本發明之實施形態擬訂考量了與停止期間相關之各發電機之個別之限制的運轉計畫。 作為本發明之一態樣之運轉計畫擬訂裝置係基於發電機特性資料、運轉限制資料、電力需求資料而擬訂各發電機之運轉計畫者，且具備：運轉狀態決定部，其決定各發電機之運轉狀態；運轉狀態修正部，其修正由運轉狀態決定部決定之各發電機之運轉狀態；及輸出電力決定部，其至少基於經運轉狀態修正部修正之各發電機之運轉狀態而決定各發電機之輸出電力。運轉狀態決定部基於與各發電機之停止期間相關之、對於各發電機共通之限制而決定各發電機之運轉狀態。運轉狀態修正部基於與各發電機之停止期間相關之、對於各發電機之個別之限制而修正各發電機之運轉狀態。 以下，一邊參照圖式一邊針對本發明之實施形態進行說明。 圖1係顯示包含第1實施形態之運轉計畫擬訂裝置之運轉計畫擬訂系統之概略構成之一例之方塊圖。圖1所示之運轉計畫擬訂裝置系統包含：運轉計畫擬訂裝置100、輸入/輸出裝置200、發電機特性資料管理裝置300、運轉限制資料管理裝置400、及電力需求預測裝置500。圖1所示之運轉計畫擬訂裝置100具備：輸入部101、記憶部102、輸出部103、運轉狀態決定部104、運轉狀態修正部105、及輸出電力決定部106。 運轉計畫擬訂裝置100擬訂與發電機之運轉狀態及輸出電力相關之運轉計畫。設想對象發電機存在有複數個。又，將發電機設想為火力發電機而記載，但並不限定於火力發電機。為了擬訂運轉計畫所需之資料自輸入/輸出裝置200被指定。在為了擬訂運轉計畫所需之資料中，包含：發電機特性資料、運轉限制資料、及電力需求資料。 圖2係顯示發電機特性資料之一例之圖。發電機特性資料係表示發電機之特性之資料。此處，在發電機之特性中，含有輸出電力及基於輸出電力之運算值。例如，在發電機特性資料中可包含：輸出電力之最小值、最大值、平均值、發熱量、每發熱量之運轉成本、每單位時間之發熱量等。發電機特性資料用於後述之優化問題之限制條件及目標函數之製作。 運轉限制資料係表示與發電機之運轉相關之限制之資料。例如，在發電機暫時停止後至能夠啟動為止所耗費之時間為運轉限制之一。運轉限制資料被用作後述之優化問題之限制條件。 電力需求資料係表示針對發電機或發電機群要求之電力需求之資料。電力需求資料亦被用作後述之優化問題之限制條件。 又，發電機群係由1台以上之發電機構成之群組。施加於發電機群之運轉限制係施加於屬發電機群之發電機全部。又，1台發電機可屬複數個發電機群。 又，設想為了擬訂運轉計畫所需之資料，從由輸入/輸出裝置200指定之外部之裝置或系統獲得。在圖1中，作為所需資料之獲得源之例，顯示有：發電機特性資料管理裝置300、運轉限制資料管理裝置400、及電力需求預測裝置500。設想發電機特性資料從發電機特性資料管理裝置300獲得，運轉限制資料從運轉限制資料管理裝置400獲得，電力需求資料從電力需求預測裝置500獲得。 針對所擬訂之運轉計畫進行說明。在所擬訂之運轉計畫中顯示有各發電機之運轉狀態及各發電機之輸出電力。圖3係顯示所擬訂之運轉計畫之一例之圖。折線之圖形表示輸出電力。縱軸表示輸出電力之值，橫軸表示時間。 發電機根據所擬訂之運轉計畫，進行停止、啟動等之處理，但在接受停止之指示後至實際上發電機停止為止耗費時間。相同地，在接受啟動之指示後至實際上發電機之輸出到達特定值為止亦耗費時間。將接受停止之指示之發電機實際上自電力系統被切離稱為解列。又，將接受啟動之指示而發電機連接於電力系統稱為並列。在圖3中，與橫軸相接之塗黑之三角形(▲)表示解列之時機。塗白之三角形(△)表示並列之時機。 將自解列至並列之時間稱為發電機之停止期間。又，此處，將停止期間之發電機之運轉狀態記載為停止狀態。將停止狀態以外之運轉狀態記載為啟動狀態。亦即，此處，發電機之運轉狀態分為啟動狀態及停止狀態之2種。在圖3中，在橫軸之下方顯示有該期間之發電機之運轉狀態。在解列與並列之間顯示為停止狀態，在其以外之部分顯示為啟動狀態。 輸出電力在發電機受理停止之指示後不斷下降，在輸出電力成為0之時點進行解列。將該輸出電力下降之部分之圖形稱為停止曲線。又，並列後之發電機之輸出電力逐漸上升，在達到一定之輸出值以後穩定。將該輸出電力上升之圖形稱為啟動曲線。啟動曲線有如圖3般形成階梯狀之情形。 如此般，為了擬訂運轉計畫，而必須求解發電機之運轉狀態及發電機之輸出電力。因此，運轉計畫擬訂裝置100基於發電機特性資料、運轉限制資料、電力需求資料進行運轉狀態決定處理及輸出電力決定處理。運轉狀態決定處理係決定使發電機之運轉狀態發生變更之時機之處理。運轉狀態決定處理係決定發電機之輸出電力之值之處理。 針對運轉計畫擬訂裝置100之構成要素進行說明。首先針對運轉計畫擬訂裝置100之構成要素之處理之流程進行說明。圖4係顯示第1實施形態之運轉計畫擬訂裝置之整體處理之概略流程圖之一例之圖。輸入部101獲得處理所需之資料(S101)。所獲得之資料記憶於記憶部102(S102)。運轉狀態決定部104基於記憶於記憶部102之資料，執行運轉狀態決定處理(S103)。運轉狀態修正部105修正由運轉狀態決定處理算出之運轉狀態(S104)。而後，輸出電力決定部106基於發電機之運轉狀態，執行輸出電力決定處理(S105)。藉此，擬訂包含發電機之運轉狀態及發電機之輸出電力之運轉計畫。而後，輸出部103輸出運轉計畫(S106)。 又，所記載之流程圖為一例，只要獲得所需之處理結果即可，既可進行其他之處理，亦可調換處理之順序等。例如，可在各構成要素之處理之後，輸出部103逐次輸出處理結果。又，可行的是，各處理之處理結果被逐次記憶於記憶部102，各構成要素參照記憶部102而獲得處理結果。此後記載之流程圖亦相同。 輸入部101從外部之裝置獲得運轉計畫擬訂裝置100之處理所需之資料。又，亦可受理針對運轉計畫擬訂裝置100之各構成要素之指令等所需資料以外之資訊。輸入部101將所輸入之資訊傳遞給特定之接收方。接收方並無特別限定。此處，傳遞給記憶部102。 記憶部102記憶輸入部101所接收之資訊。又，亦可記憶運轉計畫擬訂裝置100之各構成要素之處理結果，例如所擬訂之運轉計畫。 記憶部102既可為1個記憶體或儲存器，亦可為複數個記憶體或儲存器，還可為記憶體或儲存器之組合。可根據被記憶之資訊而區分記憶目的地。被記憶之資料可作為資料庫(DB)進行管理。例如，如圖1所示般，於記憶部102可包含：發電機特性資料管理DB，其管理發電機特性資料；運轉限制資料DB，其管理運轉限制資料；及電力需求資料管理DB，其管理電力需求資料。 輸出部103輸出所擬訂之運轉計畫。輸出目的地設想為輸入/輸出裝置200，但輸出目的地並無限定。