JP4166051B2

JP4166051B2 - Air conditioning system

Info

Publication number: JP4166051B2
Application number: JP2002227201A
Authority: JP
Inventors: 康夫高木; 徹也船津; 一徳岩渕; 君永内藤
Original assignee: Toshiba Corp
Current assignee: Toshiba Corp
Priority date: 2002-08-05
Filing date: 2002-08-05
Publication date: 2008-10-15
Anticipated expiration: 2022-08-05
Also published as: JP2004069134A

Description

【０００１】
【発明の属する技術の分野】
本発明は、例えば、ビルや病院などの建家内の冷暖房を行う空調システムに関する。
【０００２】
【従来の技術】
一般に、ビルの空調システムにおける部屋温度の制御方式には、部屋の温度を測定してこれが目標値になるように、熱源機が製造する冷水または温水の流量を制御する定風量制御方式（ＣＡＶ方式）と、冷水または温水の水量は一定で風量を変える可変風量制御方式（ＶＡＶ方式）とがある。また、両者を組み合わせたハイブリッド方式もある。
【０００３】
定風量制御方式では、冷水(温水)の流量を制御するために水循環系にポンプとバルブとを設け、ポンプは一定回転数で水を送り出す一方、バルブで所望の流量に調節する。この定風量制御方法ではポンプ動力が中問負荷のときに無駄になるので、近年ではバルブではなくインバータ制御ポンプにより流量制御が行われる場合が増えてきた。
【０００４】
一方、可変風量制御方式では空調ファンが一定回転数で空気を循環させ、その空気流量をダンパーで調節するものである。この空気の流量調節により室温を目標値に制御する。この場合も省エネルギーの観点からダンパーではなくインバータ制御ファンにて空気流量を制御することが近年行われるようになっている。
【０００５】
このように、従来の空調システムの制御では、部屋温度のフィードバックによりバルブやダンパーを制御し、または、インバータ制御ポンプやインバータ制御ファンを制御することにより、部屋温度を所定の値に制御している。
【０００６】
一方、冷却塔は熱源機の発生する熱を大気中に放散するための装置であるが、従来は一定温度の冷却水を製造するように制御されている。空調用では一般的に約３２℃程度である。
【０００７】
【発明が解決しようとする課題】
ところが、従来の空調システムでは、水流量または空気流量のみを操作して室温を制御しているので、必ずしも最もエネルギー消費が少ない状態で運用されるとは限らない。
【０００８】
冷水戻り温度と冷凍機成績係数（ＣＯＰ）との間、ファンやポンプに関し、その流量と所要動力との間には密接な相関関係がある。冷水戻り温度は一般的には高いほうが冷凍機成績係数（ＣＯＰ）は高くなる。また、ファンやポンプの所要動力は良く知られているように流量の３乗に比例する。特に、インバータ制御ファンとインバータ制御ポンプとを備えた空調システムでは、水流量と空気流量とをどのようにも調節可能であるが、室温のみにより制御しているので、必ずしも最もエネルギー消費が少ない点で運用されるとは限らなかった。
【０００９】
いま、図４に示すような空調システムを考える。熱源機である冷凍機１の温度をＴｒ、その基準温度をＴｒ_０、ポンプ２による冷却流量をＦ_Ｗ、その基準流量をＦ_Ｗ０、ポンプ２の動力をＰ_ｐｕｍｐ、その基準動力をＰ_{ｐｕｍｐ０}、空調コイル３の温度をＴｃ、その基準温度をＴｃ_０、ファン４による空調風量をＦａ、その基準風量をＦａ_０、ファン４の動力をＰ_ｆａｎ、その基準動力をＰ_ｆａｎ０、室内５の室内温度をＴａ、その基準温度をＴａ_０とする。
【００１０】
ポンプ２の動力Ｐ_ｐｕｍｐの関係式は（１）式に示され、ファン４の動力Ｐ_ｆａｎの関係式は（２）式で示される。また、ポンプ２の動力とファン４の動力との合計ｆ（Ｔｃ）を（３）式に示す。
【００１１】
【数１】

（１）式に示されるように、ポンプ２の動力Ｐ_ｐｕｍｐは流量Ｆ_Ｗの３乗に比例し、また必要流量は負荷が変わらなければ温度差に反比例する。同様に、ファン４の動力Ｐ_ｆａｎも、（２）式に示すように流量Ｆａの３乗に比例し、また必要流量は負荷が変わらなければ温度差に反比例する。
【００１２】
図５は、（３）式のポンプ２の動力とファン４の動力との合計ｆ（Ｔｃ）を空調コイル温度Ｔｃについてプロットした特性図である。図５に示すように、総動力ｆ（Ｔｃ）は空調コイル温度Ｔｃにより大きく変化する。
【００１３】
しかるに、従来の空調システムでは部屋温度のみによりポンプ２またはファン４の制御を行っているので、ポンプ２の動力およびファン４の動力の両者の最小化は考慮されておらず、例えば、運用点１にて運用されていた。
【００１４】
一方、冷却塔の製造する冷却水に関しても、冷却水温度が低いほど冷凍機１の成績係数（ＣＯＰ）は改善しその消費動力は低減するが、冷却水温度を低くするためには冷却塔ファンの消費動力が増大するという特性を有する。
【００１５】
図６は、熱源機（冷凍機）がガス炊きボイラによる蒸気吸収式冷凍機である場合の冷却水温度に対する冷却塔ファンの消費動力（電力消費量）およびガス消費量の関係を示す特性図である。図６から明らかなように、冷却水温度によりガスおよび電気の総合動力コストは変化する。特に、時間帯により電気料金は大きく変化するので、従来の一定冷却水温度制御では動力コストが最小化されないという問題があった。
【００１６】
また、熱源機である冷凍機１は冷温水の送り温度（Chilled Water Supply Temperature）によってもその効率は変化する。その一例を図７に示す。
【００１７】
特性曲線Ｓ１は負荷（Load）が１００％、特性曲線Ｓ２は負荷（Load）が７８％、特性曲線Ｓ３は負荷（Load）が５７％、特性曲線Ｓ４は負荷（Load）が３７％の時の特性曲線をそれぞれ示している。従来は、このような冷凍機１の運用最適化は考慮されず常に一定の温度で運用されるのが一般であった。
【００１８】
本発明の目的は、最適な省エネルギー化を図った空調運転を行うことができる空調システムを提供することである。
【００１９】
【課題を解決するための手段】
請求項１の発明に係る空調システムは、空調用の冷温水を生産する熱源機と、前記熱源機で生産された冷温水の熱を空気に熱交換する空調コイルと、前記熱源機と前記空調コイルとの間の水循環を受け持つポンプと、冷暖房される部屋と前記空調コイルとの間の空気循環を担当するファンと、前記熱源機の動力、前記ファンの動力、前記ポンプの動力を含む下記式で示される空調所要動力Ｊを評価関数とし、前記熱源機、前記ポンプ、前記ファンの運用の制約条件下で前記空調コイルのコイル温度と前記熱源機の冷温水温度を変数とし、非線形または線形計画法を用いて空調所要動力Ｊを最小化する前記空調コイルのコイル温度目標値と前記熱源機の冷温水温度目標値を求める最適化制御器と、前記コイル温度および前記冷温水温度が前記最適制御器で求められたコイル温度目標値および冷温水温度目標値になるように前記ファンおよび前記ポンプを制御するローカル制御器とを備えたことを特徴とする。

