JP2019091335A - Power generation amount prediction device, power generation amount prediction system, power generation amount prediction method, and power generation amount prediction program - Google Patents

Power generation amount prediction device, power generation amount prediction system, power generation amount prediction method, and power generation amount prediction program Download PDF

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JP2019091335A
JP2019091335A JP2017220691A JP2017220691A JP2019091335A JP 2019091335 A JP2019091335 A JP 2019091335A JP 2017220691 A JP2017220691 A JP 2017220691A JP 2017220691 A JP2017220691 A JP 2017220691A JP 2019091335 A JP2019091335 A JP 2019091335A
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power generation
solar radiation
amount
radiation amount
prediction
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JP6937227B2 (en
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知奈実 橋本
Chinami Hashimoto
知奈実 橋本
孝雄 野坂
Takao Nosaka
孝雄 野坂
木村　浩二
Koji Kimura
浩二 木村
建司 皆川
Kenji Minagawa
建司 皆川
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Toshiba Corp
Toshiba Infrastructure Systems and Solutions Corp
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    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E70/00—Other energy conversion or management systems reducing GHG emissions
    • Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

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  • Charge And Discharge Circuits For Batteries Or The Like (AREA)
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Abstract

To provide a power generation amount prediction device, a power generation amount prediction system, a power generation amount prediction method, and a power generation amount prediction program that can improve the accuracy in predicting the amount of power generation without handling various types of data.SOLUTION: A power generation amount prediction device 11 has a power generation amount/insolation amount actual insolation amount classification unit 1101, a power generation efficiency calculation/determination unit 1102, a power generation efficiency coefficient calculation unit 1103, a predicted insolation amount category determination unit 1104, and a power generation amount prediction unit 1105. The power generation amount/insolation amount actual insolation amount classification unit classifies a set of actual insolation amount values into a plurality of insolation amount categories. The power generation efficiency calculation/determination unit acquires power generation efficiency for each of the actual insolation amount values. The power generation efficiency coefficient calculation unit acquires a coefficient for each of the insolation amount categories on the basis of the power generation efficiency. The predicted insolation amount category determination unit identifies an insolation amount category to which the insolation amount category containing an insolation amount prediction value belongs. The power generation amount prediction unit acquires a power generation amount prediction value on the basis of the insolation amount prediction value and the coefficient of the insolation amount category containing the insolation amount prediction value.SELECTED DRAWING: Figure 1

Description

本発明の実施形態は、発電量予測装置、発電量予測システム、発電量予測方法及び発電量予測プログラムに関する。   Embodiments of the present invention relate to a power generation amount prediction device, a power generation amount prediction system, a power generation amount prediction method, and a power generation amount prediction program.

太陽光発電（PV：Photovoltaic）システムの発電量は、太陽光発電システムの発電効率と、電力の出力先である機器の状態とに応じて変化する。発電量予測装置は、太陽光発電システムの発電量を予測する場合がある。しかしながら、従来の発電量予測装置は、太陽位置気象補正係数、エリア気象環境係数、ＰＶシステム係数等の多種のデータを扱わなければ、発電量を精度よく予測することができない場合があった。   The amount of power generation of a photovoltaic power generation (PV: Photovoltaic) system changes according to the power generation efficiency of the photovoltaic power generation system and the state of the device to which the power is output. The power generation amount prediction device may predict the power generation amount of the photovoltaic power generation system. However, the conventional power generation amount prediction apparatus may not accurately predict the power generation amount unless various data such as the solar position meteorological correction coefficient, the area meteorological environment coefficient, and the PV system coefficient are handled.

特開２０１４−０６３３７２号公報JP, 2014-063372, A 特開２０１４−２１７０９２号公報JP, 2014-217092, A 特開２０１５−０７０６４０号公報JP, 2015-070640, A 特開２０１６−１２３１７０号公報JP, 2016-123170, A 特開２０１６−１３６８０７号公報JP, 2016-136807, A

D. King, W. Boyson, and J. Kratochvil, Photovoltaic Array Performance Model, SAND2004-3535, Sandia National Laboratories, Albuquerque, NM, December 2004.D. King, W. Boyson, and J. Kratochvil, Photovoltaic Array Performance Model, SAND 2004-3535, Sandia National Laboratories, Albuquerque, NM, December 2004.

本発明が解決しようとする課題は、多種のデータを扱うことなく、発電量を予測する精度を向上させることが可能である発電量予測装置、発電量予測システム、発電量予測方法及び発電量予測プログラムを提供することである。   The problem to be solved by the present invention is a power generation amount prediction device, a power generation amount prediction system, a power generation amount prediction method, and a power generation amount prediction capable of improving the accuracy of predicting the power generation amount without handling various data. It is to provide a program.

実施形態の発電量予測装置は、区分部と、発電効率取得部と、係数取得部と、区分判定部と、予測部とを持つ。区分部は、日射量実績値の集合を複数の日射量区分に区分する。発電効率取得部は、日射量実績値ごとに発電効率を取得する。係数取得部は、発電効率に基づいて日射量区分ごとに係数を取得する。区分判定部は、日射量予測値が含まれている日射量区分がいずれの日射量区分であるかを判定する。予測部は、日射量予測値が含まれている日射量区分の係数と日射量予測値とに基づいて発電量予測値を取得する。   The power generation amount prediction apparatus according to the embodiment has a sorting unit, a power generation efficiency acquiring unit, a coefficient acquiring unit, a classification determining unit, and a predicting unit. The division unit divides the set of actual solar radiation amount values into a plurality of solar radiation amount classifications. The power generation efficiency acquisition unit acquires the power generation efficiency for each of the actual solar radiation amount values. A coefficient acquisition part acquires a coefficient for every solar radiation amount division based on power generation efficiency. The category determination unit determines which range of solar radiation amount the solar radiation amount category including the solar radiation amount predicted value is. The prediction unit acquires the power generation amount prediction value based on the solar radiation amount prediction coefficient and the coefficient of the solar radiation amount division in which the solar radiation amount prediction value is included.

第１の実施形態の発電量予測システムの構成の例を示す図。BRIEF DESCRIPTION OF THE DRAWINGS The figure which shows the example of a structure of the electric power generation amount prediction system of 1st Embodiment. 第１の実施形態の日射量の判定ラインの例を示す図。The figure which shows the example of the determination line of the solar radiation amount of 1st Embodiment. 第１の実施形態の発電効率の判定ラインの例を示す図。The figure which shows the example of the determination line of the power generation efficiency of 1st Embodiment. 第１の実施形態の発電効率の算出の例を示す図。FIG. 7 is a view showing an example of calculation of power generation efficiency according to the first embodiment. 第１の実施形態の発電効率に関する係数の例を示す図。The figure which shows the example of the coefficient regarding the power generation efficiency of 1st Embodiment. 第１の実施形態の発電量予測装置の動作の例を示すフローチャート。6 is a flowchart showing an example of the operation of the power generation amount prediction device of the first embodiment. 第２の実施形態の発電効率の算出の例を示す図。The figure which shows the example of calculation of the electric power generation efficiency of 2nd Embodiment. 第２の実施形態の発電量の予測値を表す近似式の例を示す図。The figure which shows the example of the approximation formula showing the predicted value of the electric power generation amount of 2nd Embodiment. 第２の実施形態の日射量の区分の例を示す図。The figure which shows the example of division of the amount of solar radiation of 2nd Embodiment. 第２の実施形態の発電量の予測値の例を示す図。The figure which shows the example of the predicted value of the electric power generation amount of 2nd Embodiment. 第２の実施形態の時間帯ごとの発電量の予測値の例を示す図。The figure which shows the example of the predicted value of the electric power generation amount for every time slot | zone of 2nd Embodiment.

以下、実施形態の発電量予測装置、発電量予測システム、発電量予測方法及び発電量予測プログラムを、図面を参照して説明する。   Hereinafter, a power generation amount prediction device, a power generation amount prediction system, a power generation amount prediction method, and a power generation amount prediction program according to the embodiment will be described with reference to the drawings.