又，輸出部103可輸出運轉計畫以外之資料。例如，可輸出用於運轉計畫之資料、直至運轉計畫之擬訂為止進行之處理之各處理結果等。又，所輸出之資訊既可從各構成要素獲得，亦可從記憶部102獲得。 輸出部103之輸出方式並無特別限定。輸出部103將處理結果既可作為圖像顯示於畫面，亦可作為檔案而保存。 運轉狀態決定部104藉由進行運轉狀態決定處理而決定發電機之解列及並列之時機。具體而言，藉由求解基於限制條件、及目標函數之優化問題而決定解列及並列之時機。基於所算出之發電機之解列及並列之時機而決定運轉狀態。 將運轉狀態決定部104所進行之處理與流程圖一起進行說明。圖5係顯示運轉狀態決定部之運轉狀態決定處理之流程圖之圖。 運轉狀態決定部104從記憶部102獲得所需之資料，亦即：發電機特性資料、運轉限制資料、及電力需求資料(S201)。其次，運轉狀態決定部104進行目標函數設定處理(S202)。目標函數設定處理係將優化問題之目標函數公式化。目標函數設定處理可採用周知之方法。目標函數可任意設定。例如，既可以使發電機單機或包含複數台發電機之發電機群之運轉成本最小化為目的。亦可以使運轉成本接近特定之目標值作為目標函數。特定之目標值可任意地設定。 又，運轉成本只要係發電機之運轉所花費之費用即可，可包含發電機之運轉所需之物品、人、或服務之費用。發電機之運轉所需之物品既可為燃料等之發電之動力源，亦可為動力源以外之冷卻水、觸媒等。動力源亦無特別限定。例如，可為化石燃料、木質燃料、核燃料。亦可為儲存於堤壩等之揚水。亦可為在氫發電中所使用之甲基環己烷等之化學物質。又，亦可包含因使發電機運轉而產生之費用。例如，亦可包含用於去除因發電而產生之廢氣所含之化學物質之石灰石、液體氨之費用。 其次，運轉狀態決定部104進行限制條件設定處理(S203)。限制條件設定處理係將優化問題之限制條件公式化。限制條件設定處理可採用周知之方法。所擬訂之限制條件可為發電機單機之限制條件、或發電機群之限制條件。發電機群之限制條件可為發電機群整體之發電量、發電機群整體之燃料使用量的發電機群整體之限制條件。或者，可為屬發電機群之發電機各自之限制條件。 最後，運轉狀態決定部104求解基於在目標函數設定處理(S202)中設定之目標函數、及在限制條件設定處理(S203)中設定之運轉限制之優化問題。作為求解方法，可採用2次計畫法、線形計畫法等之周知之優化問題解決方法。又，為了進行求解處理，既可使用專用之程式，亦可使用周知之解算。藉此，決定發電機之解列及並列之時機。而後，運轉狀態決定部104基於所算出之解列及並列之時機，擬訂時間與發電機之運轉狀態之資訊。例如，可為就計畫期間內所決定之複數個區間每一者而顯示運轉狀態之資訊。如此般，運轉狀態決定部104決定發電機之運轉狀態。 惟，當運轉限制過多時，導致處理負荷及計算時間之增加。因此，運轉狀態決定部104將運轉限制之一之停止期間視為一律而決定最佳之時機。例如，假定發電機之停止期間之長度之限制僅為1個而決定發電機之運轉狀態。或者，將與複數台前述發電機各自之停止期間之長度相關之限制全部設為共通，而決定複數台前述發電機各自之運轉狀態。藉此，雖然減少優化問題之求解處理之負荷及計算時間，但運轉計畫之粒度變得粗略。因此，如此下去，由於背離實際情況，故經濟性受損。 運轉狀態修正部105修正由運轉狀態決定部104決定之各發電機之運轉狀態。例如，運轉狀態修正部105基於與發電機之停止期間之長度相關之限制修正發電機之停止期間之長度。藉此，可修正由運轉狀態決定部決定之發電機之運轉狀態。因此，可考量與停止期間相關之每台發電機之多種限制，而可減少與實際情況之背離。 圖6係針對運轉狀態修正部之修正處理進行說明之圖。在圖6(A)至圖6(C)中，顯示在運轉狀態修正部105進行各處理之時點下之運轉計畫案之示意圖。運轉狀態修正部105在解列之時機下製作如圖6(A)所示之停止曲線。停止曲線之製作基於發電機特性資料所含之用於停止曲線之製作之資料而進行。其次，運轉狀態修正部105確認發電機之並列之時機，如圖6(B)所示般算出停止期間。而後，運轉狀態修正部105基於與針對各發電機決定之停止期間相關之個別之運轉限制，如圖6(C)所示般修正停止期間。 圖7係顯示針對發電機決定之停止期間之運轉限制之一例之圖。在圖7中，顯示有2種停止期間之例。在左側所示之表中，停止期間以離散值表示。亦即，表示停止期間為左側所示之表之各值之任一者，在停止期間為該各值之任一者之時機下可能並列。在右側所示之表中，顯示有停止期間之容許範圍。亦即，顯示若停止期間在該容許範圍內則可能並列。又，在圖7中係分成2個表，但停止期間之運轉限制亦可為離散值之情形與容許範圍之情形之二者之組合。 例如，假定基於由運轉狀態決定部104決定之解列及並列之時機之停止期間為500。該情形下，在圖7之左側之表中，編號3之480為小於500且最接近之離散值。因此，在採用圖7之左側之表時，運轉狀態修正部105選擇編號3之運轉限制，為了將停止期間設為400而修正並列之時機。又，以與修正前之停止期間相比修正後之停止期間更短之方式進行修正。此乃緣於若加長停止期間，則無法滿足電力需求而有電力不足之虞之故。 在圖7之右側之表中，500之停止期間在編號2之範圍內。因此，在使用圖7之右側之表時，運轉狀態修正部105不修正並列之時機。 如此般，運轉狀態修正部105以與複數個容許值之任一者一致之方式修正發電機之停止期間之長度。或者，以包含於複數個容許範圍之任一者之方式修正發電機之停止期間之長度。 又，在上述中，係自複數個值或範圍中選擇1個值，但亦可就每台發電機決定不同之值或範圍。圖7之表之編號可為針對各發電機之個別之限制。例如，可將圖7之表之編號1之值及範圍分配給發電機1，將編號2之值及範圍分配給發電機2。如此般，運轉狀態修正部105可針對複數台發電機各者，採用與停止期間之長度相關之個別之限制而修正複數台發電機各自之運轉狀態。另一方面，運轉狀態決定部104在決定複數台發電機各自之運轉狀態時，可將與複數台發電機各自之停止期間之長度相關之限制設為全部共通。例如，在具有3台發電機時，運轉狀態決定部104假定圖7之左側之表之第1號為發電機1之限制，第2號為發電機2之限制，第3號為發電機3之限制。在該情形下，運轉狀態決定部104亦可使3台發電機一起使用第1號之限制。藉此，雖然由運轉狀態決定部104決定之運轉狀態背離實際情況，但由於進行由運轉狀態修正部105實施之修正，結果是運轉計畫不背離實際情況。另一方面，由於將限制設為共通更減少優化問題之複雜程度，故運轉狀態決定部104之處理所耗費之時間變短。 