ここで、Ｑ_ＨＶＡＣは冷凍機１の負荷、ηは効率（η_{ｃｈｉｌｌｅｒ}は冷凍機１の効率、η_ｐｕｍｐはポンプの効率、η_ｆａｎはファンの効率）、Ｐは定格動力（Ｐ_ｐｕｍｐはポンプの定格動力、Ｐ_ｆａｎはファンの定格動力）、Ｆは流量（Ｆ_{ｗａｔｅｒ}は冷温水の流量、Ｆ_ａｉｒはファン４空気流量）。
【００２０】
請求項１の発明に係る空調システムにおいては、最適化制御器は、冷温水を生産する熱源機の動力、空調コイルで熱交換された空気を送出するファンの動力、熱源機からの冷温水を送出するポンプの動力を含む空調所要動力が最小になるように、空調コイルのコイル温度目標値と熱源機の冷温水温度目標値を求める。ローカル制御器は、コイル温度および冷温水温度が最適制御器で求められたコイル温度目標値および冷温水温度目標値になるように、ファンおよびポンプを制御する。
【００２１】
請求項２の発明に係る空調システムは、空調用の冷温水を生産する熱源機と、前記熱源機の発生する熱を冷却水で熱交換し大気中に放散する冷却塔と、前記熱源機で生産された冷温水の熱を空気に熱交換する空調コイルと、前記冷却塔と前記熱源機との間の冷却水循環を受け持つ冷却水ポンプと、前記熱源機と前記空調コイルとの間の水循環を受け持つポンプと、冷暖房される部屋と前記空調コイルとの間の空気循環を担当するファンと、前記熱源機の動力、前記ファンの動力、前記ポンプの動力を含む下記式で示される空調所要動力Ｊを評価関数とし、前記熱源機、前記冷却塔、前記冷却水ポンプ、前記ポンプ、前記ファンの運用の制約条件下で前記空調コイルのコイル温度と前記熱源機の冷温水温度と前記冷却塔の冷却水温度を変数とし、非線形または線形計画法を用いて空調所要動力Ｊを最小化する前記空調コイルのコイル温度目標値と前記熱源機の冷温水温度目標値と前記冷却塔の冷却水温度目標値とを求める最適化制御器と、前記コイル温度、前記冷温水温度および前記冷却水温度が前記最適制御器で求められたコイル温度目標値、冷温水温度目標値および冷却水温度目標値になるように前記ファン、前記ポンプおよび前記冷却水ポンプを制御するローカル制御器とを備えたことを特徴とする。

ここで、Ｑ_ＨＶＡＣは冷凍機１の負荷、ηは効率（η_{ｃｈｉｌｌｅｒ}は冷凍機１の効率、η_ｐｕｍｐはポンプの効率、η_ｆａｎはファンの効率）、Ｐは定格動力（Ｐ_ｐｕｍｐはポンプの定格動力、Ｐ_ｆａｎはファンの定格動力）、Ｆは流量（Ｆ_{ｗａｔｅｒ}は冷温水の流量、Ｆ_ａｉｒはファン４空気流量）。
【００２２】
請求項２の発明に係る空調システムにおいては、最適化制御器は、熱源機の動力、ファンの動力、ポンプの動力を含む空調所要動力が最小になるように、空調コイルのコイル温度目標値と熱源機の冷温水温度目標値と冷却塔の冷却水温度目標値とを求める。ローカル制御器は、コイル温度、冷温水温度および冷却水温度が最適制御器で求められたコイル温度目標値、冷温水温度目標値および冷却水温度目標値になるように、ファン、ポンプおよび冷却水ポンプを制御する。
【００２３】
請求項３の発明に係る空調システムは、空調用の冷温水を生産する熱源機と、前記熱源機で生産された冷温水の熱を空気に熱交換する空調コイルと、前記熱源機と前記空調コイルとの間の水循環を受け持つポンプと、冷暖房される部屋と前記空調コイルとの間の空気循環を担当するファンと、前記熱源機の動力、前記ファンの動力、前記ポンプの動力を含む下記式で示される空調所要動力Ｊを評価関数とし、前記熱源機、前記ポンプ、前記ファンの運用の制約条件下で前記空調コイルのコイル温度と前記熱源機の冷温水温度を変数とし、非線形または線形計画法を用いて空調所要動力Ｊを最小化する前記空調コイルのコイル温度目標値と前記熱源機の冷温水温度目標値を求める最適化制御器と、前記コイル温度および前記冷温水温度が前記最適制御器で求められたコイル温度目標値および冷温水温度目標値になるように前記ファンおよび前記ポンプに搬送熱量を指示するモデル予測制御アルゴリズムを有した協調制御器と、前記協調制御器からの前記ファンおよび前記ポンプの搬送熱量に基づいて前記ファンおよび前記ポンプの回転数を制御するローカル制御装置とを備えたことを特徴とする。

ここで、Ｑ_ＨＶＡＣは冷凍機１の負荷、ηは効率（η_{ｃｈｉｌｌｅｒ}は冷凍機１の効率、η_ｐｕｍｐはポンプの効率、η_ｆａｎはファンの効率）、Ｐは定格動力（Ｐ_ｐｕｍｐはポンプの定格動力、Ｐ_ｆａｎはファンの定格動力）、Ｆは流量（Ｆ_{ｗａｔｅｒ}は冷温水の流量、Ｆ_ａｉｒはファン４空気流量）。
【００２４】
請求項３の発明に係る空調システムにおいては、最適化制御器は、熱源機の動力、ファンの動力、ポンプの動力を含む空調所要動力が最小になるように、空調コイルのコイル温度目標値と熱源機の冷温水温度目標値を求める。協調制御器はモデル予測制御アルゴリズムを有し、コイル温度および冷温水温度が前記最適制御器で求められたコイル温度目標値および冷温水温度目標値になるように、ファンおよびポンプに搬送熱量を指示する。ローカル制御器は、協調制御器からのファンおよびポンプの搬送熱量に基づいてファンおよびポンプの回転数を制御する。
【００２５】
請求項４の発明に係る空調システムは、空調用の冷温水を生産する熱源機と、前記熱源機の発生する熱を冷却水で熱交換し大気中に放散する冷却塔と、前記熱源機で生産された冷温水の熱を空気に熱交換する空調コイルと、前記冷却塔と前記熱源機との間の冷却水循環を受け持つ冷却水ポンプと、前記熱源機と前記空調コイルとの間の水循環を受け持つポンプと、冷暖房される部屋と前記空調コイルとの間の空気循環を担当するファンと、前記熱源機の動力、前記ファンの動力、前記ポンプの動力を含む下記式で示される空調所要動力Ｊを評価関数とし、前記熱源機、前記冷却塔、前記冷却水ポンプ、前記ポンプ、前記ファンの運用の制約条件下で前記空調コイルのコイル温度と前記熱源機の冷温水温度と前記冷却塔の冷却水温度を変数とし、非線形または線形計画法を用いて空調所要動力Ｊを最小化する前記空調コイルのコイル温度目標値と前記熱源機の冷温水温度目標値と前記冷却塔の冷却水温度目標値とを求める最適化制御器と、前記コイル温度、前記冷温水温度および前記冷却水温度が前記最適制御器で求められたコイル温度目標値、冷温水温度目標値および冷却水温度目標値になるように前記ファン、前記ポンプおよび前記冷却水ポンプに搬送熱量を指示するモデル予測制御アルゴリズムを有した協調制御器と、前記協調制御器からの前記ファン、前記ポンプおよび前記冷却水ポンプの搬送熱量に基づいて前記ファン、前記ポンプ、前記冷却水ポンプの回転数を制御するローカル制御装置とを備えたことを特徴とする。