図１は、発電量予測システム１０の構成の例を示す図である。発電量予測システム１０は、エネルギー機器最適運用システム１と、太陽光発電設備２と、気象情報提供設備３と、エネルギー設備４と、蓄電池設備５とを備える。エネルギー機器最適運用システム１は、例えば、分散電源ＥＭＳ（Energy Management System）である。エネルギー機器最適運用システム１は、発電量の予測値に基づく制御信号を生成する。エネルギー機器最適運用システム１は、太陽光発電設備２、エネルギー設備４及び蓄電池設備５に、制御信号を出力する。以下において「取得する」とは、効率や係数等の値をデータテーブルから取得するという意味でもよいし、効率や係数等の値を算出するという意味でもよい。   FIG. 1 is a diagram showing an example of the configuration of a power generation amount prediction system 10. The power generation amount prediction system 10 includes an energy device optimum operation system 1, a solar power generation facility 2, a weather information provision facility 3, an energy facility 4, and a storage battery facility 5. The energy device optimum operation system 1 is, for example, a distributed power supply EMS (Energy Management System). The energy device optimum operating system 1 generates a control signal based on the predicted value of the amount of power generation. The energy device optimum operating system 1 outputs control signals to the solar power generation facility 2, the energy facility 4 and the storage battery facility 5. In the following, “to acquire” may mean that values such as efficiency and coefficient are acquired from a data table, and may mean that values such as efficiency and coefficient may be calculated.

太陽光発電設備２は、太陽光を用いて発電する設備である。太陽光発電設備２の発電量は、太陽光発電システムの発電効率と、電力の出力先であるエネルギー設備の機器の状態等とに応じて変化する。太陽光発電システムの発電効率は、日射量に応じて変化する。エネルギー設備の機器の状態とは、例えば、電力を消費する機器の動作状態や、パワーコンディショナの変換効率である。   The solar power generation facility 2 is a facility that generates electricity using sunlight. The amount of power generation of the photovoltaic power generation facility 2 changes according to the power generation efficiency of the photovoltaic power generation system, the state of the equipment of the energy facility to which the power is output, and the like. The power generation efficiency of the solar power generation system changes according to the amount of solar radiation. The state of the equipment of the energy equipment is, for example, the operating state of the equipment that consumes power, and the conversion efficiency of the power conditioner.

気象情報提供設備３は、気象情報を提供する設備である。気象情報は、例えば、日射量予報、風の強さの予報である。気象情報提供設備３は、日射量の予測値である日射量予報データを、気象情報に基づいて生成する。気象情報提供設備３は、日射量予報データをエネルギー機器最適運用システム１に提供する。   The weather information provision facility 3 is a facility that provides weather information. The weather information is, for example, a solar radiation forecast, a forecast of wind intensity. The weather information providing facility 3 generates solar radiation amount forecast data, which is a predicted value of solar radiation amount, based on weather information. The weather information providing facility 3 provides solar energy forecast data to the energy device optimum operating system 1.

エネルギー設備４は、電力や燃料等のエネルギーを消費する設備である。エネルギー設備４は、電力等のエネルギーを消費する機器を備える。エネルギー設備４の機器は、エネルギー機器最適運用システム１から出力された制御信号に応じて、電力等のエネルギーを消費する。   The energy facility 4 is a facility that consumes energy such as power and fuel. The energy equipment 4 includes equipment that consumes energy such as power. The devices of the energy facility 4 consume energy such as electric power according to the control signal output from the energy device optimum operating system 1.

蓄電池設備５は、リチウムイオン電池等の蓄電池を備える設備である。蓄電池は、エネルギー機器最適運用システム１から取得された制御信号に応じて、太陽光発電設備２によって発電された電力を蓄積する。蓄電池は、エネルギー機器最適運用システム１から取得された制御信号に応じて、エネルギー設備４に電力を出力する。   The storage battery facility 5 is a facility provided with a storage battery such as a lithium ion battery. The storage battery accumulates the power generated by the solar power generation facility 2 in accordance with the control signal acquired from the energy device optimum operating system 1. The storage battery outputs power to the energy facility 4 in accordance with the control signal acquired from the energy device optimum operating system 1.

次に、エネルギー機器最適運用システム１の構成の例を説明する。
エネルギー機器最適運用システム１は、発電量予測装置１１と、入出力部１２と、発電量・日射量実績収集部１３と、気象情報収集部１４と、エネルギー機器計画部１５と、エネルギー機器制御部１６と、エネルギー機器運用パターン記憶部１７とを備える。 Next, an example of the configuration of the energy device optimum operating system 1 will be described.
The energy device optimum operation system 1 includes a power generation amount prediction device 11, an input / output unit 12, a power generation and solar radiation performance record collection unit 13, a weather information collection unit 14, an energy device planning unit 15, and an energy device control unit 16 and an energy device operation pattern storage unit 17.

発電量予測装置１１は、発電量を予測する情報処理装置である。発電量予測装置１１は、太陽光発電設備２による発電量を、日射量予報に基づいて予測する。発電量予測装置１１は、時間単位の発電量の予測値を表す発電量予測データを、エネルギー機器計画部１５に出力する。   The power generation amount prediction device 11 is an information processing device that predicts the power generation amount. The power generation amount prediction apparatus 11 predicts the power generation amount of the solar power generation facility 2 based on the solar radiation amount forecast. The power generation amount prediction device 11 outputs, to the energy device planning unit 15, power generation amount prediction data representing a predicted value of the power generation amount in units of time.

以下、予測に用いられる日射量の上限閾値を「日射量上限判定ライン」という。以下、予測に用いられる日射量の下限閾値を「日射量下限判定ライン」という。   Hereinafter, the upper threshold of the amount of solar radiation used for prediction is referred to as “the upper limit determination line of solar radiation amount”. Hereinafter, the lower limit threshold of the amount of solar radiation used for prediction is referred to as “the lower limit determination line of solar radiation amount”.

入出力部１２は、キーボード、マウス、タッチパネル等の操作デバイスである。入出力部１２は、データを送信及び受信する通信装置でもよい。入出力部１２は、日射量の区分を表す日射量区分データと、日射量上限判定ラインと、日射量下限判定ラインと、発電効率に関する係数（固定値）を算出するために必要とされる発電効率データの個数データとを取得する。入出力部１２は、日射量区分データと、日射量上限判定ラインと、日射量下限判定ラインと、発電効率データの個数データとを、発電量予測装置１１に出力する。   The input / output unit 12 is an operation device such as a keyboard, a mouse, and a touch panel. The input / output unit 12 may be a communication device that transmits and receives data. The input / output unit 12 generates power required to calculate the solar radiation amount classification data representing the classification of solar radiation amount, the solar radiation amount upper limit determination line, the solar radiation amount lower limit determination line, and the coefficient (fixed value) related to the power generation efficiency The number data of efficiency data is acquired. The input / output unit 12 outputs the solar radiation amount classification data, the solar radiation amount upper limit determination line, the solar radiation amount lower limit determination line, and the number data of the power generation efficiency data to the power generation amount prediction device 11.

発電量・日射量実績収集部１３は、太陽光発電設備２における発電量の実績値である発電量実績データを、所定周期で太陽光発電設備２から収集する。発電量・日射量実績収集部１３は、太陽光発電設備２における日射量の実績値である日射量実績データを、太陽光発電設備２から収集する。日射量実績データが１時間ごとに収集されており、予測対象の時間帯が９時から１７時までであり、予測に使う実績日数が３０日分の日射量実績データが取得されている場合、収集される日射量実績データの個数は、２４０（＝８×３０）個である。発電量・日射量実績収集部１３は、発電量実績データ及び日射量実績データを、発電量予測装置１１に出力する。日射量実績データは、数分間ごとの日射量の複数の実績値の平均値でもよい。   The power generation amount / solar radiation amount performance collecting unit 13 collects power generation amount performance data, which is a performance value of the power generation amount in the solar power generation facility 2, from the solar power generation facility 2 at a predetermined cycle. The power generation amount / solar radiation amount performance collecting unit 13 collects, from the solar power generation facility 2, solar radiation amount performance data that is the actual value of the solar radiation amount in the solar power generation facility 2. When the solar radiation amount actual data is collected every hour, and the forecast target time zone is from 9:00 to 17:00, and the actual number of days to be used for prediction is 30 days of solar radiation amount actual data acquired, The number of pieces of solar radiation amount actual data collected is 240 (= 8 × 30). The power generation amount / solar radiation amount performance collecting unit 13 outputs the power generation amount actual data and the solar radiation amount actual data to the power generation amount prediction device 11. The solar radiation amount actual data may be an average value of a plurality of actual solar radiation amounts every several minutes.