其次，運轉狀態修正部105在並列之時機下，基於發電機特性資料所含之用於啟動曲線之製作之資料而製作如圖6(D)之啟動曲線。最後，運轉狀態修正部105在確認修正解列之時機之必要性之後，修正解列之時機。若如圖6(C)所示般停止期間被修正，則並列之時機提前，但在被提前之並列之時機下，可能有因發電機之檢查等之運轉限制而並列無法提前之情形。在如此之情形下，如圖6(E)所示般，藉由將解列之時機推後而對應。如此般，擬訂運轉計畫案。 所製作之停止曲線及啟動曲線藉由基於發電機與停止期間之運轉限制而決定。例如，在停止期間為短時，在發電機之渦輪中有熱殘留，而可在短時間內提高輸出電力值。另一方面，若停止期間長，則無法一次設為所期望之輸出電力值，而包含輸出電力不上升之期間。因此，如圖6(D)所示般，啟動曲線呈階梯狀。 運轉狀態修正部105為了製作停止曲線及啟動曲線，而使用用於製作停止曲線及啟動曲線之資料。將該資料記載為曲線資料。曲線資料係就發電機及發電機之每一模式而定有輸出電力之值及時間。發電機之模式係與停止期間相應而變化之用於區別發電機之啟動曲線或停止曲線之形狀之種類的指標。 圖8係顯示曲線資料之一例之圖。圖8之上部之表顯示發電機及發電機之模式之與曲線之特性之關係。單元編號表示用於區別各發電機之編號。模式編號表示為了區別模式而附加於每台發電機之相對之編號。次序表示在其單元編號及其模式編號下，曲線之特性之變化之次序。例如，在圖8之上部之表中，若單元編號1之發電機之模式編號為1，則如次序1所示般，輸出0之時間持續0。其次，如次序2所示般，輸出0之時間持續170。且，如次序3所示般，輸出500之時間持續200。另一方面，可知若發電機之模式為2，啟動曲線與發電機之模式為1時不同。如此般，可根據模式而切換啟動或停止曲線。 圖8之下部之表係顯示每台發電機之模式之判斷基準之表。列表示單元編號，行表示模式編號。表之數值表示對應列之發電機在對應行之模式下之停止期間之上限值。例如，在被賦予單元編號1之發電機之停止期間時，當被賦予之停止期間超過第n(n為正整數)-1之模式之上限、且為第n模式之上限以下時，基於圖8之下部之表之表格判斷該發電機為第n模式。 由於啟動曲線受停止期間影響，故藉由使用如此之曲線資料，而運轉狀態修正部105不僅只修正停止期間，而且可基於修正運轉狀態後之停止期間，製作啟動曲線及停止曲線。 圖9顯示運轉狀態修正部之修正處理之流程圖之圖。設想本流程之一系列處理係就計畫期間內所定之每一區間而進行。例如，在進行完第n個區間之處理後，進行第n＋1個區間之處理。又，使用運轉狀態決定部104製作之時間及發電機之運轉狀態之資訊。 運轉狀態修正部105基於時刻及發電機之運轉狀態之資訊，確認當前處理之對象區間之發電機之運轉狀態是否自上次之對象區間發生變化(S301)。若為相同之運轉狀態(S302之否)，則轉移至下一對象區間之處理，再次進行S301之處理。若為不同之運轉狀態(S302之是)，則因對象區間之發電機之運轉狀態而處理產生分歧。 當發電機為停止狀態時(S303之停止狀態)，由於在當前處理之對象區間下存在解列之時機，故運轉狀態修正部105在解列之時機下製作如圖6(A)所示之停止曲線(S304)。在停止曲線之製作後，在進行處理之對象區間為最後之對象區間時(S311之是)，由於針對全部計畫期間已進行完處理，故流程結束。在非為最後之對象區間時(S311之否)，轉移至下一對象區間之處理，再次進行S301之處理。 在發電機為啟動處理運轉狀態時(S303之啟動狀態)，由於在當前處理之對象區間存在並列之時機，故運轉狀態修正部105基於並列之時機及在S304中已確認之解列之時機算出停止期間(S305)。而後，在所算出之停止期間滿足如圖7所示之停止期間之運轉限制時(S306之是)，運轉狀態修正部105在並列之時機下製作啟動曲線(S310)。而後，確認是否為運轉計畫內之最後之對象區間(S311)，或者轉移至下一對象區間之處理(S311之否)，或者結束流程(S311之是)。 若所算出之停止期間不滿足停止期間之運轉限制時(S306之否)，運轉狀態修正部105判斷是否可提前並列之時機。若並列之時機可提前時(S307之是)，藉由提前並列之時機而修正停止期間(S308)。若並列之時機之提前為不可能時(S307之否)，藉由推後解列之時機而修正停止期間(S309)。又，藉由推後解列之時機而如圖6(E)所示般，移動已製作完畢之停止曲線。如此般，算出滿足停止期間之運轉限制之新的停止期間。 而後，運轉狀態修正部105在藉由修正而產生之新的並列之時機下，製作啟動曲線(S310)。又，如前述所述般，基於藉由修正而產生之新的停止期間決定發電機之模式，運轉狀態修正部105在新的並列之位置製作基於發電機之模式之啟動曲線。 而後，確認是否為運轉計畫內之最後之對象區間(S311)，或者轉移至下一對象區間之處理(S311之否)，或者結束流程(S311之是)。 針對全部發電機執行以上之流程。在無執行對象之發電機時，運轉狀態修正部105之處理結束。 輸出電力決定部106進行決定各發電機之每單位期間之輸出電力之值之輸出電力決定處理。具體而言，藉由求解基於運轉限制及目標函數之優化問題而算出各發電機之輸出電力之值。單位期間意味著將運轉計畫之計畫期間區分為複數個期間之最小之期間。將單位期間稱為網目。 在輸出電力決定部106所計算之優化問題之限制條件中，含有由運轉狀態修正部105修正之與發電機之運轉狀態相關之限制條件。藉此，將運轉狀態修正部105之修正反映於所擬訂之運轉計畫中。 將輸出電力決定部106決定各發電機之輸出電力之值之處理與流程圖一起進行說明。圖10顯示輸出電力決定部之輸出電力決定處理之流程圖之圖。 輸出電力決定部106自記憶部102獲得必要之資料，亦即發電機特性資料、運轉限制資料、及電力需求資料(S401)。在所獲得之運轉限制資料中，含有由運轉狀態修正部105修正之發電機之運轉狀態。亦即，包含：解列之時機、並列之時機、啟動曲線、停止曲線。 其次，輸出電力決定部106進行目標函數設定處理(S402)。而後，輸出電力決定部106進行限制條件設定處理(S403)。目標函數設定處理及限制條件設定處理與運轉狀態決定部104之處理相同即可。 最後，輸出電力決定部106求解基於在目標函數設定處理(S402)中設定之目標函數、及在限制條件設定處理(S403)中設定之運轉限制之優化問題(S404)。該處理與運轉狀態決定部104之處理相同即可。藉此，算出計畫期間之各發電機之輸出電力之值而擬訂運轉計畫。 如此般擬訂之運轉計畫與僅考量一律之最低停止期間之運轉計畫不同。