ここで、Ｑ_ＨＶＡＣは冷凍機１の負荷、ηは効率（η_{ｃｈｉｌｌｅｒ}は冷凍機１の効率、η_ｐｕｍｐはポンプの効率、η_ｆａｎはファンの効率）、Ｐは定格動力（Ｐ_ｐｕｍｐはポンプの定格動力、Ｐ_ｆａｎはファンの定格動力）、Ｆは流量（Ｆ_{ｗａｔｅｒ}は冷温水の流量、Ｆ_ａｉｒはファン４空気流量）。
【００２７】
請求項４の発明に係る空調システムにおいては、最適化制御器は、ファンの動力、ポンプの動力を含む空調所要動力が最小になるように、空調コイルのコイル温度目標値と熱源機の冷温水温度目標値と冷却塔の冷却水温度目標値とを求める。協調制御器はモデル予測制御アルゴリズムを有し、コイル温度、冷温水温度および冷却水温度が最適制御器で求められたコイル温度目標値、冷温水温度目標値および冷却水温度目標値になるように、ファン、ポンプおよび冷却水ポンプに搬送熱量を指示する。ローカル制御器は、協調制御器からのファン、ポンプおよび冷却水ポンプの搬送熱量に基づいて、ファン、ポンプ、冷却水ポンプの回転数を制御する。
【００２８】
請求項５の発明に係る空調システムは、請求項３の発明において、前記ローカル制御器は、予め設定された空気流量とファン回転数との関係を表す関数、冷温水流量とポンプ回転数との関係を表す関数を有することを特徴とする。
【００２９】
請求項５の発明に係る空調システムにおいては、請求項３の発明の作用に加え、ローカル制御器は、予め設定された空気流量とファン回転数との関係を表す関数、冷温水流量とポンプ回転数との関係を表す関数を用いて、回転数制御することにより流量制御を行う。
【００３０】
請求項６の発明に係る空調システムは、請求項４の発明において、前記ローカル制御器は、予め設定された空気流量とファン回転数との関係を表す関数、冷温水流量とポンプ回転数との関係を表す関数、冷却水流量と冷却水ポンプ回転数との関係を表す関数を有することを特徴とする。
【００３１】
請求項６の発明に係る空調システムにおいては、請求項４の発明の作用に加え、ローカル制御器は、予め設定された空気流量とファン回転数との関係を表す関数、冷温水流量とポンプ回転数との関係を表す関数、冷却水流量と冷却水ポンプ回転数との関係を表す関数を用いて、回転数制御することにより流量制御を行う。
【００３２】
【発明の実施の形態】
以下、本発明の実施の形態を説明する。図１は本発明の実施の形態に係る空調システムの構成図である。冷却塔６からの冷却水は冷却水ポンプ７により熱源機である冷凍機１に供給される。冷却水ポンプ７はローカル制御器８ａによりインバータ９ａを介して制御される。ローカル制御器８ａは冷却塔６の冷却水温度Ｔｃｌをフィードバックし冷却水温度が所定の設定値になるように制御する。同様に、冷凍機１からの冷温水はポンプ２により空調コイル３に供給される。ポンプ２はローカル制御器８ｂによりインバータ９ｂを介して制御される。ローカル制御器８ｂは冷凍機１の冷温水温度Ｔｒをフィードバックし冷温水温度Ｔｒが所定の設定値になるように制御する。
【００３３】
また、空調コイル３からの空気はファン４により室内５に供給される。ファン４はローカル制御器８ｃによりインバータ９ｃを介して制御される。ローカル制御器８ｃは空調コイル３の空調コイル温度Ｔｃをフィードバックし空調コイル温度Ｔｃが所定の設定値になるように制御する。また、ダンパ１０はローカル制御器８ｄにより制御される。
【００３４】
このように、本発明の実施の形態における空調システムでは、冷却塔６の冷却水の温度を変化させる機能、冷房負荷量または暖房負荷量に応じて熱源機である冷凍機１の冷温水の出力温度を変化させる機能、冷房負荷量または暖房負荷量に応じて空調コイル３の温度を変化させる機能を有している。
【００３５】
最適化制御器１１は、空調システムのエネルギー消費が最も少なくなるように、熱源機出力温度Ｔｒ、コイル温度Ｔｃ、および冷却水温度Ｔｃｌの目標値を設定するものであり、気温と空調負荷とを入力して、最も省エネルギーを実現する熱源機（冷凍機）出力温度目標値Ｔｒ*、コイル温度目標値Ｔｃ*、冷却水温度目標値Ｔｃｌ*を線形または非線形計画法により求める。
【００３６】
協調制御器１２は、熱源機（冷凍機）出力温度目標値Ｔｒ*、コイル温度目標値Ｔｃ*、冷却水温度目標値Ｔｃｌ*を実現するために、冷却水ポンプ７、ポンプ２、ファン４に搬送熱量を指示するものであり、冷却水ポンプ７の回転数、ポンプ２の回転数、ファン４の回転数を操作し、コイル温度Ｔｃ、熱源機冷温水温度Ｔｒ、冷却水温度Ｔｃｌを所定の設定値に制御するアルゴリズムとして、モデル予測制御アルゴリズムを有する。ローカル制御器８ａ、８ｂ、８ｃは、協調制御器１２から、冷却水ポンプ７、ポンプ２、ファン４に搬送熱量を受けて、冷却水ポンプ７、ポンプ２、ファン４の回転数を指示する。
【００３７】
次に、最適化制御器１１について説明する。最適化制御器１１では、冷凍機出力温度目標値Ｔｒ*、コイル温度目標値Ｔｃ*、冷却水温度目標値Ｔｃｌ*を、下式の総合動力Ｊが最小になるように求める。
【００３８】
【数２】

ここで、Ｑ_ＨＶＡＣは冷凍機１の負荷、ηは効率（η_{ｃｈｉｌｌｅｒ}は冷凍機１の効率、η_ｐｕｍｐはポンプ２の効率、η_ｆａｎはファン４の効率）、Ｐは定格動力（Ｐ_ｐｕｍｐはポンプ２の定格動力、Ｐ_ｆａｎはファン４の定格動力）、Ｆは流量（Ｆ_{ｗａｔｅｒ}は冷温水の流量、Ｆ_ａｉｒはファン４の空気流量）である。また、この評価関数は以下の制約条件を考慮して最小化される。
【００３９】
（制約条件）
【数３】

（５）式は空調コイル３部分で成立する熱量計算式であり、（６）式は冷凍機１部分での温度範囲の制約条件である。ポンプ２や冷却塔６についても同様に制約条件を設定することが可能である。
【００４０】
この場合、最適化すべき評価関数の変数として、熱源機消費エネルギー（Ｑ_ＨＶＡＣ）、ファン動力Ｐ_ｆａｎ、ポンプ動力Ｐ_ｐｕｍｐ等を入力し、制約条件として熱源機の負荷許容範囲、冷温水、冷却水許容範囲、インバータファンやポンプの許容運転範囲等を入力することになる。
【００４１】
ポンプ動力Ｐ_ｐｕｍｐ、ファン動力Ｐ_ｆａｎは、流量Ｆの概ね３乗に比例するので、（４）式で消費エネルギーを表現でき、それを制約条件下で最小化することにより、所望の最適温度目標値を得る。最適化制御器１１では、非線形または線形計画法を所定の時間周期で解くことになる。例えば、冷凍機１、冷却塔６、冷却水ポンプ７、ポンプ２、ファン４等の特性カーブに微小偏差を加えて複数の最適解を求め、その平均値またはメディアンを最適運転指示値とする。
【００４２】
このように、最適化制御器１１は、気温と空調負荷とを入力して、最も省エネルギーを実現する冷凍機出力温度目標値Ｔｒ*、コイル温度目標値Ｔｃ*、冷却水温度目標値Ｔｃｌ*を求め、求めたこれら目標値は協調制御器１２に入力される。
【００４３】
次に、協調制御器１２について説明する。協調制御器１２は制御アルゴリズムとしてモデル予測制御アルゴリズムを有し、冷凍機出力温度目標値Ｔｒ*、コイル温度目標値Ｔｃ*、冷却水温度目標値Ｔｃｌ*が与えられると、冷凍機出力温度Ｔｒ、コイル温度Ｔｃ、冷却水温度Ｔｃｌがそれぞれその目標値になるように、冷却水ポンプ７の回転数、ポンプ２の回転数、ファン４の回転数を操作する指令をローカル制御器８ａ、８ｂ、８ｃに出力する。
【００４４】
すなわち、協調制御器１２のモデル予測制御アルゴリズムは、冷却水ポンプ７、ポンプ２およびファン４の運搬すべき熱量を算出する。ローカル制御器８ａ、８ｂ、８ｃは、この搬送熱量を受けて、冷却水ポンプ７、ポンプ２およびファン４の回転数を制御する。この場合、ローカル制御器８ａには、冷却水ポンプ回転数と冷却水ポンプ７を流れる冷却水流量との関係を表す関数が予め記憶されており、ローカル制御器８ｂには、ポンプ回転数とポンプ２を流れる冷温水の流量との関係を表す関数が予め記憶されており、同様に、ローカル制御器８ｃには、ファン回転数とファン４を流れる空気流量との関係を表す関数が予め記憶されている。従って、ローカル制御器８ａ、８ｂ、８ｃは回転数制御（流量制御）することにより温度制御することになる。
【００４５】
ここで、本発明の実施の形態では、制御すべき温度は３種類あり、同時にその制御端も３台のインバータ９ａ、９ｂ、９ｃである。そして、それぞれの冷却水ポンプ７、ポンプ２、ファン４には運用制限がかかっている。このような複雑な制御系を安定に操作するには、操作量の制限を直接に考慮した最適化制御が最も優れている。このような制御方式をモデル予測制御方式と呼び、従来は化学プラントの分野で使われてきた。
【００４６】
本発明の実施の形態では、このモデル予測制御方式を用いることにより、制約の多いビルなどの空調系に適した協調制御方式を実現する。モデル予測制御アルゴリズムの構成を図２に示す。このモデル予測制御アルゴリズムは、制御しようとする対象の予測モデル１３を内部に持ち、操作量出力部１４からの操作量および制御対象１５の制御量を入力し、操作量の制御量に対する影響を常に評価しながら、最適化計算１６により多数の制御量を同時に制御する。さらに、本発明の実施の形態では、ビル空調システムの空調コイル３や冷凍機１の温度などが下式に示すように、流量と温度の掛け算に関係し双線形系となっている。
【００４７】
【数４】