気象情報収集部１４は、気象情報を気象情報提供設備３から収集する。気象情報収集部１４は、日射量予報データを含む気象情報を、発電量予測装置１１に出力する。
エネルギー機器計画部１５は、発電量予測データを発電量予測装置１１から取得する。エネルギー機器計画部１５は、エネルギー設備４の機器の運用パターンを表す運用パターン情報を、発電量予測データに基づいて生成する。 The meteorological information collection unit 14 collects meteorological information from the meteorological information provision facility 3. The weather information collection unit 14 outputs the weather information including the solar radiation amount forecast data to the power generation amount prediction device 11.
The energy device planning unit 15 acquires power generation prediction data from the power generation prediction device 11. The energy device planning unit 15 generates operation pattern information representing an operation pattern of devices of the energy facility 4 based on the power generation amount prediction data.

エネルギー機器制御部１６は、エネルギー設備４の機器の動作を制御するための制御信号を、運用パターン情報に基づいて生成する。エネルギー機器制御部１６は、エネルギー設備４に制御信号を出力する。
エネルギー機器運用パターン記憶部１７は、エネルギー設備４の機器の運用パターン情報を記憶する。 The energy device control unit 16 generates a control signal for controlling the operation of the device of the energy facility 4 based on the operation pattern information. The energy device control unit 16 outputs a control signal to the energy facility 4.
The energy device operation pattern storage unit 17 stores operation pattern information of the devices of the energy facility 4.

次に、発電量予測装置１１の構成の例を説明する。
発電量予測装置１１は、発電量・日射量実績日射量区分部１１０１と、発電効率算出・判定部１１０２と、発電予測可否判定・発電効率係数算出部１１０３と、予測日射量区分判定部１１０４と、発電量予測部１１０５と、日射量区分データ記憶部１１０６と、発電量・日射量実績データ記憶部１１０７と、発電量・日射量実績・日射量区分データ記憶部１１０８と、発電効率上下限データ記憶部１１０９と、実績データ単位発電効率データ記憶部１１１０と、発電予測可否判定データ記憶部１１１１と、日射量区分別発電効率係数記憶部１１１２と、日射量予報データ記憶部１１１３と、日射量予報日射量区分データ記憶部１１１４と、予測発電量データ記憶部１１１５とを備える。 Next, an example of the configuration of the power generation amount prediction device 11 will be described.
The power generation amount prediction apparatus 11 includes a power generation amount / solation amount actual solar radiation amount division unit 1101, a power generation efficiency calculation / determination unit 1102, a power generation prediction availability judgment / power generation efficiency coefficient calculation unit 1103, and a predicted solar radiation amount judgment unit 1104 , Power generation amount prediction unit 1105, solar radiation amount data storage unit 1106, power generation amount · solar radiation amount performance data storage unit 1107, power generation amount · solar radiation amount result · solar radiation amount data storage unit 1108, power generation efficiency upper and lower limit data A storage unit 1109, a performance data unit power generation efficiency data storage unit 1110, a power generation prediction availability determination data storage unit 1111, a solar radiation amount classified power generation efficiency coefficient storage unit 1112, a solar radiation forecast data storage unit 1113, a solar radiation forecast A solar radiation amount classification data storage unit 1114 and a predicted power generation amount data storage unit 1115 are provided.

各機能部のうち一部又は全部は、例えば、ＣＰＵ（Central Processing Unit）等のプロセッサが、プログラムを実行することにより実現される。各機能部のうち一部又は全部は、ＬＳＩ（Large Scale Integration）やＡＳＩＣ（Application Specific Integrated Circuit）等のハードウェアを用いて実現されてもよい。また、各機能部は、クラウド技術によって複数の情報処理装置に分散されていてもよい。   For example, a processor such as a central processing unit (CPU) executes a program to realize a part or all of the functional units. Some or all of the functional units may be realized using hardware such as LSI (Large Scale Integration) or ASIC (Application Specific Integrated Circuit). Also, each functional unit may be distributed to a plurality of information processing apparatuses by cloud technology.

各記憶部は、フラッシュメモリ、ＨＤＤ（Hard Disk Drive）などの不揮発性の記憶媒体（非一時的な記憶媒体）を有する。各記憶部は、例えば、ＲＡＭ（Random Access Memory）やレジスタなどの揮発性の記憶媒体を有していてもよい。   Each storage unit has a non-volatile storage medium (non-temporary storage medium) such as a flash memory or a hard disk drive (HDD). Each storage unit may have, for example, a volatile storage medium such as a random access memory (RAM) or a register.

発電量・日射量実績日射量区分部１１０１は、発電量実績データ及び日射量実績データを、発電量・日射量実績データ記憶部１１０７から取得する。発電量・日射量実績日射量区分部１１０１は、日射量実績データが表す日射量の実績値の有効範囲を、複数の日射量区分に区分する。   The power generation amount / solation amount actual solar radiation amount sorting unit 1101 acquires the power generation amount actual data and the solar radiation amount actual data from the power generation amount / solar radiation amount actual data storage portion 1107. The generated energy and actual irradiance actual irradiance sorting unit 1101 categorizes the effective range of actual irradiance values represented by the irradiance actual data into plural irradiance categories.

図２は、日射量の判定ラインの例を示す図である。横軸は、所定時間帯において測定された日射量実績データの瞬時値を表す。所定時間帯の長さは、例えば、数分間、３０分間、１時間である。以下では、所定時間帯の長さは、一例として１時間である。縦軸は、同じ所定時間帯において発電された電力量（発電電力量）を表す。以下に示す図２、図３、図４、図７における各横軸は、瞬時値の平均値を表してもよく、例えば、時刻ＸＸ：００から時刻ＸＸ：３０までの発電量に対して、時刻ＸＸ：００と時刻ＸＸ：３０との２点の瞬時値の平均値を表してもよい。   FIG. 2 is a diagram showing an example of a judgment line of the amount of solar radiation. The horizontal axis represents instantaneous values of the solar radiation amount actual data measured in a predetermined time zone. The length of the predetermined time zone is, for example, several minutes, 30 minutes, and one hour. Below, the length of a predetermined time zone is 1 hour as an example. The vertical axis represents the amount of power generated in the same predetermined time zone (the amount of generated power). Each horizontal axis in FIG. 2, FIG. 3, FIG. 4 and FIG. 7 shown below may represent the average value of the instantaneous value, for example, with respect to the power generation amount from time XX: 00 to time XX: 30 It may represent an average value of instantaneous values of two points of time XX: 00 and time XX: 30.

発電量・日射量実績日射量区分部１１０１は、日射量上限判定ラインから日射量下限判定ラインまでの日射量の実績値の範囲を表す有効範囲データと、区分の一例としての「区分１」から「区分５」までの各日射量区分を表す日射量区分データとを、日射量区分データ記憶部１１０６から取得する。発電量・日射量実績日射量区分部１１０１は、日射量の実績値の有効範囲に含まれない日射量実績データを除外する。   The generated energy and actual solar radiation amount classification unit 1101 uses effective range data representing the range of actual values of solar radiation amount from the solar radiation amount upper limit judgment line to the solar radiation amount lower limit judgment line, and “division 1” as an example of the classification The solar radiation amount classification data representing each solar radiation amount classification up to “division 5” is acquired from the solar radiation amount classification data storage unit 1106. The generated energy and actual irradiance actual irradiance sorting unit 1101 excludes irradiance actual data that is not included in the effective range of the actual irradiance values.

発電量・日射量実績日射量区分部１１０１は、日射量区分データに基づいて、日射量の実績値の有効範囲を複数の日射量区分に区分する。図２では、発電量・日射量実績日射量区分部１１０１は、区分の一例としての「区分１」から「区分５」までの日射量区分に、日射量の実績値の有効範囲を区分する。   The generated energy and actual solar radiation amount classification unit 1101 divides the effective range of the actual value of the solar radiation amount into a plurality of solar radiation amount classifications based on the solar radiation amount classification data. In FIG. 2, the generated power and actual solar radiation amount division unit 1101 divides the effective range of the actual value of the solar radiation amount into solar radiation amount classifications from “division 1” to “division 5” as an example of division.

