. Record in 2.
[0015]
  In short, in the data creation program part P1, the energy consumption-related actual measurement data of each dwelling unit of the apartment house input from the keyboard 3 or the like is classified based on predetermined classification conditions, and the database part is used as basic data. B is recorded for each classification condition. The classification condition corresponds to the characteristic condition indicating the characteristic of energy consumption of each house in the apartment, and the basic data classified based on the classification condition and recorded in the database unit B corresponds to the energy consumption related information, Based on the characteristic conditions inputted from the keyboard 3 and the mouse 4 and the basic data recorded in the database part B, the energy consumption program part P2 obtains the energy consumption consumed within the set period for each house. Then, the calculated energy consumption of each house is integrated for all the houses to determine the total energy consumption of the apartment house, and the calculated total energy consumption is output through the display 6 or the printer 7.
  The energy consumption related actual measurement data includes actual energy consumption data in each dwelling unit and information on characteristic conditions obtained by a questionnaire survey for each dwelling unit.
[0016]
  First, the energy consumption calculation data creation device DE will be described.
  As shown in FIG. 2, the data creation program unit P1 includes a data input unit 200, a basic data organizing unit 300 related to electricity / kitchen gas and hot water supply, and a basic data organizing unit 400 related to air conditioning.
  The data input unit 200 is configured to input and process energy consumption related measurement data for a plurality of uses through the keyboard 3 or the like. The basic data organizing unit 300 related to electricity / kitchen gas / hot water supply is input to the input unit 200. Among energy consumption-related measurement data for multiple applications, measurement data related to electricity consumption other than for kitchen, hot water supply, and air conditioning (hereinafter may be abbreviated as electricity-related measurement data), and gas consumption related to kitchen Each of the actual measurement data (hereinafter sometimes abbreviated as kitchen gas-related actual measurement data) and hot water supply energy-related actual measurement data (hereinafter sometimes abbreviated as hot-water supply related actual measurement data), It is configured to classify according to classification conditions including energy consumption characteristics, occupant characteristics (corresponding to family characteristics) and daily characteristics. 00 is configured to classify the air conditioning energy consumption related measurement data (hereinafter referred to as air conditioning related measurement data) input to the data input unit 200 for each classification condition including building characteristics, daily characteristics, and regional characteristics. is there.
[0017]
  The data input unit 200 is input with actual energy consumption data corresponding to dates as energy consumption-related actual measurement data for a plurality of uses (corresponding to a plurality of types) of each dwelling unit. Residential area, resident characteristics indicating the family structure of each unit, building conditions (main orientation, arrangement of wife or middle, floor plan, unit plan indicating unit area, etc.), heating and cooling hours And the information obtained by the questionnaire survey about the set temperature and the like is input. In addition, as a family structure, for example, in the case of a single person, a couple and a child, the husband is a worker, the wife is a full-time housewife family, a dual working family, an elderly family, and the like.
  Gas consumption actual measurement data indicating the relationship between gas consumption and time is input as kitchen-related actual measurement data.
  In addition, the hot water supply amount and the hot water supply temperature from the hot water supply device and the water supply amount and the water supply temperature of the water supplied to be mixed with the hot water from the hot water supply device are input as the hot water supply related measurement data in a state in which they are associated with time. Is done.
  In addition, the electric power consumption except for hot water supply and air conditioning is input as electric related actual measurement data in a state associated with time.
  Further, as the air conditioning related actual measurement data, the consumed energy amount is input in a state associated with time, and the set temperature for air conditioning is input.
[0018]
  The basic data organizing unit 300 related to electricity, kitchen gas, and hot water supply will be described.
  The basic data organizing unit 300 related to electricity, kitchen gas, and hot water supply basically cuts out the measured values in the actual measurement period one day for each dwelling unit and converts it into a form that eliminates the influence of the region and year The arrangement is different depending on the usage of electricity, kitchen gas and hot water supply.
  As shown in FIGS. 2 and 3, the basic data organizing unit 300 related to electricity, kitchen gas, and hot water supply includes an actual data preprocessing unit 310 that preprocesses energy consumption related actual measurement data input to the data input unit 200. Home characteristic analogy unit 320 for analogizing the home characteristics of the calculation target dwelling unit, consumption characteristic analogy unit 330 for analogizing the energy consumption characteristic of the calculation target dwelling unit, energy consumption related measurement data input to the data input unit 200 or previous Classification processing based on pre-classified conditions such as home characteristics, energy consumption characteristics, occupant characteristics, and daily characteristics using pre-processed data obtained by pre-processing energy consumption-related actual measurement data in the processing unit 310 as organizing data And a classifying unit 340.
[0019]
  The actual measurement data pre-processing unit 310 executes a pre-process for kitchen for pre-processing the gas-related actual measurement data for kitchen and a pre-treatment for hot water supply for pre-processing the hot water-related actual measurement data. Therefore, electrical measurement data other than for hot water supply and air conditioning will be used as they are without pre-processing, but electrical measurement data other than for hot water supply and air conditioning will be less affected by the season and region. The data can be used as it is.
[0020]
  A description will be given of kitchen pretreatment.
  Kitchen pretreatment is based on the fact that kitchen gas consumption has the following characteristics when compared to heating gas consumption.
・ Gas usage time is short
  Heating is used continuously for a long time in one day, whereas kitchen is often used intermittently in a short time.
-Large fluctuations in gas consumption
  While heating is relatively stable, kitchen use has a large fluctuation during use time.・ Concentration of time distribution
  Heating is used for a long time over a wide time zone in one day, whereas kitchen use tends to concentrate in a certain time zone in one day.
[0021]
  Based on the above-described characteristics of kitchen gas consumption, the gas consumption for kitchen is separated from the actual gas consumption data in the following steps 1-4. Accordingly, the actual gas consumption data includes gas consumption amounts for the kitchen and heating, and does not include gas consumption other than for kitchen and heating.
  Step 1: Noise elimination by moving average
  The gas consumption measurement data is subjected to several-order moving averages to remove short-term fluctuations contained in the measured values.
[0022]
  Step 2: Tentative judgment of individual consumption
  Assuming that each individual consumption is for a single kitchen and heating, a provisional judgment of the action is made. Temporarily classify individual gas consumptions that are temporally continuous based on the knowledge in the non-heating period regarding gas consumption for kitchens. In other words, when the usage time is shorter than the set time ts, which is a threshold value between the kitchen and the heating, provisional determination is made for the kitchen and when the usage time is longer, respectively. The set time ts is set to about 1 hour, for example.
[0023]
  Step 3: Determine the use of the act temporarily determined to be for kitchen use
  If the characteristics of the kitchen work time appear in the gas use time temporarily determined to be for kitchen use, it is determined for kitchen use. Otherwise, it is judged for heating.
  Step 4: Separation and determination of provisional judgment data portion for heating provisionally judged for heating
  As shown to (A)-(C) of FIG. 10, in the temporary determination data part for heating, there exists a thing with the thing for heating independent, and the thing for heating and kitchen use overlapping.
  First, from the time variation of consumption in the heating temporary determination data part, if the variation is small, it is determined that the heating is independent. If the fluctuation is large, it is determined that heating and kitchen use are mixed, and individual consumption is separated from the overlapping consumption by the following method.