この空調システムを単純にポンプ２やファン４の回転数変化による流量操作だけで制御しようとすると、そのときの空調コイル３や冷凍機１、部屋の温度により大きく特性が変化し大変安定性の悪いものとなる。
【００４８】
そこで、モデル予測制御アルゴリズムを有した協調制御器１２が出力するのは、冷却水ポンプ７、ポンプ２、ファン４の搬送熱量とし、それを受けて実際に流量を制御するＰＩＤ調節系のローカル制御器８ａ、８ｂ、８ｃを設け、カスケード制御系を採用している。
【００４９】
この構成により、協調制御器１２によるモデル予測制御は、線形システムを制御することになり温度によらず安定した応答が得られる。一方、ＰＩＤ調節系は搬送熱量を目標値として、冷却水ポンプ７、ポンプ２、ファン４の回転数を制御する。搬送熱量や空気、水の流量は実際には測定していないので、前述のように回転数から流量を校正カーブにより算出する関数を持たせている。温度は図１に示したように測定しているので、搬送熱量は下式により容易に計算できる。
【００５０】
【数５】

この空調システムによる制御動作の一例を図３に示す。この実施の形態では、ダンパー制御との協調を保つために空気流量変化に制限値を設けた場合を示している。このように、多数の制御量を制限を満たしながら制御できる。
【００５１】
ここで、本発明の空調システムをビルエネルギー管理システムに組み込んでシステムを構成すると、他のさまざまなビルエネルギー管理システムと協調を図ることができ、さらに全体としての最適化を図ることができる。特に、最適化制御器１１と協調制御器１２とをビル管理システムに組み込むのが、最も他の制御システムとの整合性がよい。また、本発明の空調システムを熱源機制御装置に組み込むこともできる。近年、熱源機の制御装置も容量が大きくなり、本システムを包含させることもできる。これにより安価なシステムを実現することができる。
【００５２】
また、空調システムの一部、例えば、冷凍機１と冷却塔６に関する最適協調制御システム、冷凍機１と空調コイル３に関する最適協調制御システムもまったく同様に構成することができる。ビル等の状態によっては、インバータ化できないポンプやファンが存在することが多く、このような簡略システムは、そのようなケースに省エネを実現することができる。
【００５３】
例えば、ビルや商店、地域などに冷水または温水を供給する少なくとも1台の熱源機を有する空調システムに対して、冷房負荷量または暖房負荷量に応じて熱源機の冷水または温水の出力温度または空調コイルの温度を変化させる。このような機能をビルエネルギー管理システムに組み込むようにしても良いし、熱源機制御装置に組み込むようにしても良い。
【００５４】
【発明の効果】
以上述べたように、本発明によれば、冷却水温度、冷凍機冷温水温度、空調コイル温度を最適化計算により常に最適効率で運用できるように目標値を計算することにより、最適省エネルギー空調運転が可能となる。
【００５５】
また、冷却水温度と所要電力および所要ガスは密接な関係にあり、時間帯別に電力料金は大きく異なるので，省エネルギーおよび省コストの最適運転はそれに応じて、時間帯による冷却水温度、冷凍機冷温水温度、空調コイル温度の最適スケジューリングにより大幅な省コストを図ることができる。
【図面の簡単な説明】
【図１】本発明の実施の形態に係る空調システムの構成図。
【図２】本発明の実施の形態における協調制御器のモデル予測制御アルゴリズムの構成図。
【図３】本発明の実施の形態に係る空調システムによる制御動作の一例を示す特性図。
【図４】従来の空調システムの構成図。
【図５】従来の空調システムにおけるポンプ動力とファン動力との合計を空調コイル温度についてプロットした特性図。
【図６】従来の空調システムの冷凍機がガス炊きボイラによる蒸気吸収式冷凍機である場合の冷却水温度に対する冷却塔ファンの消費動力（電力消費量）およびガス消費量の関係を示す特性図。
【図７】従来の空調システムの熱源機が吸収式冷凍機である場合の成績係数（ＣＯＰ）と冷温水の送り温度との関係を示す特性図。
【符号の説明】
１…冷凍機、２…ポンプ、３…空調コイル、４…ファン、５…室内、６…冷却塔、７…冷却水ポンプ、８…ローカル制御器、９…インバータ、１０…ダンパ、１１…最適化制御器、１２…協調制御器、１３予測モデル、１４…操作量出力部、１５…制御対象、１６…最適化計算[0001]
[Field of the Invention]
The present invention relates to an air conditioning system that performs cooling and heating in a building such as a building or a hospital.
[0002]
[Prior art]
In general, a room temperature control method in a building air conditioning system is a constant air volume control method (CAV method) that controls the flow rate of cold water or hot water produced by a heat source device so that the temperature of a room is measured and becomes a target value. ) And a variable air volume control method (VAV method) in which the amount of cold water or hot water is constant and the air volume is changed. There is also a hybrid system combining both.
[0003]
In the constant air flow rate control method, a pump and a valve are provided in the water circulation system to control the flow rate of cold water (hot water), and the pump sends out water at a constant rotation speed while adjusting the flow rate to a desired value with the valve. In this constant air flow rate control method, the pump power is wasted when the load is moderate, and in recent years, the flow control is performed not by a valve but by an inverter control pump.
[0004]
On the other hand, in the variable air volume control system, the air conditioning fan circulates air at a constant rotation speed and adjusts the air flow rate with a damper. The room temperature is controlled to the target value by adjusting the air flow rate. Also in this case, in recent years, the air flow rate is controlled by an inverter control fan instead of a damper from the viewpoint of energy saving.
[0005]
As described above, in the control of the conventional air conditioning system, the room temperature is controlled to a predetermined value by controlling the valve and the damper by feedback of the room temperature, or by controlling the inverter control pump and the inverter control fan. .
[0006]
On the other hand, the cooling tower is a device for dissipating the heat generated by the heat source device into the atmosphere, but conventionally it is controlled so as to produce cooling water at a constant temperature. For air conditioning, it is generally about 32 ° C.
[0007]
[Problems to be solved by the invention]
However, since the conventional air conditioning system controls the room temperature by operating only the water flow rate or the air flow rate, it is not always operated in a state where the energy consumption is the least.
[0008]
There is a close correlation between the cold water return temperature and the coefficient of performance (COP) of the refrigerator, and the flow rate and required power for fans and pumps. Generally, the higher the cold water return temperature, the higher the refrigerator coefficient of performance (COP). The required power of the fan or pump is proportional to the cube of the flow rate as is well known. In particular, in an air conditioning system equipped with an inverter control fan and an inverter control pump, the water flow rate and air flow rate can be adjusted in any way. It was not necessarily operated by.
[0009]
Consider an air conditioning system as shown in FIG. The temperature of the refrigerator 1 as a heat source device is Tr, the reference temperature is Tr ₀ , the cooling flow rate by the pump 2 is F _W , the reference flow rate is F _W0 , the power of the pump 2 is P _pump , the reference power is P _pump0 , The temperature of the air conditioning coil 3 is Tc, the reference temperature is Tc ₀ , the air conditioning air volume by the fan 4 is Fa, the reference air volume is Fa ₀ , the power of the fan 4 is P _fan , the reference power is P _fan0 , and the room temperature of the room 5 Is Ta, and its reference temperature is Ta ₀ .
[0010]
The relational expression of the power P _pump of the pump 2 is represented by the expression (1), and the relational expression of the power P _fan of the fan 4 is represented by the expression (2). Further, the total f (Tc) of the power of the pump 2 and the power of the fan 4 is shown in the equation (3).
[0011]
[Expression 1]