発電効率算出・判定部１１０２は、発電量実績データ及び日射量実績データを、発電量・日射量実績・日射量区分データ記憶部１１０８から取得する。発電効率算出・判定部１１０２は、有効範囲データ及び日射量区分データを、発電量・日射量実績・日射量区分データ記憶部１１０８から取得する。   The power generation efficiency calculation / determination unit 1102 acquires the power generation amount actual data and the solar radiation amount actual data from the power generation amount, solar radiation amount actual, and solar radiation amount classification data storage unit 1108. The power generation efficiency calculation / determination unit 1102 acquires the effective range data and the solar radiation amount division data from the power generation amount, the actual solar radiation amount, and the solar radiation amount division data storage unit 1108.

発電効率算出・判定部１１０２は、発電量実績データ及び日射量実績データに基づいて、太陽光発電設備２の発電効率を日射量実績データごとに算出する。発電効率算出・判定部１１０２は、発電効率データを日射量実績データごとに、実績データ単位発電効率データ記憶部１１１０に記録する。   The power generation efficiency calculation / determination unit 1102 calculates the power generation efficiency of the solar power generation facility 2 for each of the solar radiation amount actual data, based on the power generation amount actual data and the solar radiation amount actual data. The power generation efficiency calculation / determination unit 1102 records the power generation efficiency data in the actual data unit power generation efficiency data storage unit 1110 for each of the solar radiation amount result data.

以下、予測に用いられる発電効率の上限閾値を「発電効率上限判定ライン」という。以下、予測に用いられる発電効率の下限閾値を「発電効率下限判定ライン」という。   Hereinafter, the upper limit threshold of the power generation efficiency used for the prediction is referred to as “power generation efficiency upper limit determination line”. Hereinafter, the lower limit threshold of the power generation efficiency used for prediction is referred to as “power generation efficiency lower limit determination line”.

図３は、発電効率の判定ラインの例を示す図である。発電効率算出・判定部１１０２は、発電効率上限判定ラインから発電効率下限判定ラインからまでの発電効率の有効範囲に発電効率データが含まれているか否かを、日射量実績データごとに判定する。発電効率算出・判定部１１０２は、発電効率の有効範囲に含まれていない発電効率データの日射量実績データを、予測に用いられる発電効率の日射量実績データの集合から除外する。   FIG. 3 is a diagram illustrating an example of a determination line of power generation efficiency. The power generation efficiency calculation / determination unit 1102 determines, for each of the solar radiation amount actual data, whether power generation efficiency data is included in the effective range of the power generation efficiency from the power generation efficiency upper limit judgment line to the power generation efficiency lower limit judgment line. The power generation efficiency calculation / determination unit 1102 excludes the solar radiation amount actual data of the power generation efficiency data not included in the effective range of the power generation efficiency from the set of solar radiation amount actual data of the power generation efficiency used for the prediction.

発電予測可否判定・発電効率係数算出部１１０３は、発電効率に関する係数を算出するために必要とされる発電効率データの個数データを、発電予測可否判定データ記憶部１１１１から取得する。発電予測可否判定・発電効率係数算出部１１０３は、個数データが表す個数以上の発電効率データを、実績データ単位発電効率データ記憶部１１１０から取得する。   The power generation prediction availability determination / power generation efficiency coefficient calculation unit 1103 acquires, from the power generation prediction availability data storage unit 1111, number data of power generation efficiency data required to calculate a coefficient relating to power generation efficiency. The power generation prediction availability determination / power generation efficiency coefficient calculation unit 1103 acquires power generation efficiency data equal to or greater than the number represented by the number data from the actual data unit power generation efficiency data storage unit 1110.

発電予測可否判定・発電効率係数算出部１１０３は、発電効率に関する係数を算出するために必要とされる個数以上の発電効率データを取得したか否かを、「区分１」から「区分５」までの日射量区分ごとに判定する。発電予測可否判定・発電効率係数算出部１１０３は、発電効率に関する係数を算出するために必要とされる個数以上の発電効率データを取得した場合、日射量区分における発電効率に関する係数を算出する。発電予測可否判定・発電効率係数算出部１１０３は、発電効率に関する係数を算出した場合、発電量の予測が可能であると判定する。   From "division 1" to "division 5" whether or not the power generation prediction availability judgment / power generation efficiency coefficient calculation unit 1103 has acquired power generation efficiency data more than the number required to calculate a coefficient related to power generation efficiency Determined for each category of solar radiation amount. The power generation prediction availability determination / power generation efficiency coefficient calculation unit 1103 calculates a coefficient relating to the power generation efficiency in the solar radiation amount division, when the power generation efficiency data more than the number required to calculate the coefficient relating to the power generation efficiency is acquired. When the power generation prediction availability determination / power generation efficiency coefficient calculation unit 1103 calculates a coefficient relating to power generation efficiency, it determines that prediction of the power generation amount is possible.

図４は、発電効率の算出の例を示す図である。発電予測可否判定・発電効率係数算出部１１０３は、日射量区分ごとの発電効率に基づいて、発電量の予測に用いられる発電効率に関する係数を日射量区分ごとに算出する。日射量上限判定ラインから日射量下限判定ラインまでの日射量の実績値の範囲を表す有効範囲では、発電効率に関する係数は、日射量に応じて非線形に変化する。発電予測可否判定・発電効率係数算出部１１０３は、日射量の実績値の有効範囲において日射量に応じて非線形に変化する発電効率に関する係数を、日射量区分ごとの発電効率に関する係数に置き換える。   FIG. 4 is a diagram showing an example of calculation of power generation efficiency. The power generation prediction availability determination / power generation efficiency coefficient calculation unit 1103 calculates a coefficient relating to the power generation efficiency used for the prediction of the power generation amount for each of the solar radiation amount segments, based on the power generation efficiency for each of the solar radiation amount segments. In the effective range which represents the range of the actual value of the solar radiation amount from the solar radiation amount upper limit determination line to the solar radiation amount lower limit determination line, the coefficient relating to the power generation efficiency changes non-linearly according to the solar radiation amount. The power generation prediction availability determination / power generation efficiency coefficient calculation unit 1103 replaces the coefficient relating to the power generation efficiency that changes nonlinearly according to the amount of solar radiation in the effective range of the actual value of the amount of solar radiation with the coefficient relating to the power generation efficiency for each solar radiation amount category.

発電予測可否判定・発電効率係数算出部１１０３は、日射量区分ごとの複数の発電効率に基づいて、発電効率に関する係数を日射量区分ごとに算出する。例えば、発電予測可否判定・発電効率係数算出部１１０３は、日射量区分ごとの複数の発電効率の実績値の平均値に基づいて、発電効率に関する係数を日射量区分ごとに算出する。発電予測可否判定・発電効率係数算出部１１０３は、日射量区分ごとの発電効率に関する係数を、日射量区分別発電効率係数記憶部１１１２に記録する。   The power generation prediction availability determination / power generation efficiency coefficient calculation unit 1103 calculates a coefficient relating to power generation efficiency for each of the solar radiation amount categories, based on the plurality of power generation efficiencies for each of the solar radiation amount segments. For example, the power generation prediction availability determination / power generation efficiency coefficient calculation unit 1103 calculates the coefficient relating to the power generation efficiency for each of the solar radiation amount segments based on the average value of the actual values of the plurality of power generation efficiencies for each of the solar radiation amount segments. The power generation prediction availability determination / power generation efficiency coefficient calculation unit 1103 records the coefficient relating to the power generation efficiency for each solar radiation amount category in the solar radiation amount classified power generation efficiency coefficient storage unit 1112.

図５は、発電効率に関する係数の例を示す図である。図５では、日射量区分「区分１」の発電効率に関する係数は、「１．９３９８」である。日射量区分「区分１」に対応付けられている式は、「ｙ＝１．９３９８ｘ」である。第１実施形態では、式のｙ切片は０である。   FIG. 5 is a diagram showing an example of coefficients related to power generation efficiency. In FIG. 5, the coefficient relating to the power generation efficiency of the solar radiation amount classification “division 1” is “1.9398”. The equation associated with the solar radiation amount category “segment 1” is “y = 1.9398x”. In the first embodiment, the y-intercept of the equation is zero.