  First, suppose that the heating is almost constant and the kitchen is on top of it. The gas consumption measured is the total for the kitchen and heating as shown in FIG. As shown in FIG. 10D, the minimum gas consumption of the gas consumption within this gas use time is determined and subtracted from the whole. As shown in FIG. 10E, the continuous gas use time is divided into a plurality of gas use times by this operation. Each divided gas use time is compared with the set time ts, and if the time is shorter than this, it is determined that it is for kitchen use, and if it is longer, the minimum gas consumption is determined again as shown in FIG. Then, the operation of decreasing is repeated, and the process ends when all the gas usage times become less than the set time ts. In addition, in the section more than the set gas consumption set corresponding to the minimum input of the gas equipment, the gas consumption of the section where the gas consumption is the smallest among the sections where the change of the gas consumption is substantially constant, Judge as the minimum gas consumption.
  In FIG. 10, t1 and t3 are equal to or less than ts, and t2 is longer than ts.
[0024]
  That is, the actual measurement data preprocessing unit 310 tentatively determines the data portion of the gas consumption time zone shorter than the set time ts in the gas consumption actual measurement data as the kitchen gas consumption amount, and the gas consumption time zone longer than the set time ts. Is temporarily determined as a temporary determination data portion for heating, and when the time of the data portion temporarily determined as the amount of consumption of gas for kitchen corresponds to the kitchen work time, the data portion is determined as the gas for kitchen use. If it is determined as consumption and does not correspond to the kitchen work time, the data portion is determined as the heating gas consumption, and the minimum gas consumption in the heating temporary determination data portion from the heating temporary determination data portion In the data obtained by subtracting the minimum gas consumption from the heating temporary determination data part, the data part in the gas consumption time period shorter than the set time ts is determined as the kitchen gas consumption. When there is a data portion in the gas consumption time zone that is longer than the set time ts, the minimum gas consumption in the data portion is determined from the data portion, and the minimum gas consumption is subtracted. The operation of determining the data portion of the gas consumption time period shorter than ts as the kitchen gas consumption amount is repeated until all the gas consumption time periods become shorter than the set time ts.
[0025]
  Next, a description will be given of hot water pretreatment.
  As shown in FIG. 11, the presence or absence of hot water consumption is determined based on the actual measurement data of water supply at each hour and the actual measurement data of hot water supply from the hot water supply device, and when hot water consumption is present, Assuming that the consumption of water supply is one hot water consumption, the hot water consumption V_yuAnd hot water H_yuAsk for.
[0026]
[Expression 1]
  V_yu= V_water+ V_hot
  H_yu= V_water× T_water+ V_hot× T_hot
[0027]
  However, V_yu: Hot water consumption (L)
        H_yu: Amount of hot water (kJ)
        V_water, V_hot: Amount of water supply, amount of hot water supply (L)
        T_water, T_hot: Water supply temperature, hot water supply temperature
[0028]
  That is, the actual measurement data pre-processing unit 310 obtains the hot water consumption and the hot water consumption as the hot water consumption based on the actual measurement data of the hot water supply amount, the hot water supply temperature, the water supply amount, and the water supply temperature. A pre-processing is performed in which a product obtained by adding the product of the hot water supply temperature and the product of the water supply amount and the water supply temperature is obtained as the hot water heat amount.
[0029]
  The home characteristic analogy unit 320 will be described. The at-home characteristic analogy unit 320 analogizes the at-home condition from the consumption energy generation condition, and determines the at-home condition on the actual measurement date of the actual measurement target unit. As an analogy method, a hot water supply / kitchen gas that does not occur unless there is a person at home is used. If such consumption occurs, the time is assumed to be at home, and if there is no consumption for a long time, it is absent. In this embodiment, as shown in FIG. 12, the at-home characteristic is analogized to six types A to F described later.
[0030]
  The consumption characteristic analogy unit 330 will be described. As shown in FIG. 13, the consumption characteristic analogy unit 330 is based on the daily total amount / monthly total amount of energy consumption for each use and based on the relationship with other dwelling units and literature values. Analogize consumption characteristics. That is, it is assumed that there are four levels for electricity other than for hot water supply and air conditioning, three levels for kitchen gas, and three levels for hot water supply.
[0031]
  The classification unit 340 will be further described. When the input data is kitchen gas-related actual measurement data, the classification unit 340 uses the kitchen gas consumption separated by the actual measurement data preprocessing unit 310 as basic data, the home characteristics, the energy consumption characteristics, the resident characteristics, and the Classification processing based on daily characteristics. Specifically, basic data of time fluctuation of the gas consumption for kitchen (for example, every day at 15 minute intervals) is labeled by home characteristics, energy consumption characteristics, resident characteristics, and daily characteristics.
[0032]
  When the input data is actual measurement data related to hot water supply, classification based on home characteristics, energy consumption characteristics, occupancy characteristics, and daily characteristics, with the hot water consumption and hot water quantity obtained by the actual measurement data preprocessing unit 310 as basic data To process. Specifically, basic data of hot water consumption and hot water heat fluctuation over time (for example, every day at 15-minute intervals) are labeled by home characteristics, energy consumption characteristics, resident characteristics, and daily characteristics.
  When the input data is electricity-related actual measurement data, the power consumption data that is the electricity-related actual measurement data itself is used as basic data, and classification processing is performed based on home characteristics, energy consumption characteristics, resident characteristics, and daily characteristics. Specifically, basic data of time fluctuations of power consumption (for example, every day at 15-minute intervals) are labeled by home characteristics, energy consumption characteristics, resident characteristics, and daily characteristics.
[0033]
  As described above, the day characteristic that is one of the classification conditions for classifying the gas related actual measurement data, the hot water related actual measurement data, and the electricity related actual measurement data by the classification unit 340 is derived from the measurement date of the actual measurement data. Season (for example, spring, summer and winter three conditions) and day of the week (for example, two conditions for holidays and weekdays), as well as weather (for example, sunny, cloudy and rainy) derived from the measurement date of the measured data and meteorological observation data 3 conditions) are included.
[0034]
  The basic data organizing unit 400 related to air conditioning will be described.
  As shown in FIGS. 2 and 4, the air conditioning related basic data organizing unit 400 extracts an air conditioning condition including a time zone for performing air conditioning (heating / cooling) and a set temperature from the air conditioning related actual measurement data. A calculation condition organizing unit 420 that creates a combination of calculation conditions based on the air conditioning conditions extracted by the use condition extracting unit 410, building conditions and weather conditions that are considered to be general, and the calculation condition organizing unit 420 The energy consumption calculation unit 430 for obtaining the energy consumption for air conditioning by a predetermined heat load calculation program for each of the calculation conditions created in the above, and the energy for air conditioning for each calculation condition obtained by the energy consumption calculation unit 430 It comprises a classification unit 440 that classifies each calculation condition as a classification condition using consumption as basic data.
  In addition, the building conditions (including wall specifications, plans, joinery, windows, and layout conditions) that are considered to be general are extracted and organized from the existing building as information required for the basic data organization process for air conditioning-related actual measurement data. And it is memorize | stored in the database part B as a general building condition, and the weather data of the date and time of a calculation object area are also memorize | stored in the database part B.