例如，即便在啟動曲線之輸出電力之值及時間相應於停止期間就每台發電機決定時，仍可擬訂考量該等之運轉計畫。又，停止期間之限制即便為4小時、8小時、14小時之離散之值，或是4小時至16小時之連續之時間仍可對應。藉此，可使運轉計畫符合實際情況。 如以上所述般，根據本實施形態，能夠擬訂考量複數個停止期間之運轉計畫。又，運轉狀態決定部104所進行之優化問題之求解在基於單一之停止期間執行時，與考量複數個停止期間求解優化問題相比求解之時間變短。藉此，可縮短相應於實際情況之運轉計畫之擬訂所耗費之時間。 又，上述之實施形態為一例，上述實施形態之構成要素之一部分可位於外部之裝置。例如，上述之實施形態具有運轉狀態決定部104，但運轉狀態決定部104亦可位於外部之裝置。該情形下，輸入部101可自外部之裝置獲得解列及並列之時機，且傳遞給運轉狀態修正部105。 又，計畫擬訂裝置亦可由可藉由通信或電氣信號進行資料之交接之複數個裝置構成。例如，可分為具有運轉狀態決定部104及運轉狀態修正部105之第1裝置、及具有輸出電力決定部106之第2裝置。 (第2實施形態) 在第2實施形態中，在進行運轉狀態決定部104之優化問題之求解之前，調整用於運轉計畫之資料。例如，藉由本調整而擬訂加進有時間變動之資料。如圖2所示之發電機特性資料般，發電機之特性之值在各發電機中大多被設為一定。然而，實際上而言，可能有根據發電機周圍之環境等而發電機之特性之值發生變化之情形。因此，將在運轉計畫之計畫期間內被設為一定的特性之值就計畫期間之每單位期間進行調整，可擬訂更符合實際情況之運轉計畫。 又，在本實施形態中，例如可基於已有之運轉限制資料製作新的運轉限制資料。可能存在即便不藉由優化問題進行求解，基於運轉限制而決定發電機之運轉狀態或輸出電力之情形。因此，基於已有之運轉限制，算出發電機之運轉狀態或輸出電力，並新擬訂與所算出之運轉狀態等相關之運轉限制。藉此，在優化問題上應探討之組合變少，而可使擬訂運轉計畫之時間較第1實施形態更加縮短。 圖11係顯示包含第2實施形態之運轉計畫擬訂裝置之運轉計畫擬訂系統之概略構成之一例之方塊圖。在圖11所示之運轉計畫擬訂裝置100之系統中進一步包含環境資料管理裝置600。圖11所示之第2實施形態之運轉計畫擬訂裝置100相對於第1實施形態進一步具備資料調整部107。 在第2實施形態中，運轉計畫擬訂裝置有獲得相應於時間而變動之資料之情形。將相應於時間而變動之資料記載為時間變動資料。如圖11所示般，此處，設想運轉計畫擬訂裝置100自環境資料管理裝置600獲得環境資料作為時間變動資料。環境資料係例如溫度、氣壓、天氣等之與發電機周圍之環境相關之資料，該等之值相應於時間而變動。因此，環境資料相當於時間變動資料。所獲得之環境資料與其他資料相同地被記憶於記憶部102。 又，在因保養等而運轉限制等發生變化時，所變化之運轉限制亦相當於時間變動資料。例如，在發電機群中，在通常時，即便在已決定啟動狀態之台數時，但因保養等而可能有該台數發生變化之情形。如此之因時間所致之運轉限制亦相當於時間變動資料。又，在獲得相當於時間變動資料之運轉限制時，可無需獲得環境資料。 針對第2實施形態之運轉計畫擬訂裝置100之構成要素進行說明。將與截至目前之實施形態相同之點省略說明。 資料調整部107在運轉狀態決定部104執行運轉狀態決定處理之前，實施對該各處理所使用之資料之調整處理。圖12係顯示第2實施形態之運轉計畫擬訂裝置之整體處理之概略流程圖之一例之圖。與第1實施形態之運轉計畫擬訂裝置之整體處理之概略流程圖相比，在S103之處理之前追加資料調整部107之資料調整處理(S501)。 圖13係顯示資料調整部之資料調整處理之流程圖之圖。又，在本流程中，針對在輸入資料之正常確認(S602)之後，進行發電機單位期間資料製作處理(S603)、發電機群單位期間資料製作處理(S604)、發電機輸出固定處理(S605)、及運轉限制插補處理(S606)之4個處理之情形進行說明。然而，發電機單位期間資料製作處理(S603)、發電機群單位期間資料製作處理(S604)、發電機輸出固定處理(S605)、及運轉限制插補處理(S606)係彼此獨立之處理。因此，無須全部進行該等4個處理，而執行至少任一個處理即可。資料調整部107可發揮相應於該等4個處理中被進行之處理之功能。又，進行該等4個處理之次序並無特別限定。該等4個處理可並行地進行。 又，各處理可以獨立之構成要素進行。例如，資料調整部107可具備：發電機單位期間資料製作部，其製作發電機單位期間資料；發電機群單位期間資料製作部，其製作發電機群單位期間資料；預先決定部，其進行發電機輸出固定處理；及插補部，其進行運轉限制插補處理。或者，可將資料調整部107置換為發電機群單位期間資料製作部、發電機群單位期間資料製作部、預先決定部、或插補部。 資料調整部107獲得調整所需之資料(S601)。調整所需之資料根據上述之4個各處理而不同。上述之4個各處理所需之資料在各處理中敘述。 其次，資料調整部107確認所獲得之資料之符合性。在由於在所獲得之資料內含有異常值等而判斷為無符合性時，流程結束。又，可將錯誤訊息經由輸出部103輸出至輸入/輸出裝置200。 其次，資料調整部107為了掌握變動之發電機之特性，而製作表示每單位期間之發電機之特性之資料(S603)。將表示每單位期間之發電機之特性之資料記載為發電機單位期間資料。在用於算出發電機單位期間資料的資料中，包含發電機特性資料及時間變動資料。 在圖14及圖15中，顯示用於算出發電機單位期間資料的資料。圖14係顯示用於算出發電機單位期間資料的發電機特性資料之一例之圖。圖14所示之資料係表示發電機輸出與發電效率之關係之資料。 圖14之表示發電機輸出與發電效率之關係之資料不表示與時間之關係。然而，已知發電效率因相應於時間而變化的大氣溫度等之外部要因而變化。因此，在使用不表示與時間之關係之圖14之發電機特性資料擬訂運轉計畫時，有運轉計畫背離實際情況之虞。 圖15係顯示用於算出發電機單位期間資料的時間變動資料之一例之圖。圖15所示之時間變動資料係表示每單位期間之大氣溫度之氣象資料。如上述所述般，已知發電效率因外部要因而發生變化。因此，考量圖15所示之大氣溫度之影響而調整發電機輸出之發電效率之值。例如，基於複數個測定結果使用最小二乘法等調整發電效率之值。 而後，基於經調整之發電效率之值算出每單位期間之發電機之特性。圖16係顯示發電機單位期間資料之一例之圖。在圖16中，表示單位期間為30分鐘時之各單位期間之發電機之特性。作為以網目單位變動之特性之一例，顯示有表示與發電機之燃料相關之特性之2次近似式所含之複數個係數、最大輸出、最低輸出等。