図１に戻り、発電量予測装置１１の構成の説明を続ける。予測日射量区分判定部１１０４は、予測対象の時間帯における日射量予報データが表す日射量の予測値ｘがいずれの日射量区分に含まれているかを判定する。発電量予測部１１０５は、日射量の予測値ｘが含まれている日射量区分の発電効率に関する係数と日射量予報データとに基づいて、予測対象の時間帯における発電量の予測値ｙを算出する。予測対象の時間帯における日射量予報データが表す日射量の予測値ｘが日射量区分「区分１」に含まれている場合、発電量予測部１１０５は、日射量区分「区分１」の発電効率に関する係数「１．９３９８」を日射量の予測値ｘに乗算することによって、予測対象の時間帯における発電量の予測値ｙ（＝１．９３９８ｘ）を算出する。   Returning to FIG. 1, the description of the configuration of the power generation amount prediction device 11 will be continued. The predicted solar radiation amount category determination unit 1104 determines which solar radiation amount range the predicted value x of the solar radiation amount represented by the solar radiation amount forecast data in the time zone to be predicted is included. The power generation amount prediction unit 1105 calculates the prediction value y of the power generation amount in the time zone of the prediction target based on the coefficient regarding the power generation efficiency of the solar radiation amount category including the predicted value x of the solar radiation amount and the solar radiation amount forecast data Do. When the predicted value x of the solar radiation amount represented by the solar radiation amount forecast data in the time zone of the prediction target is included in the solar radiation amount category "Division 1", the power generation amount prediction unit 1105 generates the power generation efficiency of the solar radiation amount category "Division 1" The predicted value y (= 1. 9398 x) of the power generation amount in the time zone to be predicted is calculated by multiplying the predicted value x of the amount of solar radiation by the coefficient “1.9 398” related to.

なお、発電量予測部１１０５は、式を用いて発電量の予測値ｙを算出する代わりに、発電量の予測値ｙと日射量予報データが表す日射量の実績値ｘとの関係を表すデータテーブルを参照することによって、データテーブルから発電量ｙを取得してもよい。データテーブルは、例えば、日射量区分別発電効率係数記憶部１１１２に記憶される。   In addition, instead of calculating the power generation amount predicted value y using a formula, the power generation amount prediction unit 1105 is data representing the relationship between the power generation amount predicted value y and the actual value x of the solar radiation amount represented by the solar radiation amount forecast data. The power generation amount y may be obtained from the data table by referring to the table. The data table is stored, for example, in the solar radiation amount classified power generation efficiency coefficient storage unit 1112.

日射量区分データ記憶部１１０６は、入出力部１２の出力に基づいて、有効範囲データと日射量区分データとを記憶する。   The solar radiation amount data storage unit 1106 stores effective range data and solar radiation amount data based on the output of the input / output unit 12.

発電量・日射量実績データ記憶部１１０７は、例えば３０分間ごとの発電量実績データ及び日射量実績データを、発電量・日射量実績収集部１３から取得する。発電量・日射量実績データ記憶部１１０７は、発電量実績データ及び日射量実績データを記憶する。   The power generation amount / solar radiation amount performance data storage unit 1107 acquires, for example, the power generation amount performance data and the solar radiation amount performance data for every 30 minutes from the power generation amount / solar radiation amount performance collecting unit 13. The power generation and solar radiation performance data storage unit 1107 stores the power generation performance data and the solar radiation performance data.

発電量・日射量実績・日射量区分データ記憶部１１０８は、日射量の有効範囲に含まれている日射量実績データを、３０分間等の時間単位で記憶する。発電量・日射量実績・日射量区分データ記憶部１１０８は、発電量・日射量実績日射量区分部１１０１から出力された日射量区分データを記憶する。   The power generation amount · solar radiation amount performance · solar radiation amount classification data storage unit 1108 stores the solar radiation amount performance data included in the effective range of the solar radiation amount in a time unit such as 30 minutes. The power generation amount · solar radiation amount actual · solar radiation amount classification data storage unit 1108 stores the solar radiation amount classification data output from the power generation amount · solar radiation amount actual solar radiation amount classification unit 1101.

発電効率上下限データ記憶部１１０９は、発電効率の有効範囲データを記憶する。
実績データ単位発電効率データ記憶部１１１０は、発電効率データを発電量実績データごとに記憶する。
発電予測可否判定データ記憶部１１１１は、発電効率に関する係数を算出するために必要とされる発電効率データの個数データ（必要数データ）を記憶する。 The power generation efficiency upper and lower limit data storage unit 1109 stores effective range data of the power generation efficiency.
Performance data unit power generation efficiency data storage unit 1110 stores power generation efficiency data for each power generation performance data.
The power generation prediction availability determination data storage unit 1111 stores number data (necessary number data) of power generation efficiency data required to calculate a coefficient related to power generation efficiency.

日射量区分別発電効率係数記憶部１１１２は、発電効率に関する係数データを日射量区分ごとに記憶する。
日射量予報データ記憶部１１１３は、所定時間帯の日射量予報データを、例えば１時間等の時間単位で記憶する。
日射量予報日射量区分データ記憶部１１１４は、例えば１時間等の時間単位の日射量予報データを、日射量区分データごとに記憶する。
予測発電量データ記憶部１１１５は、例えば１時間等の時間単位の発電量予測データを、発電量予測部１１０５から取得する。予測発電量データ記憶部１１１５は、時間単位の発電量予測データを記憶する。 The solar radiation amount category power generation efficiency coefficient storage unit 1112 stores coefficient data relating to the power generation efficiency for each solar radiation amount category.
The solar radiation amount forecast data storage unit 1113 stores the solar radiation amount forecast data of a predetermined time zone, for example, in a time unit such as one hour.
The solar radiation amount forecasted solar radiation amount classification data storage unit 1114 stores, for each of the solar radiation amount classification data, solar radiation amount prediction data in a unit of time, such as one hour.
The predicted power generation amount data storage unit 1115 acquires power generation amount prediction data in units of time, such as one hour, from the power generation amount prediction unit 1105, for example. The predicted power generation amount data storage unit 1115 stores power generation amount prediction data in units of time.

次に、発電量予測装置１１の動作の例を説明する。
図６は、発電量予測装置１１の動作の例を示すフローチャートである。発電量・日射量実績日射量区分部１１０１及び発電効率算出・判定部１１０２は、予測に用いられる日射量実績データの数だけ、ステップＳ１０１からステップＳ１０２までの手順を、日射量実績データごとに繰り返す。発電量・日射量実績日射量区分部１１０１は、日射量の実績値の有効範囲に含まれない日射量実績データを除外する（ステップＳ１０１）。発電効率算出・判定部１１０２は、発電量実績データ及び日射量実績データに基づいて、太陽光発電設備２の発電効率を日射量実績データごとに算出する。発電効率算出・判定部１１０２は、発電効率の有効範囲に含まれていない発電効率データの日射量実績データを、予測に用いられる発電効率の日射量実績データの集合から除外する（ステップＳ１０２）。 Next, an example of the operation of the power generation amount prediction device 11 will be described.
FIG. 6 is a flowchart showing an example of the operation of the power generation amount prediction apparatus 11. The amount of generated power / actual amount of solar radiation amount classification unit 1101 and the generation efficiency calculation / determination unit 1102 repeat the procedure from step S101 to step S102 for each amount of actual solar radiation amount data, as many as the number of actual solar radiation amount data used for prediction . The generated energy and actual irradiance actual irradiance sorting unit 1101 excludes irradiance actual data not included in the effective range of the actual irradiance values (step S101). The power generation efficiency calculation / determination unit 1102 calculates the power generation efficiency of the solar power generation facility 2 for each of the solar radiation amount actual data, based on the power generation amount actual data and the solar radiation amount actual data. The power generation efficiency calculation / determination unit 1102 excludes the solar radiation amount actual data of the power generation efficiency data not included in the effective range of the power generation efficiency from the set of solar radiation amount actual data of the power generation efficiency used for prediction (step S102).