[0035]
  When the calculation condition rearrangement unit 420 is described further, the calculation condition rearrangement unit 420 calculates the calculation target dwelling unit plan (for example, 60 m as a building condition).²80m², 100m²), Dwelling arrangement conditions (main orientation, wife or middle arrangement, floor) as building conditions, air-conditioning usage time zone pattern (weekdays), air-conditioning usage time zone pattern (holiday), air conditioning set temperature (e.g., 26 ° C, 28 ° C, 30 ° C), a calculation condition is created by a combination of a calculation target area and a calculation target year. The number of combinations is as shown in Equation 2 below.
[0036]
[Expression 2]
C_num= Rplan x Rpos x AS_wday× AS_wend× RT × Rg × Y
[0037]
  C: Number of condition combinations
  Rplan: Number of dwelling unit plans to be calculated
  Rpos: Number of housing units
  AS_wday: Number of air-conditioning usage hours (weekdays)
  AS_wend: Number of air-conditioning usage time patterns (holiday)
  RT: Air conditioning set temperature
  Rg: Number of areas to be calculated
  Y: Number of years subject to calculation
[0038]
  The energy consumption calculation unit 430 will be further described.
  The energy consumption calculation unit 430 calculates the energy consumption of the air conditioner for each calculation condition created by the calculation condition organizing unit 420 using a predetermined thermal load calculation program. As the predetermined thermal load calculation program, for example, a residential thermal load calculation program BRIMAP (see “Housing and Architectural Energy Conservation Organization”) can be used.
  In other words, when building conditions and external weather conditions are given, extensive studies have been conducted over a long period of time on how to calculate the energy (heat load) consumed to keep the room temperature inside the building constant. Since the theory and solution have already been established, only an outline of the indoor heat load calculation will be explained.
[0039]
The amount of heat flowing into the room i from the room j between the adjacent rooms in the building is represented by the following mathematical formula 3. The same formula is used for the portion facing the outside air.
[0040]
[Equation 3]

[0041]
  Since the above formula is used for each room in the building, the problem is a simultaneous equation for the room temperature of each room. The room temperature of each room is calculated by solving the simultaneous equations by the SOR method or the like.
  In a room that is air-conditioned at the calculation target time, the room temperature is determined according to the room temperature setting condition, and the amount of heat necessary to maintain the room temperature at the calculation target time, that is, the air-conditioning heat load is calculated. However, if the air conditioning heat load exceeds the capacity of the air conditioner, the room temperature is recalculated assuming that only the capacity of the air conditioner has been processed. In a room that is not air-conditioned at the calculation target time, the room temperature (natural room temperature) is calculated.
[0042]
  When the classification unit 440 is further described, the classification unit 440 performs classification processing based on the classification condition (corresponding to the calculation condition) with the energy consumption for air conditioning calculated by the energy consumption calculation unit 430 as basic data. Specifically, the basic data of the time variation of the energy consumption for air conditioning (for example, 15 minutes at one day) is labeled with classification conditions. That is, the classification conditions include building characteristics (including dwelling unit plans and arrangement conditions), air conditioning conditions (including set temperature and air conditioning usage time), day characteristics (including weekdays and holidays), and regional characteristics.
[0043]
  The recording program unit 100 will be described. The recording program unit 100 includes the basic data classified by the classification unit 340 of the basic data organizing unit 300 related to electricity, kitchen gas, and hot water supply, and the air conditioning related data. Each basic data classified by the classification unit 440 of the basic data organizing unit 400 is recorded in the database unit B in a state of being classified for each classification condition.
[0044]
  That is, the energy consumption-related actual measurement data classified by the classification units 340 and 440 include the actual measurement data itself, the data obtained by processing the actual measurement data by the actual measurement data preprocessing unit 310, and the actual measurement data as the use condition extraction unit 410 and Data processed by the energy consumption calculation unit 430 is included.
[0045]
  Next, the overall processing procedure of the data creation program part P1 will be described based on the flowcharts shown in FIGS.
  As shown in FIG. 5, in the data input unit 200, kitchen gas-related actual measurement data, hot water supply-related actual measurement data, electricity-related actual measurement data, and air-conditioning-related actual measurement data are each input and processed. When each of hot water supply related measurement data and electricity related measurement data is input, the basic data organizing process for classifying the input data for each classification condition is executed by the basic data organizing unit 300 related to electricity, kitchen gas, and hot water. The recording program unit 100 executes a recording process for recording the classified data in the database unit B for each classification condition, and when the air conditioning related actual measurement data is input, the air conditioning related basic data organizing unit 400 The basic data organizing process for classifying the input data for each classification condition is executed by the recording program unit 100. Executing a recording process of recording for each classification condition database unit B.
[0046]
  As shown in FIG. 6, in the basic data arrangement processing of the actual measurement data related to kitchen gas, the actual data pre-processing unit 310 executes pre-processing for separating the gas consumption for kitchen from the actual gas consumption data. The home characteristic analogy unit 320 analogizes the home characteristic based on the gas consumption actual measurement data, and the consumption characteristic analogy unit 330 analogizes the energy consumption characteristic based on the gas consumption actual measurement data. The daily characteristic derivation process for obtaining the daily characteristic based on the measurement date input together with the actual gas consumption data is executed, and then the classification unit 340 uses the gas consumption for the kitchen as basic data, the home characteristics and the energy consumption characteristics. Then, a classification process for classifying based on the tenant characteristics and the day characteristics is executed.
[0047]
  As shown in FIG. 7, the basic data arrangement processing of the hot water supply related measurement data is performed by the actual measurement data pre-processing unit 310 based on the actual measurement data of the hot water supply at each time and the actual measurement data of the hot water supply from the hot water supply device. Pre-processing for determining the amount of hot water is executed, and then the home characteristic analogy unit 320 analogizes the home characteristic based on the actual gas consumption data, and then the consumption characteristic analogy unit 330 calculates the hot water consumption. Based on the energy consumption characteristics based on the measurement data, the daily characteristics derivation process for obtaining the daily characteristics based on the measurement date input together with the actual measurement data is executed. Subsequently, the classification unit 340 performs hot water consumption and hot water consumption. Based on the amount of heat as basic data, classification processing is performed based on home characteristics, energy consumption characteristics, resident characteristics, and daily characteristics.
[0048]
  As shown in FIG. 8, the basic data arrangement processing of the electrical related actual measurement data is performed by analogizing the home characteristics based on the gas consumption actual measurement data in the home characteristic analogy unit 320, and then in the consumption characteristic analogy unit 330. By analogizing energy consumption characteristics based on the power consumption data, and subsequently performing a daily characteristic derivation process for obtaining the daily characteristics based on the measurement date input together with the actual measurement data, and subsequently in the classification unit 340 The power consumption data itself is used as basic data for classification processing based on home characteristics, energy consumption characteristics, resident characteristics, and daily characteristics.
[0049]
  As shown in FIG. 9, the basic data arrangement processing of the air conditioning related actual measurement data is performed by the use condition extraction unit 410 in the air conditioning related actual measurement data including the actual measurement data with the passage of time of the energy consumption for heating and cooling, the set temperature of the air conditioning, and the like. Air-conditioning condition extraction processing for extracting the air-conditioning conditions including the time zone for air conditioning and the set temperature.