若輸出效率變化，則輸出電力變化，且相應於此燃料消耗量等亦變化。又，發電單價如圖2所示般包含於發電機特性資料。如此般，針對2次近似式、最大輸出之發電機之特性亦然，亦可加進相應於時間而變動之大氣溫度之影響。 如此般，藉由進行發電機單位期間資料製作之處理，而製作表示每網目之值之變動之發電機單位期間資料。如此般，藉由資料調整部107可將在運轉計畫之計畫期間內值為一定之發電機特性資料或運轉限制資料之值就運轉計畫之計畫期間內之複數個區間每一者而調整。而後，藉由使用時間變動資料擬訂運轉計畫，而可擬訂符合實際情況之精確之運轉計畫。 其次，資料調整部107為了掌握變動之發電機群之特性，而製作表示每單位期間之發電機之特性之資料(S604)。將表示每單位期間之發電機群之特性之資料記載為發電機群單位期間資料。在用於算出發電機群單位期間資料的資料中，包含發電機群資料及時間變動資料。 發電機群資料係發電機群之發電機資料，不是表示發電機單機之特徵，而是表示發電機群之特徵。又，針對1個發電機群可決定複數個特徵。 圖17係顯示用於算出發電機群單位期間資料的資料之例之圖。圖17之上部之表係發電機群資料之一例。顯示各發電機群之編號、及屬該發電機群之發電機之編號。圖17之下部之表係發電機群資料之另一例。表示通常時之各發電機群之運轉台數。 圖18係時間變動資料之一例。顯示圖17之下部之表所示之通常時之運轉台數自變更開始之時刻至變更結束之時刻變更為圖18所示之變更值。亦即，圖18之資料相當於時間變動資料之運轉限制。 圖19至圖21分別顯示發電機群單位期間資料之第1例至第3例之圖。圖19之發電機群單位期間資料藉由針對在圖17之下部之表所示之發電機群之運轉台數之資料，組合在圖18中所示之時間變動之運轉限制資料而製作。圖19之發電機群單位期間資料表示就每網目發電機群之運轉台數。因此，藉由將圖19之發電機群單位期間資料用作運轉限制，而可使各網目之運轉計畫更符合實際情況。 又，圖20表示每網目之發電機群之輸出範圍。圖21表示每網目之發電機群之燃料消耗量之範圍。圖20及圖21之資料亦為與發電機群相關之資料就每網目而展開之資料之例。針對該等之資料亦然，藉由將通常時之資料基於氣溫等之氣象資料、運送燃料之時刻等之燃料庫存資料之時間變動資料進行修正，而可設為每網目之資料。 如此般，藉由發電機群資料製作之處理，而基於發電機群資料及時間變動資料製作包含每網目之資料之發電機群單位期間資料。而後，藉由基於發電機群單位期間資料擬訂運轉計畫，而可實現符合實際情況之精確之運轉計畫。 其次，資料調整部107進行發電機輸出固定處理(S605)。發電機輸出固定處理係基於發電機特性資料及運轉限制資料之至少任一者，決定發電機之特定期間內之狀態或輸出電力之處理。 在第1實施形態中，運轉狀態決定部104針對全部發電機算出解列及並列之時機。然而，運轉狀態決定部104所進行之組合優化問題之求解非常複雜。因此，若將優化問題之對象設為全部發電機，則擬訂出運轉計畫之時間變長。因此，在本實施形態中，在運轉狀態決定部104之處理之前。先決定一部分發電機之解列及並列之時機。被決定之一部分發電機之解列及並列之時機作為運轉限制被賦予運轉狀態決定部104。藉此，在運轉狀態決定部104之組合優化問題上，計算範圍被限定，而可實現運轉計畫擬訂之高速化。 在發電機輸出固定處理中，例如，在藉由複數個運轉限制指定針對特定之發電機之運轉狀態、輸出電力等時，基於優先級等而合成複數個運轉限制。 圖22係針對發電機輸出固定處理進行說明之圖。設定針對某1台發電機具有與輸出電力相關之運轉限制之第1運轉限制及第2運轉限制此2個運轉限制。自上向下之第1個圖形表示第1運轉限制，自上而下之第2個圖形表示第2運轉限制。又，圖形之縱軸表示輸出電力，橫軸表示時間。又，設定自上而下之第1個圖形優先級高於第2個圖形。又，在圖形與橫軸為一致之期間不是將輸出電力設為0，而是意味著在此期間內運轉限制未被規定。因此，在圖22所示之網目2及網目3之期間內，施加第1運轉限制及第2運轉限制之二者。在具有如此之2個運轉限制時，資料調整部107合成2個運轉限制。自上而下之第3個圖形表示合成後之運轉限制。 在網目1之區間內，由於第1運轉限制未被規定，故合成後之運轉限制之圖形與第2運轉限制之圖形一致。在網目2及網目3之區間內，由於規定有優先級為高之第1運轉限制，故合成後之運轉限制之圖形與第1運轉限制之圖形一致。資料調整部107如此般將2個運轉限制置換為1個新的運轉限制。藉此，可減少運轉狀態決定部104操作之運轉限制之數目。 圖23係顯示合成後之運轉限制之一例之圖。與發電機群單位期間資料相同，製作每網目之運轉限制。 又，例如，在針對某台發電機有與運轉狀態之期間相關之運轉限制時，可能有該運轉限制雖不是直接指定輸出電力，但基於該運轉限制將輸出電力決定為唯一之情形。因此，在無關於優化問題，基於特定之發電機之運轉限制而可決定特定期間之特定之發電機之輸出電力時，資料調整部107可決定特定之發電機輸出電力，且可將其作為運轉限制。 圖24係顯示相關於基於與運轉狀態之期間相關之運轉限制而算出之發電機之輸出電力的運轉限制之一例之圖。假定有在自時刻3：00至時刻4：30之期間內，將發電機8設為停止狀態之運轉限制。在該假定中，資料調整部107與運轉狀態修正部105產生停止曲線及啟動曲線相同地就每網目決定輸出電力之值。藉此，如圖24所示般，製作與每網目之輸出電力相關之運轉限制。 如此般，藉由發電機輸出固定處理基於運轉限制而製作與輸出電力相關之新的運轉限制。藉此，在運轉狀態決定部104之組合優化問題上應探討之組合變少，而可使擬訂運轉計畫之時間較第1實施形態更加縮短。 其次，資料調整部107進行運轉限制插補處理(S606)。運轉限制插補處理係基於與某特定之發電機之停止期間相關之複數個運轉限制，算出與新的停止期間相關之運轉限制之處理。 圖25係針對運轉限制插補處理進行說明之圖。假定針對某1台發電機，具有複數個與停止期間相關之運轉限制。資料調整部107基於該複數個運轉限制，如圖25(A)所示般，掌握停止期間A、停止期間B、及停止期間C。 其次，資料調整部107基於該等之停止期間及發電機特性資料，插補複數個停止期間之間的運轉狀態。具體而言，考量發電機啟動所需之時間、停止所需之時間，而判定在停止期間之間發電機能否啟動。例如，如圖25(B)所示般，在停止期間A與停止期間B之間判斷為能夠啟動，但在停止期間B與停止期間C之間判斷為無法啟動。 而後，資料調整部107將判定為無法啟動之期間設為停止期間，而將複數個停止期間合為1個停止期間。