As shown in the equation (1), the power P _{pump of the} pump 2 is proportional to the cube of the flow rate _FW , and the required flow rate is inversely proportional to the temperature difference unless the load changes. Similarly, the power P _fan of the fan 4 is also proportional to the cube of the flow rate Fa as shown in the equation (2), and the required flow rate is inversely proportional to the temperature difference unless the load changes.
[0012]
FIG. 5 is a characteristic diagram in which the total f (Tc) of the power of the pump 2 and the power of the fan 4 in the formula (3) is plotted with respect to the air conditioning coil temperature Tc. As shown in FIG. 5, the total power f (Tc) varies greatly depending on the air conditioning coil temperature Tc.
[0013]
However, in the conventional air conditioning system, since the pump 2 or the fan 4 is controlled only by the room temperature, minimization of both the power of the pump 2 and the power of the fan 4 is not considered. It was operated in.
[0014]
On the other hand, as for the cooling water produced by the cooling tower, the coefficient of performance (COP) of the refrigerator 1 is improved and the power consumption is reduced as the cooling water temperature is lower. It has the characteristic that the power consumption increases.
[0015]
FIG. 6 is a characteristic diagram showing the relationship between the cooling tower fan power consumption (electric power consumption) and the gas consumption amount with respect to the cooling water temperature when the heat source machine (refrigeration machine) is a steam absorption refrigerator using a gas-fired boiler. is there. As is apparent from FIG. 6, the total power cost of gas and electricity varies depending on the cooling water temperature. In particular, since the electricity rate varies greatly depending on the time of day, there is a problem that the power cost is not minimized by the conventional constant cooling water temperature control.
[0016]
Moreover, the efficiency of the refrigerator 1 as a heat source device also changes depending on the feed temperature of the cold / hot water (Chilled Water Supply Temperature). An example is shown in FIG.
[0017]
The characteristic curve S1 is when the load is 100%, the characteristic curve S2 is when the load is 78%, the characteristic curve S3 is when the load is 57%, and the characteristic curve S4 is when the load is 37%. Each characteristic curve is shown. Conventionally, operation optimization of the refrigerator 1 is not considered and it is generally operated at a constant temperature.
[0018]
The objective of this invention is providing the air-conditioning system which can perform the air-conditioning driving | operation which aimed at the optimal energy saving.
[0019]
[Means for Solving the Problems]
An air conditioning system according to a first aspect of the present invention includes a heat source device that produces cold / hot water for air conditioning, an air conditioning coil that exchanges heat of cold / hot water produced by the heat source device with air, the heat source device, and the air conditioner. A pump responsible for water circulation between the coil, a fan in charge of air circulation between the air-conditioning coil and the air-conditioned room, the following formula including the power of the heat source machine, the power of the fan, and the power of the pump As an evaluation function, the air conditioning required power J shown in the above is used as an evaluation function, and the coil temperature of the air conditioning coil and the cold / hot water temperature of the heat source machine are variables under the constraint conditions of the operation of the heat source machine, the pump, and the fan. and optimization controller to determine the hot and cold water temperature target value of the coil temperature target value of the air-conditioning coil to minimize the air conditioning power required J and the heat source unit by using the law, the coil temperature and the cold water temperature is the lowest Coil temperature target value determined by the controller and controls the fan and the pump so that the hot and cold water temperature target value, characterized in that a local controller.

Where Q _HVAC is the load of the refrigerator 1, η is the efficiency (η _chiller is the efficiency of the refrigerator 1, η _pump is the efficiency of the pump, η _fan is the efficiency of the fan), P is the rated power (P _pump is the pump's efficiency) Rated power, P _fan is the rated power of the fan, F is the flow rate (F _water is the flow rate of cold / hot water, F _air is the fan 4 air flow rate).
[0020]
In the air conditioning system according to the first aspect of the invention, the optimization controller uses the power of the heat source machine that produces cold / hot water, the power of the fan that sends out the air heat-exchanged by the air conditioning coil, and the cold / hot water from the heat source machine. The coil temperature target value of the air conditioning coil and the cold / hot water temperature target value of the heat source unit are obtained so that the required air conditioning power including the power of the pump to be delivered is minimized. The local controller controls the fan and the pump so that the coil temperature and the cold / hot water temperature become the coil temperature target value and the cold / hot water temperature target value obtained by the optimum controller.
[0021]
An air conditioning system according to a second aspect of the present invention includes a heat source unit that produces cold / hot water for air conditioning, a cooling tower that exchanges heat generated by the heat source unit with cooling water and dissipates it into the atmosphere, and the heat source unit. An air conditioning coil for exchanging heat of the produced cold / hot water into air, a cooling water pump responsible for cooling water circulation between the cooling tower and the heat source unit, and a water circulation between the heat source unit and the air conditioning coil. Air conditioning required power J represented by the following formula including the pump in charge, the fan in charge of air circulation between the air-conditioning coil and the air-conditioning room, the power of the heat source machine, the power of the fan, and the power of the pump As an evaluation function, and the coil temperature of the air conditioning coil, the cold / hot water temperature of the heat source machine, and the cooling tower cooling under the constraint conditions of operation of the heat source machine, the cooling tower, the cooling water pump, the pump, and the fan With water temperature as a variable Using non-linear or linear programming optimization control for obtaining a coolant temperature target value of the coil temperature target value of the air-conditioning coil to minimize the air conditioning power required J and hot and cold water temperature target value of the heat source unit and the cooling tower And the fan, the pump so that the coil temperature, the cold / hot water temperature, and the cooling water temperature become the coil temperature target value, the cold / hot water temperature target value, and the cooling water temperature target value obtained by the optimum controller. And a local controller for controlling the cooling water pump.

Where Q _HVAC is the load of the refrigerator 1, η is the efficiency (η _chiller is the efficiency of the refrigerator 1, η _pump is the efficiency of the pump, η _fan is the efficiency of the fan), P is the rated power (P _pump is the pump's efficiency) Rated power, P _fan is the rated power of the fan, F is the flow rate (F _water is the flow rate of cold / hot water, F _air is the fan 4 air flow rate).
[0022]
In the air conditioning system according to the second aspect of the present invention, the optimization controller includes the coil temperature target value of the air conditioning coil so that the power required for air conditioning including the power of the heat source unit, the power of the fan, and the power of the pump is minimized. The target value for the cold / hot water temperature of the heat source unit and the target value for the cooling water temperature of the cooling tower are obtained. The local controller adjusts the fan, pump, and cooling water so that the coil temperature, cold / hot water temperature, and cooling water temperature become the coil temperature target value, cold / hot water temperature target value, and cooling water temperature target value obtained by the optimal controller. Control the pump.
[0023]
An air conditioning system according to a third aspect of the present invention includes a heat source device that produces cold / hot water for air conditioning, an air conditioning coil that exchanges heat of cold / hot water produced by the heat source device with air, the heat source device, and the air conditioner. A pump responsible for water circulation between the coil, a fan in charge of air circulation between the air-conditioning coil and the air-conditioned room, the following formula including the power of the heat source machine, the power of the fan, and the power of the pump As an evaluation function, the air conditioning required power J shown in the above is used as an evaluation function, and the coil temperature of the air conditioning coil and the cold / hot water temperature of the heat source machine are variables under the constraint conditions of the operation of the heat source machine, the pump, and the fan. and optimization controller to determine the hot and cold water temperature target value of the coil temperature target value of the air-conditioning coil to minimize the air conditioning power required J and the heat source unit by using the law, the coil temperature and the cold water temperature is the lowest A cooperative controller having a model predictive control algorithm that instructs the fan and the pump to convey heat quantity so as to be the coil temperature target value and the cold / hot water temperature target value obtained by the controller, and the cooperative controller from the cooperative controller And a local control device for controlling the rotational speeds of the fan and the pump based on the amount of heat transported by the fan and the pump.