  Subsequently, general building conditions are read out, and then, in the calculation condition organizing unit 420, the calculation target dwelling unit plan, dwelling unit arrangement conditions, air conditioning usage time zone pattern (weekdays), air conditioning usage time zone pattern (holiday), Calculation condition arrangement processing is executed to arrange calculation conditions according to a combination of the set temperature of the air conditioning, the calculation target area, and the calculation target year.
  Subsequently, while reading the weather conditions of the region / date of calculation target, the energy consumption calculation unit 430 executes energy consumption calculation processing for calculating the energy consumption of the air conditioner on the day of the calculation target day. When the calculation for the day ends, the calculation of the energy consumption of the air conditioning equipment for one day on the next calculation target day is repeated until the calculation target period ends, and when the calculation for the calculation target period ends, the classification unit 440 Then, a classification process for classifying each calculation condition as a classification condition is executed.
  The basic data arrangement process of the air conditioning-related actual measurement data is executed for all combinations of target areas and all calculation conditions.
[0050]
  Next, the energy consumption calculation device CE will be described.
  As shown in FIGS. 2 and 14, the energy consumption calculation program unit P2 that executes various processes of the energy consumption calculation device CE includes a condition input unit 500, a dwelling unit characteristic assignment unit 600, a use-specific consumption energy integration unit 700, The calculation result organizing unit 800 and the output unit 900 are configured.
[0051]
  The condition input unit 500 is configured to input and process the characteristic conditions input through the keyboard 3 and the mouse 4, and the dwelling unit characteristic assignment unit 600 calculates the characteristic conditions input by the condition input unit 500 and is an apartment for calculation. The consumption energy integrating unit 700 for each use is a database for each energy use (corresponding to the type of energy) based on the characteristic condition assigned to each dwelling unit by the dwelling unit characteristic assigning unit 600. Select the basic data that meets the characteristic conditions for each unit from Part B, accumulate for each unit, determine the energy consumption consumed within the set period, and further calculate the energy consumption for each unit by energy usage. It is configured to calculate the total energy consumption of the apartment by dividing up, and the calculation result organizing unit 800 uses the energy consumption product by application. The total energy consumption for each energy use obtained in the unit 700 is arranged in various ways to be useful, and the output unit 900 displays the data arranged in the calculation result arranging unit 800 on the display 6 or the printer. 7 is output.
[0052]
  The condition input unit 500 will be described based on FIG. The condition input unit 500 includes an essential condition input unit 510 and a detailed condition input unit 520 in order to reduce the burden on the input person.
  The indispensable condition input unit 510 executes an input process of characteristic conditions that are indispensable for integration and can be easily checked for each apartment house. The input person must input all characteristic conditions.
  The detailed condition input unit 520 executes input processing of conditions that are important but cannot be easily checked by the input person, such as the in-home situation of the residents and energy consumption characteristics.
[0053]
  The essential condition input unit 510 includes a calculation target year input unit 511 for inputting a calculation target year, a calculation region input unit 512 for inputting a calculation target region, a dwelling number input unit 513 for inputting the number of dwelling units of a calculation target apartment, and a calculation target About the occupancy rate input unit 514 that inputs the proportion of dwelling units that are actually inhabited in apartment buildings, and the combination of dwelling unit conditions consisting of the dwelling unit plan (floor area), main orientation, and floor of each dwelling unit in the calculation target apartment From the dwelling unit condition input unit 515 for inputting the number of dwelling units corresponding to each combination, and the family characteristic input unit 516 for inputting the family characteristics of residents expected to move in at a ratio to the total number of dwelling units in the housing complex for each family characteristic. It is configured.
[0054]
  The detailed condition input unit 520 is a home characteristic input unit 521 that inputs the daily home characteristics of the resident unit, and heating that inputs the heating characteristics of each dwelling unit (period of use throughout the year, each use time zone on weekdays and holidays). Condition input unit 522, cooling condition input unit 523 for inputting the cooling characteristics of each dwelling unit (period of use throughout the year, each use time zone on weekdays and holidays), energy consumption in electric energy consumption other than for hot water supply and air conditioning An electric condition input unit 524 that inputs characteristics, a hot water supply condition input unit 525 that inputs energy consumption characteristics in hot water supply, and a kitchen gas condition input unit 526 that inputs energy consumption characteristics in kitchen gas.
[0055]
  The condition input unit 500 displays a basic input screen as shown in FIG. 26 on the display 6, and executes each input process using the input basic screen.
  The calculation target year input unit 511, the calculation region input unit 512, the dwelling unit input unit 513, and the occupancy rate input unit 514 each execute data input processing on this basic input screen.
[0056]
  The dwelling unit condition input unit 515 displays a dwelling unit condition input screen (not shown) on the display 6 when the “set dwelling unit setting” button is clicked on the basic input screen, and displays the dwelling unit plan (floor area), main direction / Input processing of the number of dwelling units of each dwelling unit condition combination consisting of floor arrangement conditions is executed. That is, the dwelling unit condition input unit 515 inputs the dwelling unit plan and arrangement condition assignment conditions as the dwelling unit characteristic assignment conditions for assigning the characteristic conditions to each dwelling unit.
[0057]
  When the “entry unit family configuration” button is clicked on the basic input screen, the family characteristic input unit 516 displays a family configuration input screen (not shown) on the display 6 and displays “single person”, “couple + child”. A process is executed in which the number of dwelling units corresponding to each family characteristic such as “wife is a full-time housewife”, “married couple + children working together”, and “elderly family” is input as a ratio to the total number of tenants. That is, the family characteristic input unit 516 includes family characteristics such as “single person”, “couple + child with wife and full-time housewife”, “couple + child working together”, and “elderly family” as conditions for assigning dwelling unit characteristics. The assignment conditions for family characteristics are entered.
[0058]
  When the “set home status” button is clicked on the family composition input screen, the at-home characteristic input unit 521 displays a home status input screen (not shown) on the display 6 and displays “all day” for each weekday and holiday. Corresponds to each of the six patterns A to F: “Available in the room”, “Out of the day for a short time”, “Out of the day for a long time”, “Absence in the afternoon”, “Absence in the morning”, and “Absence all day” The process which inputs the number of dwelling units in the ratio with respect to the total number of occupancy is performed. In other words, the home property input unit 521 inputs home property assignment conditions including six patterns A to F for weekdays and holidays as the residence unit property assignment conditions.
[0059]
  When the “heating related” button is clicked on the basic input screen, the heating condition input unit 522 displays a heating usage status input screen (not shown) on the display 6 and inputs the heating usage period throughout the year. For each weekday and holiday, the number of dwelling units corresponding to each usage time zone and the number of dwelling units corresponding to each set temperature are input in a ratio to the total number of occupants. That is, the heating condition input unit 522 inputs the allocation condition of the heating condition (corresponding to the air conditioning condition) composed of each use time zone on weekdays and the set temperature as the dwelling unit characteristic allocation condition.