発電予測可否判定・発電効率係数算出部１１０３は、発電効率に関する係数を算出するために必要とされる個数以上の発電効率データを取得したか否かを、日射量区分ごとに判定する（ステップＳ１０３）。発電予測可否判定・発電効率係数算出部１１０３は、発電効率に関する係数を算出するために必要とされる個数以上の発電効率データを取得した場合、日射量区分における発電効率に関する係数を算出する（ステップＳ１０４）。   The power generation prediction availability determination / power generation efficiency coefficient calculation unit 1103 determines, for each solar radiation amount division, whether or not power generation efficiency data equal to or more than the number required to calculate the coefficient relating to power generation efficiency has been acquired (step S103) ). The power generation prediction availability judgment / power generation efficiency coefficient calculation unit 1103 calculates a coefficient relating to the power generation efficiency in the solar radiation amount division when acquiring power generation efficiency data more than the number required to calculate the coefficient relating to the power generation efficiency (step S104).

予測日射量区分判定部１１０４及び発電量予測部１１０５は、予測対象日における予測対象の時間帯の個数だけ、ステップＳ１０５からステップＳ１０６までの手順を、予測対象の時間帯ごとに繰り返す。予測日射量区分判定部１１０４は、予測対象の時間帯における日射量予報データが表す日射量の予測値ｘがいずれの日射量区分に含まれているかを判定する（ステップＳ１０５）。発電量予測部１１０５は、日射量の予測値ｘが含まれている日射量区分の発電効率に関する係数と日射量予報データとに基づいて、予測対象の時間帯における発電量の予測値ｙを算出する（ステップＳ１０６）。   The forecasted solar radiation amount classification determination unit 1104 and the power generation amount forecasting unit 1105 repeat the procedure from step S105 to step S106 for each time zone to be predicted by the number of time zones to be predicted on the day to be predicted. The predicted solar radiation amount category determination unit 1104 determines which solar radiation amount range the predicted value x of the solar radiation amount represented by the solar radiation amount forecast data in the time zone to be predicted is included in (step S105). The power generation amount prediction unit 1105 calculates the prediction value y of the power generation amount in the time zone of the prediction target based on the coefficient regarding the power generation efficiency of the solar radiation amount category including the predicted value x of the solar radiation amount and the solar radiation amount forecast data (Step S106).

以上のように、第１の実施形態の発電量予測装置１１は、発電量・日射量実績日射量区分部１１０１と、発電効率算出・判定部１１０２と、発電予測可否判定・発電効率係数算出部１１０３と、予測日射量区分判定部１１０４と、発電量予測部１１０５とを持つ。発電量・日射量実績日射量区分部１１０１は、日射量実績データの集合を複数の日射量区分に区分する。発電効率算出・判定部１１０２は、日射量実績データごとに発電効率を取得する。発電予測可否判定・発電効率係数算出部１１０３は、発電効率に基づいて日射量区分ごとに係数を取得する。予測日射量区分判定部１１０４は、日射量予測データが含まれている日射量区分がいずれの日射量区分であるかを判定する。発電量予測部１１０５は、日射量予測データが含まれている日射量区分の係数と日射量予測データとに基づいて。発電量の予測値を取得する。   As described above, the power generation amount prediction apparatus 11 according to the first embodiment includes the power generation amount / solation amount actual solar radiation amount division unit 1101, the power generation efficiency calculation / determination unit 1102, and the power generation prediction availability judgment / power generation efficiency coefficient calculation unit It has 1103, a predicted solar radiation amount classification determination unit 1104, and a power generation amount prediction unit 1105. The power generation amount / solation amount actual irradiance division unit 1101 divides the set of sunshine amount actual data into a plurality of irradiance amount classifications. The power generation efficiency calculation / determination unit 1102 acquires the power generation efficiency for each of the solar radiation amount actual data. The power generation prediction availability determination / power generation efficiency coefficient calculation unit 1103 acquires a coefficient for each of the solar radiation amount categories based on the power generation efficiency. The predicted solar radiation amount category determination unit 1104 determines which solar radiation amount range the solar radiation amount category containing the solar radiation amount forecast data is. The power generation amount prediction unit 1105 is based on the solar radiation amount coefficient including the solar radiation amount prediction data and the solar radiation amount prediction data. Obtain the predicted value of the amount of power generation.

これにより、第１の実施形態の発電量予測装置１１は、多種のデータを扱うことなく、発電量を予測する精度を向上させることが可能である。   Thereby, the power generation amount prediction apparatus 11 of the first embodiment can improve the accuracy of predicting the power generation amount without handling various data.

第１の実施形態の発電量予測装置１１は、日射量区分に区分せずに日射量の有効範囲の全体で発電効率を算出する場合と比較して、発電効率を精度よく算出することができるので、発電量を予測する精度を向上させることが可能である。第１の実施形態の発電量予測装置１１は、日射量に対して非線形である発電効率に関する係数を精度よく算出することができるので、発電量を予測する精度を向上させることが可能である。   The power generation amount prediction apparatus 11 according to the first embodiment can calculate the power generation efficiency with high accuracy, as compared with the case where the power generation efficiency is calculated in the entire effective range of the solar radiation amount without being divided into the solar radiation amount classification. Therefore, it is possible to improve the accuracy of predicting the amount of power generation. The power generation amount prediction apparatus 11 according to the first embodiment can accurately calculate the coefficient relating to the power generation efficiency that is non-linear with respect to the amount of solar radiation, so that it is possible to improve the accuracy of predicting the power generation amount.

（第２の実施形態）
第２の実施形態では、日射量区分ごとの固定値である発電効率の平均値を発電量予測部１１０５が用いる代わりに、発電効率の近似式を用いて発電量予測部１１０５が発電量を算出する点が、第１の実施形態と相違する。第２の実施形態では、第１の実施形態との相違点についてのみ説明する。 Second Embodiment
In the second embodiment, instead of using the average value of the power generation efficiency which is a fixed value for each solar radiation amount group to be used by the power generation amount prediction unit 1105, the power generation amount prediction unit 1105 calculates the power generation amount using an approximate expression of power generation efficiency. Is different from the first embodiment. In the second embodiment, only differences from the first embodiment will be described.

図７は、発電効率の算出の例を示す図である。発電予測可否判定・発電効率係数算出部１１０３は、日射量区分ごとの発電効率に基づいて、発電量の予測に用いられる発電効率を表す近似式の係数及び切片を、日射量区分ごとに算出する。   FIG. 7 is a diagram showing an example of calculation of power generation efficiency. The power generation prediction availability determination / power generation efficiency coefficient calculation unit 1103 calculates, for each of the solar radiation amount segments, a coefficient and an intercept of an approximate expression representing the power generation efficiency used to predict the power generation amount based on the power generation efficiency for each of the solar radiation amount segments. .

図８は、発電量の予測値を表す近似式の例を示す図である。図８では、日射量区分「区分１」に対応付けられている一次近似式は、「ｙ＝１．９５４５ｘ−２．９６４５」である。第２実施形態では、発電量に関する式のｙ切片は０でなくてもよい。   FIG. 8 is a diagram showing an example of an approximate expression representing a predicted value of the amount of power generation. In FIG. 8, the first-order approximate expression associated with the solar radiation amount classification “division 1” is “y = 1.9545x−2.9645”. In the second embodiment, the y intercept of the equation relating to the amount of power generation may not be zero.

図９は、日射量の区分の例を示す図である。予測日射量区分判定部１１０４は、予測対象の時間帯における日射量予報データが表す日射量の予測値ｘがいずれの日射量区分に含まれているかを判定する。図９では、日射量予報データが表す日射量は、一例として６８９．５Ｗ／ｍ２であり、「区分３」に含まれている。 FIG. 9 is a diagram showing an example of the division of the amount of solar radiation. The predicted solar radiation amount category determination unit 1104 determines which solar radiation amount range the predicted value x of the solar radiation amount represented by the solar radiation amount forecast data in the time zone to be predicted is included. In FIG. 9, the solar radiation amount represented by the solar radiation amount forecast data is, for example, 689.5 W / m 2 and is included in “Category 3”.