Where Q _HVAC is the load of the refrigerator 1, η is the efficiency (η _chiller is the efficiency of the refrigerator 1, η _pump is the efficiency of the pump, η _fan is the efficiency of the fan), P is the rated power (P _pump is the pump's efficiency) Rated power, P _fan is the rated power of the fan, F is the flow rate (F _water is the flow rate of cold / hot water, F _air is the fan 4 air flow rate).
[0024]
In the air conditioning system according to the invention of claim 3, the optimization controller includes the coil temperature target value of the air conditioning coil and the coil temperature target value so as to minimize the power required for air conditioning including the power of the heat source unit, the power of the fan, and the power of the pump. Find the target value of the cold / hot water temperature of the heat source unit. The coordinating controller has a model predictive control algorithm and instructs the fan and pump to transfer heat so that the coil temperature and chilled / hot water temperature become the coil temperature target value and chilled / hot water temperature target value obtained by the optimal controller. To do. The local controller controls the rotation speed of the fan and the pump based on the heat of conveyance of the fan and the pump from the cooperative controller.
[0025]
An air conditioning system according to a fourth aspect of the present invention includes a heat source unit that produces cold / hot water for air conditioning, a cooling tower that exchanges heat generated by the heat source unit with cooling water and dissipates it into the atmosphere, and the heat source unit. An air conditioning coil for exchanging heat of the produced cold / hot water into air, a cooling water pump responsible for cooling water circulation between the cooling tower and the heat source unit, and a water circulation between the heat source unit and the air conditioning coil. Air conditioning required power J represented by the following formula including the pump in charge, the fan in charge of air circulation between the air-conditioning coil and the air-conditioning room, the power of the heat source machine, the power of the fan, and the power of the pump As an evaluation function, and the coil temperature of the air conditioning coil, the cold / hot water temperature of the heat source machine, and the cooling tower cooling under the constraint conditions of operation of the heat source machine, the cooling tower, the cooling water pump, the pump, and the fan With water temperature as a variable Using non-linear or linear programming optimization control for obtaining a coolant temperature target value of the coil temperature target value of the air-conditioning coil to minimize the air conditioning power required J and hot and cold water temperature target value of the heat source unit and the cooling tower And the fan, the pump so that the coil temperature, the cold / hot water temperature, and the cooling water temperature become the coil temperature target value, the cold / hot water temperature target value, and the cooling water temperature target value obtained by the optimum controller. And a cooperative controller having a model predictive control algorithm for instructing the cooling water pump to convey heat, the fan from the cooperative controller, the pump, and the fan based on the conveying heat of the cooling water pump, the pump And a local control device for controlling the rotational speed of the cooling water pump.

Where Q _HVAC is the load of the refrigerator 1, η is the efficiency (η _chiller is the efficiency of the refrigerator 1, η _pump is the efficiency of the pump, η _fan is the efficiency of the fan), P is the rated power (P _pump is the pump's efficiency) Rated power, P _fan is the rated power of the fan, F is the flow rate (F _water is the flow rate of cold / hot water, F _air is the fan 4 air flow rate).
[0027]
In the air conditioning system according to the fourth aspect of the present invention, the optimization controller includes the coil temperature target value of the air conditioning coil and the cold / hot water of the heat source so that the required power for air conditioning including the power of the fan and the power of the pump is minimized. A temperature target value and a cooling tower temperature target value for the cooling tower are obtained. The cooperative controller has a model predictive control algorithm so that the coil temperature, cold / hot water temperature and cooling water temperature become the coil temperature target value, cold / hot water temperature target value and cooling water temperature target value obtained by the optimal controller. Instruct the amount of heat transported to the fan, pump and cooling water pump. The local controller controls the number of rotations of the fan, the pump, and the cooling water pump based on the conveyance heat amount of the fan, the pump, and the cooling water pump from the cooperative controller.
[0028]
The air conditioning system according to a fifth aspect of the present invention is the air conditioning system according to the third aspect of the present invention, wherein the local controller includes a function representing a relationship between a preset air flow rate and a fan rotational speed, a cold / hot water flow rate and a pump rotational speed. It has a function representing a relationship.
[0029]
In the air conditioning system according to the fifth aspect of the invention, in addition to the operation of the third aspect of the invention, the local controller includes a function representing the relationship between the preset air flow rate and the fan rotational speed, the cold / hot water flow rate and the pump rotation. The flow rate is controlled by controlling the number of rotations using a function representing the relationship with the number.
[0030]
The air conditioning system according to a sixth aspect of the present invention is the air conditioning system according to the fourth aspect of the present invention, wherein the local controller includes a function representing a relationship between a preset air flow rate and a fan rotational speed, a cold / hot water flow rate and a pump rotational speed. It has a function representing a relationship, and a function representing a relationship between the coolant flow rate and the coolant pump rotational speed.
[0031]
In the air conditioning system according to the sixth aspect of the invention, in addition to the operation of the fourth aspect of the invention, the local controller includes a function representing the relationship between the preset air flow rate and the fan rotation speed, the cold / hot water flow rate and the pump rotation. The flow rate is controlled by controlling the number of revolutions using a function representing the relationship with the number and a function representing the relationship between the cooling water flow rate and the number of rotations of the cooling water pump.
[0032]
DETAILED DESCRIPTION OF THE INVENTION
Embodiments of the present invention will be described below. FIG. 1 is a configuration diagram of an air conditioning system according to an embodiment of the present invention. The cooling water from the cooling tower 6 is supplied to the refrigerator 1 which is a heat source machine by a cooling water pump 7. The cooling water pump 7 is controlled by the local controller 8a through the inverter 9a. The local controller 8a feeds back the cooling water temperature Tcl of the cooling tower 6 and controls the cooling water temperature to be a predetermined set value. Similarly, cold / hot water from the refrigerator 1 is supplied to the air conditioning coil 3 by the pump 2. The pump 2 is controlled by the local controller 8b via the inverter 9b. The local controller 8b feeds back the cold / hot water temperature Tr of the

refrigerator

1 so as to control the cold / hot water temperature Tr to a predetermined set value.
[0033]
Air from the air conditioning coil 3 is supplied to the room 5 by the fan 4. The fan 4 is controlled by the local controller 8c through the inverter 9c. The local controller 8c feeds back the air conditioning coil temperature Tc of the air conditioning coil 3 and controls the air conditioning coil temperature Tc to be a predetermined set value. The damper 10 is controlled by the local controller 8d.
[0034]
As described above, in the air conditioning system according to the embodiment of the present invention, the function of changing the temperature of the cooling water in the cooling tower 6, the cooling load amount or the heating load amount, the output of the cold / hot water of the refrigerator 1 as the heat source device It has a function of changing the temperature, and a function of changing the temperature of the air conditioning coil 3 in accordance with the cooling load or the heating load.
[0035]
The optimization controller 11 sets target values for the heat source device output temperature Tr, the coil temperature Tc, and the cooling water temperature Tcl so that the energy consumption of the air conditioning system is minimized. Input the heat source machine (refrigerator) output temperature target value Tr *, coil temperature target value Tc *, and coolant temperature target value Tcl * that achieves the most energy saving by linear or nonlinear programming.
[0036]
In order to realize the heat source machine (refrigeration machine) output temperature target value Tr *, the coil temperature target value Tc *, and the cooling water temperature target value Tcl *, the cooperative controller 12 provides the cooling water pump 7, the pump 2, and the fan 4. The amount of heat transported is instructed, and the rotation speed of the cooling water pump 7, the rotation speed of the pump 2, and the rotation speed of the fan 4 are operated, and the coil temperature Tc, the heat source machine cold / hot water temperature Tr, and the cooling water temperature Tcl are set to predetermined values. A model predictive control algorithm is provided as an algorithm for controlling the set value. The local controllers 8 a, 8 b, and 8 c receive the amount of heat transferred from the cooperative controller 12 to the cooling water pump 7, the pump 2, and the fan 4 and instruct the rotation speeds of the cooling water pump 7, the pump 2, and the fan 4.
[0037]
Next, the optimization controller 11 will be described. The optimization controller 11 obtains the refrigerator output temperature target value Tr *, the coil temperature target value Tc *, and the cooling water temperature target value Tcl * so that the total power J of the following equation is minimized.
[0038]
[Expression 2]