  When the “cooling relation” button is clicked on the basic input screen, the cooling condition input unit 523 displays a cooling use status input screen (not shown) on the display 6 and inputs the cooling use period throughout the year. For each weekday and holiday, the number of dwelling units corresponding to each usage time zone and the number of dwelling units corresponding to each set temperature are input in a ratio to the total number of occupants. That is, the cooling condition input unit 523 inputs the allocation condition of the cooling condition (corresponding to the air conditioning condition) composed of each use time zone on weekdays and the set temperature as the dwelling unit characteristic allocation condition.
[0060]
  When the “electrical” button is clicked on the basic input screen, the electrical condition input unit 524 displays an electrical energy consumption characteristic input screen (not shown) on the display 6 to display “multiple consumption type”, “quasi-multiple”. A process of inputting the number of dwelling units corresponding to the electricity-related energy consumption characteristics of “consumption type”, “standard type”, and “saving type” by the ratio to the total number of occupants is executed. In other words, the electric condition input unit 524 inputs the electric energy consumption characteristic assignment condition including “multi-consumption type”, “semi-multi-consumption type”, “standard type”, and “saving type” as the dwelling unit characteristic assignment condition. .
[0061]
  When a “hot water supply related” button is clicked on the basic input screen, the hot water supply condition input unit 525 displays a hot water supply related energy consumption characteristic input screen (not shown) on the display 6 to display “multi-consumption type” and “standard type”. ”And“ saving type ”, a process of inputting the number of dwelling units corresponding to the energy consumption characteristics in a ratio to the total number of dwelling units is executed. That is, the hot water supply condition input unit 525 inputs hot water energy consumption characteristic assignment conditions of “multi-consumption type”, “standard type”, and “saving type” as dwelling unit characteristic assignment conditions.
[0062]
  When the “kitchen relation” button is clicked on the basic input screen, the kitchen gas condition input unit 526 displays a kitchen-related energy consumption characteristic input screen (not shown) on the display 6 to display “multi-consumption type” and “standard”. A process of inputting the number of dwelling units corresponding to the energy consumption characteristics of each of the “type” and “saving type” in the ratio to the total number of dwelling units is executed. That is, the kitchen gas condition input unit 526 inputs kitchen gas consumption characteristic allocation conditions including “multi-consumption type”, “standard type”, and “saving type” as the dwelling unit characteristic allocation conditions.
[0063]
  The dwelling unit characteristic assignment unit 600 will be described. The dwelling unit property allocation unit 600 is based on the dwelling unit property allocation conditions input by the condition input unit 500, and for each dwelling unit, the dwelling unit plan, arrangement conditions, family characteristics, home characteristics, heating conditions, cooling conditions, electrical energy consumption characteristics, Each allocation condition of hot water supply energy consumption characteristic and kitchen gas consumption characteristic is assigned. In the condition input unit 500, in order to simplify the input, the allocation condition for each item is input as a ratio to the total number of dwelling units that apply to each type. In this dwelling unit characteristic allocation unit 600, the individual dwelling unit is calculated from this ratio. One type is assigned to one house by the Monte Carlo method. FIG. 27 shows an example of assignment.
[0064]
  The Monte Carlo method assigns one characteristic value (parameter) according to the probability of generating a random number using a computer, and since it is well known, a detailed description will be omitted and only a brief description will be given below. .
  P₁・ P₂~ P_n: Occurrence probability (0 to 1) of each of types 1 to n related to characteristics (characteristic assignment condition)
  Ran: If it is a uniformly distributed random number (takes an arbitrary number between 0 and 1), then the one that satisfies the mathematical formula shown in the following equation 4 among k satisfying 1 ≦ k ≦ n. It becomes the type assigned to the dwelling unit (k type).
[0065]
[Expression 4]

[0066]
  Based on FIG. 16, the usage-specific energy consumption integrating unit 700 will be described. The usage-specific energy consumption accumulation unit 700 determines the season and day of the week as the day characteristic from the date of the calculation target date, and reads the weather condition as the day characteristic relating to the weather of the day from the database unit B. , A home status generation unit 720 that determines the home status by the Monte Carlo method according to the home characteristics and the daily characteristics of each resident, a power integration unit 730 that integrates energy consumption related to electricity, a hot water supply integration unit 740 that integrates energy consumption related to hot water supply, It is composed of a kitchen gas integrating unit 750 that integrates consumption energy related to kitchen gas, a heating integration unit 760 that integrates energy consumption related to heating, and a cooling integration unit 770 that integrates energy consumption related to cooling.
[0067]
  As shown in FIG. 17, for the calculation target dwelling on the calculation target date, the electricity integrating unit 730 first sets the characteristic conditions of the day characteristic, the at-home characteristic, and the electric energy consumption characteristic including the day of the week / season / weather in the condition selection unit 731. Organize and select basic data that conforms to all the characteristic conditions from the electrical relationship in the database part B. When there are a plurality of basic data that meet the characteristic conditions, the random selection unit 732 selects one basic data at random based on the Monte Carlo method. In the basic data, the time variation of the power consumption is recorded, and this variation is accumulated by the electricity consumption integrating unit 733 for all the dwelling units.
  As a result, it is possible to accumulate daily fluctuations that affect all dwelling units, and to accumulate time fluctuations in power consumption taking into consideration daily randomness, taking into account the characteristics at home and energy consumption characteristics. It becomes.
[0068]
  As shown in FIG. 18, the hot water supply integration unit 740 first sets the characteristic conditions of the day characteristics, the home characteristics, and the hot water energy consumption characteristics of the day of the week / season / weather in the condition selection unit 741 for the calculation target dwelling on the calculation target date. Organize and select basic data that conforms to all the characteristic conditions from the hot water supply relationship in the database part B. When there are a plurality of basic data that meet the characteristic conditions, the random selection unit 742 selects one basic data at random based on the Monte Carlo method. Since the basic data records the time variation of the hot water consumption and the hot water amount, the hot water supply heat load calculation unit 744 uses the hot water consumption and the hot water amount based on the feed water temperature calculated by the feed water temperature calculation unit 743. The hot water supply heat load, which is the actual energy consumption, is calculated, and the time fluctuation of the hot water supply heat load is accumulated by the hot water supply energy consumption integration unit 745 for all the dwelling units.
[0069]
  In addition, the feed water temperature calculation part 743 estimates a feed water temperature based on the estimation formula of the feed water temperature from external temperature. The formula for estimating the temperature of the water supply from the outside air temperature has already been proposed by the “Study Committee on Examination and Maintenance of Basic Data for Hot Water Supply Equipment Design” and the Air Conditioning and Sanitation Engineering Society. There are several forms for the estimation formula, but in the present embodiment, a linear single regression equation shown in the following equation 5 is used with only the outside air temperature of the day as an explanatory variable.
[0070]
[Equation 5]
  T_water= A_i× T_air+ B_i
[0071]
  However, T_Water: Estimated water supply temperature
        T_air: Outside temperature on the calculation day in the calculation target area
        a_i, B_i: Coefficient in region I (in Tokyo, a_i= 0.8516, b_i= 2.473)
[0072]
  However, in apartment houses, water is often stored in a water tank once inside the plant, so the water supply temperature tends to increase throughout the year. Therefore, in this embodiment, the temperature increase correction coefficient C for the whole year of the plant._plantAnd the following mathematical formula 6 is used.