在圖25(C)中，由於停止期間B與停止期間C之間成為插補後之停止期間，而決定包含停止期間B及停止期間C之1個停止期間D。藉此，將與停止期間B相關之運轉限制及與停止期間C相關之運轉限制彙總為與停止期間D相關之運轉限制。 如此般，資料調整部107基於發電機啟動所需之時間及發電機停止所需之時間，將發電機之第1停止期間與發電機之第2停止期間之間的期間作為新的停止期間。藉此，停止期間變長，在運轉狀態決定部104之組合優化問題上應探討之組合變少，而可將擬訂運轉計畫之時間較第1實施形態更加縮短。 又，資料調整部107可基於可導出停止期間之運轉限制，算出停止期間並進行運轉限制插補處理。 以上為資料調整部107之資料調整處理之流程圖。如此般，將資料調整部107之各處理中算出之結果傳遞至運轉狀態決定部104。運轉狀態決定部14進一步基於該等之處理結果，決定發電機之運轉狀態。 如以上所述般，根據本實施形態，藉由資料調整部107調整運轉狀態決定部104所使用之資料。藉此，對於先前未考量到因時間所致之變動之資料，進行依循時間軸之調整，而可擬訂符合實際之應用之精確之運轉計畫。又，在優化問題上應探討之組合變少，可將擬訂運轉計畫之時間較第1實施形態更加縮短。 (第3實施形態) 在第3實施形態中，在藉由運轉狀態決定部104進行優化問題之求解之前，基於一部分運轉限制算出解列及並列之時機。將基於該一部分運轉限制而算出之解列及並列之時機記載為初始解。該初始解係用於緩和運轉狀態決定部104之組合優化問題。 圖26係顯示第3實施形態之運轉計畫擬訂裝置之概略構成之一例之方塊圖。第3實施形態除了第2實施形態以外，還具備初始解產生部108。又，亦可為在第1實施形態上添加初始解產生部108。將與截至目前之實施形態相同之點省略說明。 初始解產生部108基於複數個運轉限制之一部分算出運轉計畫之初始解。由於優化問題之求解非常複雜，故在使運轉狀態決定部104處理全部時，增加處理負荷及擬訂之時間。又，對運轉狀態決定部104要求之處理能力變高，而對運轉計畫擬訂裝置100之製作費用等產生影響。因此，本實施形態使初始解產生部108亦算出解列及並列之時機。惟，由於初始解產生部108不考量運轉限制全部，故初始解產生部108之處理能力可低於運轉狀態決定部104。又，求解方法亦可與運轉狀態決定部104不同。如此般，由於藉由將優化問題之求解分成複數個處理，可抑制運轉狀態決定部104之處理負荷，因此亦可抑制運轉狀態決定部104之處理能力。 又，用於初始解之算出之運轉限制之數目愈多，愈可確保運轉狀態決定部104算出之解之精度，且可愈加縮短運轉狀態決定部104求出解之時間。 初始解之算出方法可不是求解最佳組合，而是就每網目針對時間軸在沿著順方向或反方向下算出解。亦可基於在沿著順方向下算出之解及在沿著反方向下算出之解之二者而算出。又，既可在計畫期間整體上算出解，亦可限定於計畫期間內之特定之期間而算出解。又，在使用如第2實施形態之發電機群單位期間資料之每網目之資料時，初始解產生部108就每網目算出初始解。 例如，可將賦予每網目之電量作為運轉限制，以運轉成本為最小之方式算出。又，在就所決定之發電單價累加輸出，無法滿足運轉限制時，可採用以滿足運轉限制之方式變更一部分發電機之輸出，直至滿足運轉限制為止累加輸出之方法。 又，初始解產生部108與運轉狀態決定部104相同地可使用公式化之數理規劃法。該情形下，與運轉狀態決定部104相同地，由於進行目標函數設定處理、限制條件設定處理、最適問題之求解即可，故省略說明。 圖27係顯示第3實施形態之運轉計畫擬訂裝置之整體處理之概略流程圖之一例之圖。初始解產生部108在資料調整部107執行資料調整處理後(S501)產生初始解(S701)。與第2實施形態之運轉計畫擬訂裝置100之整體處理之概略流程圖相比，在S501之後追加初始解產生部108之初始解之產生之處理(S701)。又，與第1實施形態相同地，運轉狀態決定部104執行運轉狀態決定處理(S702)。惟，由於本實施形態之運轉狀態決定處理包含使用初始解之處理，故一部分與第1實施形態不同。此後之處理與截至目前之實施形態相同。 針對第3實施形態之運轉狀態決定部104之運轉狀態決定處理進行說明。第3實施形態之運轉狀態決定部104進一步進行運轉狀態模式製作處理及運轉狀態模式削減處理。針對運轉狀態模式製作處理及運轉狀態模式削減處理與處理之流程一起進行說明。圖28係顯示第3實施形態之運轉狀態決定部之運轉狀態決定處理之流程圖之圖。 運轉狀態決定部104與截至目前之實施形態相同，在獲得必要之資料後(S201)，針對各發電機進行運轉狀態模式製作處理(S802)。運轉狀態模式製作處理係擬訂特定之範圍之表示發電機之運轉狀態之候選之組合之運轉狀態模式。運轉狀態模式藉由自複數個特定之時機候選選擇解列與並列之時機而擬訂。 圖29係說明運轉狀態模式之圖。解列與並列之時機之候選就每網目而決定。圖29顯示運轉狀態模式1至運轉狀態模式3。如此般，在特定範圍內，組合運轉狀態之候選，亦即啟動狀態與停止狀態，而製作複數個運轉狀態模式。 又，與第1實施形態相同，就每台發電機決定停止期間之運轉限制。又，啟動狀態之運轉限制係決定最低啟動時間，且設定啟動狀態之時間為最低啟動時間以上。 最低啟動時間以啟動曲線之所需時間與將緊接著啟動曲線後之輸出作為停止曲線之開始起點時之停止曲線之所需時間的和來表示。亦即，意味著自發電機之並列起在無須使發電機穩定作動下可使其最快解列為止之時間。又，啟動曲線與截至目前之實施形態相同，可相應於停止期間而所需時間不同。或者，無關於停止期間，可藉由特定之啟動曲線及停止曲線決定最低啟動時間。又，用於最低啟動時間之算出之啟動曲線及停止曲線可與被稱為試運轉曲線的通常之啟動曲線及停止曲線不同。 又，運轉狀態之製作範圍既可為計畫期間整體，亦可為計畫期間之一部分。計畫期間之一部分可為藉由將計畫期間基於特定之條件區劃而製作之期間。例如，可將1日作為運轉狀態之製作範圍。 其次，運轉狀態決定部104選擇使用初始解還是不使用初始解(S802)。在使用初始解時(S802之是)，判定是否實施運轉狀態模式削減處理(S803)。在實施運轉狀態模式削減處理時(S803之是)，基於由初始解產生部108製作之初始解削減運轉狀態模式(S804)。 運轉狀態模式之削減處理係基於並列及解列之時機之初始解，限定發電機之運轉狀態變化之網目之處理。若假定初始解具有一定之精度，則可考量在初始解之時機之附近具有正解之時機。因此，削除運轉狀態模式中之不符合特定之條件者，而可減少運轉狀態模式。 例如，如圖29之最下圖所示般，藉由初始解判明解列之時機為範圍A，且判明並列之時機為範圍B。