Here, Q _HVAC is the load of the refrigerator 1, η is the efficiency (η _chiller is the efficiency of the refrigerator 1, η _pump is the efficiency of the pump 2 , η _fan is the efficiency of the fan 4), P is the rated power (P _pump is The rated power of the pump 2 , P _fan is the rated power of the fan 4, and F is the flow rate (F _water is the flow rate of cold / hot water, and F _air is the air flow rate of the fan 4). This evaluation function is minimized in consideration of the following constraints.
[0039]
(Restrictions)
[Equation 3]

Equation ( 5 ) is a calorific value calculation formula established in the air conditioning coil 3 portion, and equation ( 6 ) is a temperature range constraint condition in the refrigerator 1 portion. Restrictions can be similarly set for the pump 2 and the cooling tower 6.
[0040]
In this case, heat source machine consumption energy (Q _HVAC ), fan power P _fan, pump power P _pump, etc. are input as variables of the evaluation function to be optimized, and the allowable load range of the heat source machine, cold / hot water, cooling water as constraints The allowable range, the allowable operating range of the inverter fan and pump, etc. are input.
[0041]
Since the pump power P _pump and the fan power P _fan are approximately proportional to the cube of the flow rate F, the consumption energy can be expressed by the equation (4), and by minimizing it under the constraint conditions, the desired optimum temperature target Get the value. The optimization controller 11 solves the nonlinear or linear programming with a predetermined time period. For example, a plurality of optimum solutions are obtained by adding minute deviations to the characteristic curves of the refrigerator 1, the cooling tower 6, the cooling water pump 7, the pump 2, the fan 4, etc., and the average value or median is set as the optimum operation instruction value.
[0042]
Thus, the optimization controller 11 inputs the air temperature and the air conditioning load, and sets the refrigerator output temperature target value Tr *, the coil temperature target value Tc *, and the cooling water temperature target value Tcl * that realize the most energy saving. The obtained target values are input to the cooperative controller 12.
[0043]
Next, the cooperative controller 12 will be described. The cooperative controller 12 has a model predictive control algorithm as a control algorithm. When the refrigerator output temperature target value Tr *, the coil temperature target value Tc *, and the coolant temperature target value Tcl * are given, the refrigerator output temperature Tr, Commands for operating the rotation speed of the cooling water pump 7, the rotation speed of the pump 2, and the rotation speed of the fan 4 so that the coil temperature Tc and the cooling water temperature Tcl become the target values, respectively. Output to.
[0044]
That is, the model predictive control algorithm of the cooperative controller 12 calculates the amount of heat that the cooling water pump 7, the pump 2, and the fan 4 should carry. The local controllers 8a, 8b, and 8c receive the amount of heat transported and control the rotational speeds of the cooling water pump 7, the pump 2, and the fan 4. In this case, the local controller 8a stores in advance a function representing the relationship between the cooling water pump rotational speed and the cooling water flow rate flowing through the cooling water pump 7, and the local controller 8b stores the pump rotational speed and the pump. 2 is stored in advance. Similarly, the local controller 8c stores in advance a function indicating the relationship between the fan speed and the air flow rate through the fan 4. ing. Therefore, the local controllers 8a, 8b, and 8c perform temperature control by controlling the rotation speed (flow rate control).
[0045]
Here, in the embodiment of the present invention, there are three types of temperatures to be controlled, and at the same time, the control ends are also the three inverters 9a, 9b, 9c. In addition, operation restrictions are imposed on each of the cooling water pump 7, the pump 2, and the fan 4. In order to stably operate such a complicated control system, the optimization control that directly considers the limitation of the operation amount is the best. Such a control method is called a model predictive control method and has been used in the field of chemical plants.
[0046]
In the embodiment of the present invention, by using this model predictive control method, a cooperative control method suitable for an air conditioning system such as a building with many restrictions is realized. The configuration of the model predictive control algorithm is shown in FIG. This model predictive control algorithm has a predictive model 13 to be controlled inside, inputs the operation amount from the operation amount output unit 14 and the control amount of the control target 15, and always affects the influence of the operation amount on the control amount. While evaluating, a large number of controlled variables are simultaneously controlled by the optimization calculation 16. Further, in the embodiment of the present invention, the temperature of the air conditioning coil 3 and the refrigerator 1 of the building air conditioning system is a bilinear system related to the multiplication of the flow rate and the temperature as shown in the following equation.
[0047]
[Expression 4]

If this air conditioning system is controlled simply by operating the flow rate by changing the rotational speed of the pump 2 or the fan 4, the characteristics change greatly depending on the temperature of the air conditioning coil 3, the refrigerator 1 and the room at that time, and the stability is very poor. It will be a thing.
[0048]
Therefore, the cooperative controller 12 having the model predictive control algorithm outputs the heat quantity of the cooling water pump 7, the pump 2, and the fan 4, and the local control of the PID adjustment system that actually controls the flow rate in response thereto. Units 8a, 8b and 8c are provided and a cascade control system is employed.
[0049]
With this configuration, the model predictive control by the cooperative controller 12 controls the linear system, and a stable response can be obtained regardless of the temperature. On the other hand, the PID adjustment system controls the number of rotations of the cooling water pump 7, the pump 2, and the fan 4 with the conveyance heat amount as a target value. Since the conveyance heat quantity, the air flow rate, and the water flow rate are not actually measured, as described above, a function for calculating the flow rate from the rotation speed by a calibration curve is provided. Since the temperature is measured as shown in FIG. 1, the amount of heat transported can be easily calculated by the following equation.
[0050]
[Equation 5]