[0073]
[Formula 6]
  T_water= A_i× T_air+ B_i+ C_plant
[0074]
Moreover, the hot water supply heat load calculation unit 744 calculates the hot water supply heat load according to the following equation (7).
[0075]
[Expression 7]
  H_load= H_yu-(V_yu× T_water) × 4.2
[0076]
  However, H_load: Hot water supply heat load [kJ]
        H_yu: Calorie of hot water (kJ)
        V_yu: Hot water consumption (L)
[0077]
  As shown in FIG. 19, the kitchen gas integrating unit 750 first sets the condition conditions of the day characteristics, home characteristics, and kitchen gas consumption characteristics of the day of the week / season / weather in the condition selection section 751 for the calculation target dwelling on the calculation target date. And basic data that meets all the characteristic conditions are selected from the kitchen gas relations in the database part B. When there are a plurality of basic data that meet the characteristic conditions, the random selection unit 752 selects one basic data at random based on the Monte Carlo method. In the basic data, the time fluctuation of the kitchen gas consumption is recorded, and the time fluctuation of the kitchen gas consumption is accumulated by the kitchen gas consumption integration unit 753 over all the dwelling units.
[0078]
  Since the heating integration unit 760 and the cooling integration unit 770 are the same, they will be described together with reference to FIG.
  It is determined whether or not the calculation target date is within the air conditioning period input by the condition input unit 500. If it is not the calculation period, the calculation proceeds to the next day. Next, from the at-home characteristics of the calculation target dwelling unit, the calculation shifts to the next dwelling unit, assuming that no energy consumption for air conditioning has occurred on that day if it is an absent day. If the calculation target date is during the air conditioning period and there is no calculation target dwelling unit, the condition selection units 761 and 771 select basic data based on the assumption that energy consumption for air conditioning has occurred. Based on the air conditioning conditions (air conditioning usage time zone, set room temperature), dwelling unit plan, arrangement conditions, and the area where the calculation target apartment is located, basic data that matches the combination of the conditions is selected from the air conditioning relationship of the database B. Unlike other applications, there is only one basic data that matches one condition combination.
  In the basic data, the calculation result of the air-conditioning-related energy consumption under a certain condition combination on the calculation target date is recorded in the form of time fluctuation. The selected basic data is accumulated by the air-conditioning consumption energy integrating units 762 and 772 corresponding to all the dwelling units on the calculation target date.
[0079]
  The calculation result organizing unit 800 will be described based on FIG. The calculation result organizing unit 800 is the time variation of the energy consumption in the apartment house calculated by each of the integrating units 730, 740, 750, 760, 770 of the above-described usage-specific energy integrating unit 700 (in this embodiment, every 15 minutes) ) And summarize as useful calculation results.
  The result of integration by the energy consumption integration unit 700 for each application takes the form of time fluctuations in the energy consumption of all the dwelling units in the calculation target apartment on each day during the calculation period.
  Therefore, the summarizing unit 810 sorts the summation results for each day as a form of time variation of energy consumption for all uses.
  Further, the total average processing unit 820 arranges the total value / average value such as the monthly average time fluctuation and the daily total value.
  The statistical value processing unit 830 organizes statistical values such as average values and peak values required during design.
[0080]
  The output unit 900 is the time variation of the energy consumption in the apartment house calculated by the integrating units 730, 740, 750, 760, and 770 of the energy consumption integrating unit 700 for each use, and all uses calculated by the integrating and arranging unit 810. Fluctuations in energy consumption, monthly average time fluctuations calculated by the total average processing unit 820, total values / average values such as daily total values, and average values and peaks calculated by the statistical value processing unit 830 Statistical values such as values are output to the display 6 and the printer 7.
  FIG. 28 shows an output example of time fluctuations of consumed energy for all uses, and FIG. 29 shows an output example of changes and distribution of daily total values of power consumption and peak values of power consumption.
[0081]
  Next, the processing procedure of the entire energy consumption program unit P2 will be described based on the flowcharts shown in FIGS.
  As shown in FIG. 22, the condition input unit 500 executes a characteristic condition input process for inputting a characteristic condition input through the keyboard 3 or the mouse 4, and the dwelling unit characteristic assignment unit 600 executes the condition input unit 500. For each dwelling unit, each allocation of the dwelling unit plan, layout conditions, family characteristics, home characteristics, heating conditions, cooling conditions, electrical energy consumption characteristics, hot water energy consumption characteristics, and kitchen gas consumption characteristics Executes the dwelling unit characteristic assignment process for assigning conditions, and executes the consumption energy integration process for each use in the application-specific consumption energy integration unit 700 to integrate the energy consumption for each use of electricity, hot water supply, kitchen gas, heating and cooling. The result organizing unit 800 executes a calculation result organizing process for organizing the energy consumption result for each application, and outputs the output unit 9 At 0, it executes the output processing for outputting the calculation result of the application-specific energy consumption accumulating unit 700 and the calculation result summarizer 800 to a display 6 and a printer 7.
[0082]
  As shown in FIG. 23, the characteristic condition input process includes an essential condition input process for inputting an essential characteristic condition based on a basic input screen as shown in FIG. 26, and a detailed condition input for inputting a characteristic condition other than the essential condition. When the process is executed and the “calculation start” button on the basic input screen as shown in FIG. 26 is clicked, it is determined whether or not all the essential conditions are entered. Return and wait for the remaining required conditions to be entered if not entered.
[0083]
  As shown in FIG. 24, the dwelling unit property assignment process is performed for each assignment condition of a dwelling unit plan, arrangement conditions, family characteristics, home characteristics, heating conditions, cooling conditions, electrical energy consumption characteristics, hot water supply energy consumption characteristics, and kitchen gas consumption characteristics. Among them, the process of assigning the characteristic condition input in the characteristic condition input process to all the dwelling units of the apartment house to be calculated is executed. However, vacant dwelling units are not allocated.
[0084]
  As shown in FIG. 25, the energy consumption processing for each application uses the day characteristic generation unit 710 to determine the season and day of the week as the day characteristic from the date of the calculation target date from the database part B, and as the day characteristic. The daily characteristic generation process for reading the weather conditions related to the weather of the day is executed, and the at-home condition generation unit 720 executes the at-home condition generation process for determining the at-home condition by the Monte Carlo method according to the at-home characteristic and the day characteristic of each resident unit. Electricity integration unit 730, hot water supply integration unit 740, kitchen gas integration unit 750, heating integration unit 760, and cooling integration unit 770 integrate the daily energy consumption for each usage of electricity, hot water supply, kitchen gas, heating, and cooling. Repeat until the process is completed for all occupancy units, and for all occupancy units, if all calculations for the calculation period have not been completed, Moved to the day of repeated consumption energy accumulated in the loop of the day again from day characteristic generation process, calculation target period if completed, and terminates the application-specific energy consumption accumulation process.
[0085]
  In the energy consumption simulation system configured as described above, the input means I for inputting the energy consumption related actual measurement data which is the actual data related to the energy consumption of the house includes the keyboard 3, the arithmetic processing unit 1, and the data creation program unit. The data input unit 200 of P1 is used.