図１０は、発電量の予測値の例を示す図である。発電量予測部１１０５は、日射量の予測値ｘが含まれている日射量区分の発電効率に関する係数と日射量予報データとに基づいて、予測対象の時間帯における発電量の予測値ｙを算出する。予測対象の時間帯における日射量予報データが表す日射量の予測値ｘが日射量区分「区分３」に含まれている場合、発電量予測部１１０５は、日射量区分「区分３」に対応付けられた一次近似式「ｙ＝２．１２５９ｘ−１９７．５４」に基づいて、予測対象の時間帯における発電量の予測値ｙを算出する。   FIG. 10 is a diagram showing an example of the predicted value of the power generation amount. The power generation amount prediction unit 1105 calculates the prediction value y of the power generation amount in the time zone of the prediction target based on the coefficient regarding the power generation efficiency of the solar radiation amount category including the predicted value x of the solar radiation amount and the solar radiation amount forecast data Do. When the predicted value x of the solar radiation amount represented by the solar radiation amount forecast data in the time zone of the prediction target is included in the solar radiation amount classification "division 3", the power generation amount prediction unit 1105 associates the solar radiation amount division "division 3" The predicted value y of the power generation amount in the time zone to be predicted is calculated based on the linear approximation formula “y = 2.1259x−197.54”.

図１１は、時間帯ごとの発電量の予測値の例を示す図である。１４時から１５時までの時間帯における日射量の予測値ｘが６８９．５Ｗ／ｍ２である場合、予測日射量区分判定部１１０４は、予測対象の時間帯における日射量予報データが表す日射量の予測値ｘが日射量区分「区分３」に含まれていると判定する。発電量予測部１１０５は、日射量区分「区分３」に対応付けられた一次近似式「ｙ＝２．１２５９ｘ−１９７．５４」に基づいて、予測対象の時間帯における発電量の予測値ｙを１２６８．３ｋＷｈと算出する。 FIG. 11 is a diagram showing an example of predicted values of the amount of power generation for each time zone. When the predicted value x of the solar radiation amount in the time zone from 14 o'clock to 15 o'clock is 689.5 W / m 2 , the predicted solar radiation amount category determination unit 1104 indicates the solar radiation amount represented by the solar radiation amount forecast data in the time zone to be forecasted It is determined that the predicted value x of x is included in the solar radiation classification “division 3”. The power generation amount prediction unit 1105 calculates the predicted value y of the power generation amount in the time zone to be predicted, based on the primary approximate expression “y = 2. 1259 x-197.54” associated with the solar radiation amount classification “division 3”. Calculated as 1268.3 kWh.

以上のように、第２の実施形態の発電量予測装置１１は、発電量予測装置１１は、発電量・日射量実績日射量区分部１１０１と、発電効率算出・判定部１１０２と、発電予測可否判定・発電効率係数算出部１１０３と、予測日射量区分判定部１１０４と、発電量予測部１１０５とを持つ。発電量予測部１１０５は、日射量予測データが含まれている日射量区分の係数を含む近似式と日射量予測データとに基づいて。発電量の予測値を取得する。   As described above, in the power generation amount prediction apparatus 11 according to the second embodiment, the power generation amount prediction apparatus 11 includes the power generation amount / solation amount actual sunshine amount division unit 1101, the power generation efficiency calculation / determination unit 1102, and the power generation prediction availability It has a judgment and power generation efficiency coefficient calculation unit 1103, a predicted solar radiation classification determination unit 1104 and a power generation prediction unit 1105. The power generation amount prediction unit 1105 is based on the solar radiation amount prediction data and the approximate expression including the coefficient of the solar radiation amount division in which the solar radiation amount prediction data is included. Obtain the predicted value of the amount of power generation.

これにより、第２の実施形態の発電量予測装置１１は、多種のデータを扱うことなく、発電量を予測する精度を向上させることが可能である。   Thereby, the power generation amount prediction apparatus 11 of the second embodiment can improve the accuracy of predicting the power generation amount without handling various data.

以上述べた少なくともひとつの実施形態によれば、日射量予測データが含まれている日射量区分の係数と日射量予測データとに基づいて発電量の予測値を取得する発電量予測部とを持つことにより、多種のデータを扱うことなく、発電量を予測する精度を向上させることができる。   According to at least one embodiment described above, it has a power generation amount prediction unit that acquires a predicted value of power generation amount based on the solar radiation amount prediction data and the coefficient of solar radiation amount division in which the solar radiation amount prediction data is included. By this, it is possible to improve the accuracy of predicting the amount of power generation without handling various data.

以上、本発明のいくつかの実施形態を説明したが、これらの実施形態は、例として提示したものであり、発明の範囲を限定することは意図していない。これら実施形態は、その他の様々な形態で実施されることが可能であり、発明の要旨を逸脱しない範囲で、種々の省略、置き換え、変更を行うことができる。これら実施形態やその変形は、発明の範囲や要旨に含まれると同様に、特許請求の範囲に記載された発明とその均等の範囲に含まれるものである。   While certain embodiments have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of the invention. These embodiments can be implemented in other various forms, and various omissions, replacements, and modifications can be made without departing from the scope of the invention. These embodiments and modifications thereof are included in the invention described in the claims and the equivalents thereof as well as included in the scope and the gist of the invention.

１…エネルギー機器最適運用システム、２…太陽光発電設備、３…気象情報提供設備、４…エネルギー設備、５…蓄電池設備、１０…発電量予測システム、１１…発電量予測装置、１２…入出力部、１３…発電量・日射量実績収集部、１４…気象情報収集部、１５…エネルギー機器計画部、１６…エネルギー機器制御部、１７…エネルギー機器運用パターン記憶部、１１０１…発電量・日射量実績日射量区分部、１１０２…発電効率算出・判定部、１１０３…発電予測可否判定・発電効率係数算出部、１１０４…予測日射量区分判定部、１１０５…発電量予測部、１１０６…日射量区分データ記憶部、１１０７…発電量・日射量実績データ記憶部、１１０８…発電量・日射量実績・日射量区分データ記憶部、１１０９…発電効率上下限データ記憶部、１１１０…実績データ単位発電効率データ記憶部、１１１１…発電予測可否判定データ記憶部、１１１２…日射量区分別発電効率係数記憶部、１１１３…日射量予報データ記憶部、１１１４…日射量予報日射量区分データ記憶部、１１１５…予測発電量データ記憶部   DESCRIPTION OF SYMBOLS 1 ... Energy apparatus optimal operation system, 2 ... Photovoltaic power generation facility, 3 ... Weather information provision facility, 4 ... Energy facility, 5 ... Storage battery facility, 10 ... Power generation prediction system, 11 ... Power generation prediction device, 12 ... I / O Part 13 13 amount of generated power · actual amount of solar radiation collecting portion 14 14 weather information collecting portion 15 energy device planning portion 16 energy device control portion 17 energy device operation pattern storage portion 1101 generated amount solar radiation amount Actual solar irradiance classification unit, 1102 ... generation efficiency calculation / determination unit, 1103 ... power generation prediction availability judgment / power generation efficiency coefficient calculation unit, 1104 ... predicted solar radiation classification judgment unit, 1105 ... power generation prediction unit, 1106 ... solar radiation amount division data Storage unit, 1107 ... power generation amount / solar radiation amount performance data storage unit, 1108 ... power generation amount / solar radiation amount actual result / solar radiation amount classification data storage unit, 1109 ... generation efficiency upper and lower limit data Storage unit 1110 Performance data unit Power generation efficiency data storage unit 1111 Power generation prediction availability determination data storage unit 1112 Solar radiation amount classified power generation efficiency coefficient storage unit 1113 Solar radiation forecast data storage unit 1114 Solar radiation forecast Solar radiation classification data storage unit, 1115 ... predicted power generation data storage unit

Claims (9)