該情形下，由於運轉狀態模式1在範圍A內不被解列，故被削除。又，由於運轉狀態模式3在範圍B內不被並列，故被削除。在圖29中所示之運轉狀態模式2由於在範圍A內解列，且在範圍B內並列，故不被削除而保留。運轉狀態決定部104如此般基於初始解，自所算出之複數個前述運轉狀態模式獲得與條件相符之前述運轉狀態模式。 又，在圖29中以範圍A與範圍B所示之解列之範圍及並列之範圍之寬度可任意決定。範圍之寬度亦可基於發電機特性資料或運轉限制資料而算出。 又，亦可將之前所擬訂之運轉計畫之解列及並列之時機作為初始解。亦即，可基於之前所擬訂之運轉計畫之解列及並列之時機，進行運轉狀態模式削減處理。 如此般，藉由削減運轉狀態模式，而可縮短運轉狀態決定部104之運轉狀態決定處理所耗費之時間。 在不使用初始解時(S802之否)，不實施運轉狀態模式削減處理時(S803之否)，及實施運轉狀態模式削減處理(S804)後，運轉狀態決定部104執行目標函數設定處理(S202)。與所獲得之條件相符之前述運轉狀態模式亦包含於目標函數。由於此後之處理與截至目前之實施形態相同，故省略。如此般，運轉狀態決定部104進一步基於與條件相符之運轉狀態模式決定發電機之運轉狀態。 如以上所述般，根據本實施形態，初始解產生部108求得至少滿足一部分運轉限制之初始解。而後，運轉狀態決定部104基於初始解削減運轉狀態模式。藉此，可限定由運轉狀態決定部104求解之優化問題之範圍。因此，運轉狀態決定部104之處理所耗費之時間變短，而可在隨著運用之時間內算出解。 本發明之全部實施形態之各處理可藉由軟體(程式)而實現。因此，上述所說明之各實施形態例如可藉由將通用之電腦裝置用作基本硬體，使搭載於電腦裝置之中央處理裝置(CPU：Central Processing Unit，中央處理單元)等之處理器執行程式而實現。 圖30係顯示本發明之一實施形態之運轉計畫擬訂裝置之硬體構成之一例之方塊圖。運轉計畫擬訂裝置100可以電腦裝置700而實現，該電腦裝置700具備：處理器701、主記憶裝置702、輔助記憶裝置703、網路介面704、及裝置介面705，且將該等經由匯流排706連接。又，運轉計畫擬訂裝置100可具備通用之輸入裝置及輸出裝置作為輸入/輸出裝置200。 本實施形態之運轉計畫擬訂裝置100即可藉由將各裝置所執行之程式預先安裝於電腦裝置700而實現，亦可藉由將程式記憶於CD-ROM等之記憶媒體，或經由網路發佈，且適當安裝於電腦裝置700而實現。 又，在圖30中，電腦裝置具備1個各構成要素，但相同之構成要素可具備複數個。又，在圖30中係顯示1台電腦裝置，但軟體可安裝於複數台電腦裝置。可藉由該複數台電腦裝置分別執行軟體之不同之一部分處理，而產生處理結果。亦即，運轉計畫擬訂裝置100可作為系統而構成。 處理器701係包含電腦之控制裝置及運算裝置之電子電路。處理器701基於自電腦裝置700之內部構成之各裝置等輸入之資料或程式進行運算處理，且將運算結果及控制信號輸出至各裝置等。具體而言，處理器701執行電腦裝置700之OS(作業系統)或應用程式等，而控制構成電腦裝置700之各裝置。 處理器701並無特別限定，只要可進行上述之處理即可。處理器701例如亦可為：通用目的處理器、中央處理裝置(CPU)、微處理器、數位信號處理器(DSP)、控制器、微控制器、運轉狀態機器等。又，處理器701亦可為面向特定用途之積體電路、現場可程式化閘陣列(FPGA)、可程式化邏輯電路(PLD)等。又，處理器701可由複數個處理裝置構成。例如，既可為DSP及微處理器之組合，亦可為與DSP核協同之1個以上之微處理器。 主記憶裝置702係記憶供處理器701執行之命令及各種資料等之記憶裝置，記憶於主記憶裝置702之資訊由處理器701直接讀出。輔助記憶裝置703係主記憶裝置702以外之記憶裝置。又，記憶裝置意味著可儲存電子資訊之任意之電子零件。作為主記憶裝置702主要使用RAM、DRAM、SRAM等之用於暫時之資訊之保存的揮發性記憶體，在本發明之實施形態中，主記憶裝置702並不限定於該等之揮發性記憶體。用作主記憶裝置702及輔助記憶裝置703之記憶裝置既可為揮發性記憶體，亦可為非揮發性記憶體。非揮發性記憶體具有可程式化唯讀記憶體(PROM)、可抹除可程式化唯讀記憶體(EPROM)、可電性抹除PROM(EEPROM)、非揮發性隨機存取記憶體(NVRAM)、快閃記憶體、MRAM等。又，作為輔助記憶裝置703可使用磁性或光學性資料儲存器。作為資料儲存器，可使用硬碟等之磁碟、DVD等之光碟、USB等之快閃記憶體、及磁帶等。 又，若處理器701對於主記憶裝置702或輔助記憶裝置703進行直接或間接地讀出或寫入資訊或該等之二者，則可謂記憶裝置與處理器進行電性通信。又，主記憶裝置702亦可集中於處理器。該情形下亦然，可謂主記憶裝置702與處理器進行電性通信。 網路介面704係用於藉由無線或有線連接於通信網路800之介面。網路介面704只要使用現有之適合於通信規格者即可。可藉由網路介面704朝經由通信網路800通信連接之外部裝置900發送輸出結果等。外部裝置900既可為外部記憶媒體，亦可為顯示裝置，還可為資料庫等之儲存器。 裝置介面705係與記錄輸出結果等之外部記憶媒體連接之USB等之介面。外部記憶媒體可為HDD、CD-R、CD-RW、DVD-RAM、DVD-R、BD-ROM、BD-R、BD-RE、SAN(storage area network，儲存區域網路)、DAT等之任意之記錄媒體。可經由裝置介面705與儲存器等連接。 又，電腦裝置700之一部分或全部、亦即運轉計畫擬訂裝置100之一部分或全部可藉由安裝處理器701等之半導體積體電路等之專用之電子電路(亦即硬體)而構成。專用之硬體可以RAM、ROM等之記憶裝置之組合而構成。 又，在圖30中，係顯示1台電腦裝置，但軟體亦可安裝於複數台電腦裝置。可藉由該複數台電腦裝置分別執行軟體之不同之一部分處理，而算出處理結果。 上述內容說明了本發明之實施形態，但該等實施形態係作為例子而提出者，並非意欲限定發明之範圍。該等新穎之實施形態可利用其他各種形態實施，在不脫離發明之要旨之範圍內可進行各種省略、置換、變更。該等實施形態及其變化，包含於發明之範圍及要旨內，且包含於申請專利範圍所記載之發明及其均等之範圍內。