  Further, the classification means C for classifying the energy consumption related actual measurement data input to the input means I based on a predetermined classification condition includes an arithmetic processing unit 1 and a classification unit 340 of the data creation program unit P1. 440 is configured.
  The storage means R for recording the energy consumption related actual measurement data classified by the classification means C for each classification condition is composed of the arithmetic processing unit 1, the recording program unit 100, and the storage unit 2.
  The home characteristic analogy means H for analogizing the home characteristic is constituted by the arithmetic processing unit 1 and the home characteristic analogy unit 320 of the data creation program unit P1.
  The consumption characteristic analogy means S for estimating the energy consumption characteristic is constituted by the calculation processing unit 1 and the consumption characteristic analogy unit 330 of the data creation program unit P1.
  The preprocessing means T is constituted by the arithmetic processing unit 1 and the actual measurement data preprocessing unit 310 of the data creation program unit P1.
  The use condition extraction means A for obtaining the air conditioning use time zone and the set room temperature from the air conditioning energy consumption-related measured data input to the input means I is the use condition of the arithmetic processing unit 1 and the data creation program unit P1. The extraction unit 410 is configured.
  The energy consumption calculation means K for obtaining the energy consumption for air conditioning by a predetermined heat load calculation program based on the air conditioning use time zone and the set room temperature obtained by the use condition extraction means A is the arithmetic processing unit 1, And it is comprised in the energy consumption calculation part 430 of the program part P1 for data creation.
[0086]
    [Another embodiment]
  Next, another embodiment will be described.
(A) In processing energy consumption-related measured data for a plurality of energy applications (corresponding to the types of energy) in the energy creation calculation data DE for residential energy consumption calculation according to the present invention, the energy application is performed in the above embodiment The application is not limited to the exemplified application, and a part of the application exemplified in the above embodiment may be omitted, or a new application such as a bath gas application may be added.
  Or you may comprise so that the energy consumption related actual measurement data of one type of energy use may be processed.
  Or you may comprise so that two data of consumption of the whole gas and consumption of the whole electricity may be processed.
[0087]
(B) Each of the characteristic conditions and the classification conditions is not limited to those exemplified in the above embodiment, and a part may be omitted from those exemplified in the above embodiment. Each condition and classification condition may be one type, or new ones such as income group, occupation, location (city center, suburb) may be added.
[0088]
(C) In the above embodiment, the pretreatment means T is omitted, and the actual measurement data of the kitchen gas consumption is input as the actual measurement data related to the kitchen gas, and the actual measurement data of the hot water supply heat load is input as the actual measurement data related to the hot water supply Then, the input data itself may be classified by the classification means C for each classification condition.
[0089]
(D) In the above embodiment, the case where the present invention is applied to the creation of data for predicting the energy consumption of an apartment is illustrated, but also for the creation of data for predicting the energy consumption of a detached house. It is possible to apply.
[0090]
(E) A data creation program unit P1 and a recording program unit 100 that execute various processes of the energy consumption calculation data creation device DE, and a consumption energy integration program unit that executes various processes of the energy consumption calculation device CE P2 may be configured to be downloaded by the arithmetic processing unit 1 via the web such as the Internet and recorded in the storage unit 2.
[0091]
(F) In the above embodiment, the residential energy consumption calculation data creation device DE according to the present invention is a collective housing energy consumption simulation system equipped with an energy consumption calculation device CE for multiple dwellings. Although illustrated about the case where it provides, it can supply by the data preparation apparatus DE for energy consumption calculation of a house independently.
[Brief description of the drawings]
FIG. 1 is a block diagram of an energy consumption simulation system for an apartment house provided with a data creation device for calculating energy consumption of a house according to the embodiment.
FIG. 2 is a diagram for explaining a program configuration of an energy consumption simulation system for an apartment house
FIG. 3 is a diagram for explaining the configuration of a basic data organizing unit related to electricity, kitchen gas and hot water supply.
FIG. 4 is a diagram for explaining the configuration of an air conditioning-related basic data organizing unit
FIG. 5 is a flowchart showing a data creation program unit.
FIG. 6 is a flowchart showing basic data arrangement processing of kitchen-related actual measurement data for kitchens
FIG. 7 is a diagram showing a flowchart of basic data arrangement processing of hot water related measurement data
FIG. 8 is a view showing a flowchart of basic data arrangement processing of electricity-related actual measurement data
FIG. 9 is a flowchart showing basic data organization processing of air conditioning related measurement data
FIG. 10 is a diagram for explaining pre-processing for kitchens
FIG. 11 is a diagram illustrating hot water pretreatment
FIG. 12 is a diagram for explaining analogy of at-home characteristics
FIG. 13 illustrates an analogy of energy consumption characteristics
FIG. 14 is a diagram for explaining the configuration of a program unit for energy consumption accumulation
FIG. 15 is a diagram showing a configuration of a condition input unit
FIG. 16 is a diagram for explaining the configuration of an energy consumption accumulator by application
FIG. 17 is a diagram for explaining the configuration of an electric integrator
FIG. 18 is a diagram for explaining the configuration of a hot water supply integration unit
FIG. 19 is a diagram illustrating the configuration of a kitchen gas integrating unit
FIG. 20 is a diagram illustrating the configuration of a heating integration unit and a cooling integration unit
FIG. 21 is a diagram for explaining the configuration of a calculation result organizing unit
FIG. 22 is a diagram showing a flowchart of a program unit for energy consumption accumulation
FIG. 23 shows a flowchart of a characteristic condition input process.
FIG. 24 is a diagram showing a flowchart of dwelling unit property assignment processing.
FIG. 25 is a diagram showing a flowchart of energy consumption integration processing by application.
FIG. 26 shows a basic input screen.
FIG. 27 is a diagram of a display screen showing an allocation example.