An example of the control operation by this air conditioning system is shown in FIG. In this embodiment, a case is shown in which a limit value is provided for the change in air flow rate in order to maintain coordination with damper control. In this way, a large number of control amounts can be controlled while satisfying the restrictions.
[0051]
Here, when the air conditioning system of the present invention is incorporated into a building energy management system to constitute a system, it can be coordinated with other various building energy management systems, and further optimization as a whole can be achieved. In particular, incorporating the optimization controller 11 and the cooperative controller 12 in the building management system is most consistent with other control systems. In addition, the air conditioning system of the present invention can be incorporated into a heat source machine control device. In recent years, the capacity of the control device of the heat source machine has also increased, and this system can be included. Thereby, an inexpensive system can be realized.
[0052]
Also, a part of the air conditioning system, for example, the optimum cooperative control system related to the refrigerator 1 and the cooling tower 6 and the optimal cooperative control system related to the refrigerator 1 and the air conditioning coil 3 can be configured in exactly the same manner. Depending on the state of the building or the like, there are many pumps and fans that cannot be converted into inverters, and such a simplified system can realize energy saving in such a case.
[0053]
For example, for an air conditioning system having at least one heat source unit that supplies cold water or hot water to buildings, shops, areas, etc., the output temperature or air conditioning of the cold source or hot water of the heat source unit according to the cooling load or heating load Change the coil temperature. Such a function may be incorporated into a building energy management system or may be incorporated into a heat source machine control device.
[0054]
【The invention's effect】
As described above, according to the present invention, the optimum energy-saving air-conditioning operation is achieved by calculating the target value so that the cooling water temperature, the refrigerator cold / hot water temperature, and the air-conditioning coil temperature can always be operated at the optimum efficiency by the optimization calculation. Is possible.
[0055]
In addition, the cooling water temperature is closely related to the required power and required gas, and the electricity charge varies greatly depending on the time of day. Significant cost savings can be achieved by optimal scheduling of water temperature and air conditioning coil temperature.
[Brief description of the drawings]
FIG. 1 is a configuration diagram of an air conditioning system according to an embodiment of the present invention.
FIG. 2 is a configuration diagram of a model predictive control algorithm of a cooperative controller according to an embodiment of the present invention.
FIG. 3 is a characteristic diagram showing an example of a control operation by the air conditioning system according to the embodiment of the present invention.
FIG. 4 is a configuration diagram of a conventional air conditioning system.
FIG. 5 is a characteristic diagram in which the sum of pump power and fan power in a conventional air conditioning system is plotted with respect to the air conditioning coil temperature.
FIG. 6 is a characteristic diagram showing the relationship between the cooling tower fan power consumption (electric power consumption) and the gas consumption amount with respect to the cooling water temperature when the conventional air-conditioning system refrigerator is a steam absorption refrigerator using a gas-fired boiler. .
FIG. 7 is a characteristic diagram showing the relationship between the coefficient of performance (COP) and the feed temperature of cold / hot water when the heat source unit of the conventional air conditioning system is an absorption refrigerator.
[Explanation of symbols]
DESCRIPTION OF SYMBOLS 1 ... Refrigerator, 2 ... Pump, 3 ... Air conditioning coil, 4 ... Fan, 5 ... Indoor, 6 ... Cooling tower, 7 ... Cooling water pump, 8 ... Local controller, 9 ... Inverter, 10 ... Damper, 11 ... Optimum Control controller, 12 ... cooperative controller, 13 prediction model, 14 ... manipulated variable output unit, 15 ... controlled object, 16 ... optimization calculation

Claims

A heat source machine that produces cold / hot water for air conditioning, an air conditioning coil that exchanges heat of the cold / hot water produced by the heat source machine with air, a pump that is responsible for water circulation between the heat source machine and the air conditioning coil, A fan in charge of air circulation between a room to be air-conditioned and the air-conditioning coil, the power of the heat source device, the power of the fan, and the power of the pump, and the power required for air-conditioning J represented by the following formula as an evaluation function Using the nonlinear or linear programming method to minimize the air conditioning power requirement J using the coil temperature of the air conditioning coil and the cold / hot water temperature of the heat source machine as variables under the constraint conditions of operation of the heat source unit, the pump, and the fan the coil temperature target value of the air-conditioning coil and the optimization controller to determine the hot and cold water temperature target value of the heat source machines, the coil temperature and the cold water temperature is the optimum controller in the obtained coil temperature target value Air conditioning system characterized by comprising a local controller for controlling the fan and the pump so that the hot and cold water temperature target value and.

Where Q _HVAC is the load of the refrigerator 1, η is the efficiency (η _chiller is the efficiency of the refrigerator 1, η _pump is the efficiency of the pump, η _fan is the efficiency of the fan), P is the rated power (P _pump is the pump's efficiency) Rated power, P _fan is the rated power of the fan, F is the flow rate (F _water is the flow rate of cold / hot water, F _air is the fan 4 air flow rate).

Heat source machine that produces cold / hot water for air conditioning, cooling tower that exchanges heat generated by the heat source machine with cooling water and dissipates it to the atmosphere, and heat of cold / hot water produced by the heat source machine to heat An air conditioning coil to be exchanged, a cooling water pump responsible for cooling water circulation between the cooling tower and the heat source machine, a pump responsible for water circulation between the heat source machine and the air conditioning coil, a room to be air-conditioned and the air conditioning The heat source machine, the cooling, and the heat source machine, the cooling, using the fan in charge of air circulation between the coil, the power of the heat source machine, the power of the fan, and the required air conditioning power J represented by the following formula including the power of the pump as an evaluation function Non-linear or linear programming method with the coil temperature of the air conditioning coil, the cold / hot water temperature of the heat source unit, and the cooling water temperature of the cooling tower as variables under the constraint conditions of operation of the tower, the cooling water pump, the pump, and the fan Using air conditioning And optimization controller for obtaining a coolant temperature target value for the hot and cold water temperature target value of the coil temperature target value of the air-conditioning coil to minimize the main power J and the heat source unit and the cooling tower, the coil temperature, the cold Local for controlling the fan, the pump, and the cooling water pump so that the water temperature and the cooling water temperature become the coil temperature target value, the cold / hot water temperature target value, and the cooling water temperature target value obtained by the optimum controller. An air conditioning system comprising a controller.

A heat source machine that produces cold / hot water for air conditioning, an air conditioning coil that exchanges heat of the cold / hot water produced by the heat source machine with air, a pump that is responsible for water circulation between the heat source machine and the air conditioning coil, A fan in charge of air circulation between a room to be air-conditioned and the air-conditioning coil, the power of the heat source device, the power of the fan, and the power of the pump, and the power required for air-conditioning J represented by the following formula as an evaluation function Using the nonlinear or linear programming method to minimize the air conditioning power requirement J using the coil temperature of the air conditioning coil and the cold / hot water temperature of the heat source machine as variables under the constraint conditions of operation of the heat source unit, the pump, and the fan the coil temperature target value of the air-conditioning coil and the optimization controller to determine the hot and cold water temperature target value of the heat source machines, the coil temperature and the cold water temperature is the optimum controller in the obtained coil temperature target value And a cooperative controller having a model predictive control algorithm for instructing the fan and the pump to convey heat quantity so that the target temperature of the hot / cold water becomes a target value, and based on the conveyed heat quantity of the fan and the pump from the cooperative controller An air conditioning system comprising: a local control device that controls the rotational speed of the fan and the pump.

Heat source machine that produces cold / hot water for air conditioning, cooling tower that exchanges heat generated by the heat source machine with cooling water and dissipates it to the atmosphere, and heat of cold / hot water produced by the heat source machine to heat An air conditioning coil to be exchanged, a cooling water pump responsible for cooling water circulation between the cooling tower and the heat source machine, a pump responsible for water circulation between the heat source machine and the air conditioning coil, a room to be air-conditioned and the air conditioning The heat source machine, the cooling, and the heat source machine, the cooling, using the fan in charge of air circulation between the coil, the power of the heat source machine, the power of the fan, and the required air conditioning power J represented by the following formula including the power of the pump as an evaluation function Non-linear or linear programming method with the coil temperature of the air conditioning coil, the cold / hot water temperature of the heat source unit, and the cooling water temperature of the cooling tower as variables under the constraint conditions of operation of the tower, the cooling water pump, the pump, and the fan Using air conditioning And optimization controller for obtaining a coolant temperature target value for the hot and cold water temperature target value of the coil temperature target value of the air-conditioning coil to minimize the main power J and the heat source unit and the cooling tower, the coil temperature, the cold The amount of heat transferred to the fan, the pump, and the cooling water pump is set so that the water temperature and the cooling water temperature become the coil temperature target value, the cold / hot water temperature target value, and the cooling water temperature target value obtained by the optimal controller. A cooperative controller having a model predictive control algorithm to instruct, and the number of revolutions of the fan, the pump, and the cooling water pump based on the amount of conveyance heat of the fan, the pump, and the cooling water pump from the cooperative controller An air conditioning system comprising a local control device for control.

4. The air conditioning system according to claim 3, wherein the local controller has a function representing a relationship between a preset air flow rate and a fan rotational speed, and a function representing a relationship between a cold / hot water flow rate and a pump rotational speed. .

The local controller has a function representing a relationship between a preset air flow rate and a fan rotational speed, a function representing a relationship between a cold / hot water flow rate and a pump rotational speed, and a relationship between the cooling water flow rate and the cooling water pump rotational speed. The air conditioning system according to claim 4, further comprising a function to represent.