日射量実績値の集合を複数の日射量区分に区分する区分部と、
前記日射量実績値ごとに発電効率を取得する発電効率取得部と、
前記発電効率に基づいて前記日射量区分ごとに係数を取得する係数取得部と、
日射量予測値が含まれている前記日射量区分がいずれの前記日射量区分であるかを判定する区分判定部と、
前記日射量予測値が含まれている前記日射量区分の前記係数と前記日射量予測値とに基づいて発電量予測値を取得する予測部と
を備える発電量予測装置。 A division unit that divides a set of actual solar radiation amount values into a plurality of solar radiation amount classifications;
A power generation efficiency acquisition unit that acquires power generation efficiency for each of the solar radiation amount actual values;
A coefficient acquisition unit that acquires a coefficient for each of the solar radiation amount sections based on the power generation efficiency;
A classification determination unit that determines which of the solar radiation amount classifications the solar radiation amount classifications include a solar radiation amount prediction value;
A power generation amount prediction device comprising: a prediction unit that acquires a power generation amount prediction value based on the solar radiation amount prediction value and the coefficient of the solar radiation amount class that includes the solar radiation amount prediction value. 前記日射量実績値は、第１の時間ごとの日射量の実績値である、請求項１に記載の発電量予測装置。   The power generation amount prediction apparatus according to claim 1, wherein the solar radiation amount actual value is a first actual value of solar radiation amount per hour. 前記日射量実績値は、第２の時間ごとの日射量の複数の実績値の平均値である、請求項１に記載の発電量予測装置。   The power generation amount prediction apparatus according to claim 1, wherein the actual solar radiation amount value is an average value of a plurality of actual solar radiation amounts per second time. 前記区分判定部は、前記発電効率の有効範囲から外れた前記発電効率を示す前記日射量実績値を、前記日射量実績値の集合から除外する、請求項１から請求項３のいずれか一項に記載の発電量予測装置。   The said division determination part excludes the said solar radiation amount actual value which shows the said power generation efficiency which remove | deviated from the effective range of the said power generation efficiency from the set of the said solar radiation amount actual value any one of Claim 1 to 3 The power generation amount prediction device described in. 前記係数取得部は、予め定められた個数以上の前記発電効率に基づいて、前記日射量区分ごとに前記係数を取得する、請求項１から請求項４のいずれか一項に記載の発電量予測装置。   The power generation amount prediction according to any one of claims 1 to 4, wherein the coefficient acquisition unit acquires the coefficient for each of the solar radiation amount sections based on a predetermined number or more of the power generation efficiency. apparatus. 前記予測部は、前記日射量区分の前記係数を含む式と前記日射量予測値とに基づいて発電量予測値を取得する、請求項１から請求項４のいずれか一項に記載の発電量予測装置。   The power generation amount according to any one of claims 1 to 4, wherein the prediction unit acquires a power generation amount prediction value based on an equation including the coefficient of the solar radiation amount class and the solar radiation amount prediction value. Prediction device. 日射量実績値の集合を複数の日射量区分に区分する区分部と、
前記日射量実績値ごとに発電効率を取得する発電効率取得部と、
前記発電効率に基づいて前記日射量区分ごとに係数を取得する係数取得部と、
日射量予測値が含まれている前記日射量区分がいずれの前記日射量区分であるかを判定する区分判定部と、
前記日射量予測値が含まれている前記日射量区分の前記係数と前記日射量予測値とに基づいて発電量予測値を取得する予測部と、
前記発電量予測値に基づく制御信号に応じて蓄電する蓄電池と
を備える発電量予測システム。 A division unit that divides a set of actual solar radiation amount values into a plurality of solar radiation amount classifications;
A power generation efficiency acquisition unit that acquires power generation efficiency for each of the solar radiation amount actual values;
A coefficient acquisition unit that acquires a coefficient for each of the solar radiation amount sections based on the power generation efficiency;
A classification determination unit that determines which of the solar radiation amount classifications the solar radiation amount classifications include a solar radiation amount prediction value;
A prediction unit that acquires a power generation predicted value based on the solar radiation amount predicted value and the coefficient of the solar radiation amount class including the solar radiation amount predicted value;
A storage battery configured to store power according to a control signal based on the power generation predicted value. 発電量予測装置が実行する発電量予測方法であって、
日射量実績値の集合を複数の日射量区分に区分するステップと、
前記日射量実績値ごとに発電効率を取得するステップと、
前記発電効率に基づいて前記日射量区分ごとに係数を取得するステップと、
日射量予測値が含まれている前記日射量区分がいずれの前記日射量区分であるかを判定するステップと、
前記日射量予測値が含まれている前記日射量区分の前記係数と前記日射量予測値とに基づいて発電量予測値を取得するステップと
を含む発電量予測方法。 A power generation amount prediction method executed by the power generation amount prediction device, which
Segmenting the set of actual solar radiation values into a plurality of solar radiation categories;
Acquiring the power generation efficiency for each of the solar radiation amount actual values;
Acquiring a coefficient for each of the solar radiation amount sections based on the power generation efficiency;
Determining whether the solar radiation amount category including the solar radiation amount predicted value is any of the solar radiation amount categories;
Obtaining a power generation predicted value based on the solar radiation amount predicted value and the coefficient of the solar radiation amount class including the solar radiation amount predicted value. コンピュータに、
日射量実績値の集合を複数の日射量区分に区分する手順と、
前記日射量実績値ごとに発電効率を取得する手順と、
前記発電効率に基づいて前記日射量区分ごとに係数を取得する手順と
日射量予測値が含まれている前記日射量区分がいずれの前記日射量区分であるかを判定する手順と、
前記日射量予測値が含まれている前記日射量区分の前記係数と前記日射量予測値とに基づいて発電量予測値を取得する手順と
を実行させるための発電量予測プログラム。 On the computer
A procedure for dividing a set of actual solar radiation values into a plurality of solar radiation categories;
A procedure for acquiring power generation efficiency for each of the solar radiation amount actual values;
A step of acquiring a coefficient for each of the solar radiation amount segments based on the power generation efficiency, and a procedure of determining which of the solar radiation amount segments the solar radiation amount segment including a solar radiation amount predicted value is included;
A power generation amount prediction program for executing a procedure of acquiring a power generation amount predicted value based on the solar radiation amount predicted value and the coefficient of the solar radiation amount class including the solar radiation amount predicted value.
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2021145509A (en) * 2020-03-13 2021-09-24 オムロン株式会社 Abnormality detection device, abnormality detection method, and abnormality detection program
KR20220167555A (en) * 2021-06-14 2022-12-21 한국전력공사 Management System and Method for Controlling Output of Power Generation
CN117040030A (en) * 2023-10-10 2023-11-10 国网浙江宁波市鄞州区供电有限公司 New energy consumption capacity risk management and control method and system

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2013191672A (en) * 2012-03-13 2013-09-26 Omron Corp Information processing apparatus, abnormality detecting method, program, and solar power generation system
JP2014179464A (en) * 2013-03-14 2014-09-25 Omron Corp Photovoltaic power generation system, abnormality determination processor, abnormality determination processing method and program
JP2016065484A (en) * 2014-09-24 2016-04-28 トヨタ自動車株式会社 Estimation device of throttle upstream pressure

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2013191672A (en) * 2012-03-13 2013-09-26 Omron Corp Information processing apparatus, abnormality detecting method, program, and solar power generation system
JP2014179464A (en) * 2013-03-14 2014-09-25 Omron Corp Photovoltaic power generation system, abnormality determination processor, abnormality determination processing method and program
JP2016065484A (en) * 2014-09-24 2016-04-28 トヨタ自動車株式会社 Estimation device of throttle upstream pressure

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2021145509A (en) * 2020-03-13 2021-09-24 オムロン株式会社 Abnormality detection device, abnormality detection method, and abnormality detection program
JP7435073B2 (en) 2020-03-13 2024-02-21 オムロン株式会社 Anomaly detection device, anomaly detection method, and anomaly detection program
KR20220167555A (en) * 2021-06-14 2022-12-21 한국전력공사 Management System and Method for Controlling Output of Power Generation
KR102621374B1 (en) * 2021-06-14 2024-01-08 한국전력공사 Management System and Method for Controlling Output of Power Generation
CN117040030A (en) * 2023-10-10 2023-11-10 国网浙江宁波市鄞州区供电有限公司 New energy consumption capacity risk management and control method and system
CN117040030B (en) * 2023-10-10 2024-04-02 国网浙江宁波市鄞州区供电有限公司 New energy consumption capacity risk management and control method and system

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