FIG. 28 is a diagram showing an output example of calculation results
FIG. 29 is a diagram showing an output example of calculation results
[Explanation of symbols]
  A Use condition extraction means
  C Classification means
  I Input means
  H Home characteristics analogy means
  K Energy consumption calculation means
  R storage means
  S Consumption characteristics analogy means
  T Pretreatment means

Claims (5)

An input means for inputting energy consumption-related measured data, which is measured data related to energy consumption of a house,
Classification means for classifying the energy consumption related actual measurement data input to the input means based on a predetermined classification condition; and
Storage means for recording the energy consumption related actual measurement data classified by the classification means for each classification condition is provided ,
A plurality of types of energy consumption related actual measurement data are input to the input means,
The classification means is configured to classify each of the plurality of types of energy consumption-related actual measurement data input to the input means based on classification conditions predetermined for each type,
The storage means is configured to record each type of energy consumption related actual measurement data classified by the classification means for each classification condition,
The classifying means includes actual measurement data related to kitchen gas consumption, actual measurement data related to energy consumption for hot water supply, and measurement data related to energy consumption for hot water supply among the plurality of types of actual measurement data related to energy consumption input to the input means. And each of the measured data of power consumption other than for air conditioning are configured to be classified for each of the classification conditions including home characteristics, energy consumption characteristics, family characteristics, and daily characteristics,
Home property analogy means for analogizing the home property is provided,
The home characteristic analogy means determines whether or not there is energy consumption for kitchen or hot water supply based on the measured data related to gas consumption for kitchen or the measured data related to energy consumption for hot water supply. A data creation device for calculating energy consumption of a house, which is configured to analogize home when there is energy consumption and absence when there is no energy consumption. An input means for inputting energy consumption-related measured data, which is measured data related to energy consumption of a house,
Classification means for classifying the energy consumption related actual measurement data input to the input means based on a predetermined classification condition; and
Storage means for recording the energy consumption related actual measurement data classified by the classification means for each classification condition is provided,
A plurality of types of energy consumption related actual measurement data are input to the input means,
The classification means is configured to classify each of the plurality of types of energy consumption-related actual measurement data input to the input means based on classification conditions predetermined for each type,
The storage means is configured to record each type of energy consumption related actual measurement data classified by the classification means for each classification condition ;
The classifying means includes actual measurement data related to kitchen gas consumption, actual measurement data related to energy consumption for hot water supply, and measurement data related to energy consumption for hot water supply among the plurality of types of actual measurement data related to energy consumption input to the input means. And each of the measured data of power consumption other than for air conditioning are configured to be classified for each of the classification conditions including home characteristics, energy consumption characteristics, family characteristics, and daily characteristics,
Consumption characteristic analogy means for analogizing the energy consumption characteristic is provided,
The consumption characteristic analogy means is based on the measured data related to the consumption of gas for the kitchen, the measured data related to the energy consumption for hot water supply, and the measured data of the electric power consumption, respectively. A data creation device for calculating energy consumption of a house configured to analogize energy consumption characteristics of each power consumption. An input means for inputting energy consumption-related measured data, which is measured data related to energy consumption of a house,
Classification means for classifying the energy consumption related actual measurement data input to the input means based on a predetermined classification condition; and
Storage means for recording the energy consumption related actual measurement data classified by the classification means for each classification condition is provided,
A plurality of types of energy consumption related actual measurement data are input to the input means,
The classification means is configured to classify each of the plurality of types of energy consumption-related actual measurement data input to the input means based on classification conditions predetermined for each type,
The storage means is configured to record each type of energy consumption related actual measurement data classified by the classification means for each classification condition,
The classifying means includes actual measurement data related to kitchen gas consumption, actual measurement data related to energy consumption for hot water supply, and measurement data related to energy consumption for hot water supply among the plurality of types of actual measurement data related to energy consumption input to the input means. And each of the measured data of power consumption other than for air conditioning are configured to be classified for each of the classification conditions including home characteristics, energy consumption characteristics, family characteristics, and daily characteristics ,
Gas consumption actual measurement data indicating the relationship between gas consumption and time is input to the input means as the energy consumption related actual measurement data,
Pre-processing means for performing pre-processing for separating the gas consumption for kitchen from the gas consumption actual measurement data input to the input means is provided,
The classification means is configured to classify the gas consumption for the kitchen separated for the kitchen by the preprocessing means based on the classification conditions as actual measurement data related to the gas consumption for the kitchen,
The pre-processing means is
In the gas consumption actual measurement data, a data portion in a gas consumption time zone shorter than a set time is provisionally determined as a kitchen gas consumption amount, and a data portion in a gas consumption time zone longer than the set time is temporarily determined as a heating temporary determination data portion Tentatively determined as
Subsequently, when the time of the data portion tentatively determined as the kitchen gas consumption corresponds to the kitchen work time, the data portion is determined as the kitchen gas consumption and does not correspond to the kitchen work time Determines the data portion as heating gas consumption, and
In the data obtained by determining the minimum gas consumption amount in the heating temporary determination data portion from the temporary determination data portion for heating and subtracting the minimum gas consumption amount from the temporary determination data portion for heating, the gas shorter than the set time The data portion of the consumption time zone is determined as the kitchen gas consumption, and when there is a data portion of the gas consumption time zone that is longer than the set time, the minimum gas consumption in the data portion is determined from the data portion and The operation of determining the data portion of the gas consumption time zone shorter than the set time in the obtained data as the gas consumption for the kitchen by reducing the minimum gas consumption, and all the gas consumption time zones are shorter than the set time. A data creation device for calculating energy consumption of a house configured to repeat until it becomes. An input means for inputting energy consumption-related measured data, which is measured data related to energy consumption of a house,
  Classification means for classifying the energy consumption related actual measurement data input to the input means based on a predetermined classification condition; and
  Storage means for recording the energy consumption related actual measurement data classified by the classification means for each classification condition is provided,
  A plurality of types of energy consumption related actual measurement data are input to the input means,
  The classification means is configured to classify each of the plurality of types of energy consumption-related actual measurement data input to the input means based on classification conditions predetermined for each type,
  The storage means is configured to record each type of energy consumption related actual measurement data classified by the classification means for each classification condition,
  The classifying means includes actual measurement data related to gas consumption for kitchen use, actual measurement data related to energy consumption for hot water supply, and measurement data related to energy consumption for hot water supply among the plurality of types of actual measurement data related to energy consumption input to the input means. And each of the measured data of power consumption other than for air conditioning are configured to be classified for each of the classification conditions including home characteristics, energy consumption characteristics, family characteristics, and daily characteristics,
  As the actual measurement data related to the energy consumption for hot water supply, the amount of hot water supplied from the hot water supply device and the hot water supply temperature, and the amount of water supplied and the water supply temperature to be mixed with the hot water from the hot water supply device are input to the input means. And
  Based on the measured amount of hot water supplied to the input means, the hot water supply temperature, the amount of water supplied, and the actual measured data of the water supply temperature, the amount of hot water supplied and the amount of water supplied are determined as hot water consumption, and Pretreatment means is provided for performing a pretreatment for obtaining a hot water heat amount by adding a product of the hot water supply amount and the hot water supply temperature and a product of the water supply amount and the water supply temperature,
  A data creation apparatus for calculating energy consumption of a house, wherein the classification means is configured to classify the hot water consumption and the hot water quantity obtained by the preprocessing means for each classification condition. An input means for inputting energy consumption-related measured data, which is measured data related to energy consumption of a house,
  Classification means for classifying the energy consumption related actual measurement data input to the input means based on a predetermined classification condition; and
  Storage means for recording the energy consumption related actual measurement data classified by the classification means for each classification condition is provided,
  A plurality of types of energy consumption related actual measurement data are input to the input means,
  The classification means is configured to classify each of the plurality of types of energy consumption-related actual measurement data input to the input means based on classification conditions predetermined for each type,
  The storage means is configured to record each type of energy consumption related actual measurement data classified by the classification means for each classification condition,
  The classification means includes, for each of the classification conditions including building characteristics, daily characteristics, and regional characteristics, air conditioning energy consumption-related measured data among the plurality of types of energy consumption-related measured data input to the input means. Configured to classify,
  Use condition extraction means for obtaining an air conditioning use time zone and a set room temperature from the measured data related to energy consumption for air conditioning input to the input means;
  Based on the air conditioning use time zone and the set room temperature obtained by the use condition extraction means, a consumption energy calculation means for obtaining an energy consumption for air conditioning by a predetermined heat load calculation program is provided,
  The classification means is an energy consumption calculation data creation device for a house configured to classify the air conditioning energy consumption obtained by the consumption energy calculation means based on the classification conditions.

Images