Embodiments of the present invention create an operational plan that takes into account the individual limitations of each of the generators associated with the stop period. The operation plan drawing device which is one aspect of the present invention is based on the characteristics of the generator, Operational restriction data, The plan for the operation of each generator is based on the electricity demand data. And has: Operation status determination unit, It determines the operating state of each generator; Operation state correction unit, Correcting the operating state of each of the generators determined by the operating state determining unit; And output power determination unit, The output power of each of the generators is determined based on at least the operating state of each of the generators corrected by the operating state correction unit. The operation state determining unit is based on the stop period of each of the generators. The operating state of each generator is determined by the restrictions common to the generators. The operation state correction unit is based on the stop period of each generator. The operating state of each generator is corrected for individual limitations of each generator. the following, Embodiments of the present invention will be described with reference to the drawings. Fig. 1 is a block diagram showing an example of a schematic configuration of an operation plan drawing system including the operation plan drawing device of the first embodiment. The operating plan drawing device system shown in Figure 1 comprises: Operation plan drawing device 100, Input/output device 200, Generator characteristic data management device 300, Operation limit data management device 400, And a power demand forecasting device 500. The operation plan drawing device 100 shown in Fig. 1 is provided with: Input unit 101, Memory unit 102, Output unit 103, The operation state determining unit 104, Operation state correction unit 105, And an output power determination unit 106. The operation plan drawing device 100 formulates an operation plan relating to the operating state of the generator and the output power. It is envisaged that there are a plurality of generators present. also, The generator is conceived as a thermal power generator, But it is not limited to thermal power generators. The data required for the development of the operation plan is specified from the input/output device 200. In the information required to develop a plan of operation, contain: Generator characteristics data, Operational restriction data, And electricity demand information. Fig. 2 is a view showing an example of the characteristics of the generator. The generator characteristic data is information indicating the characteristics of the generator. Here, Among the characteristics of the generator, Contains output power and calculated values based on output power. E.g, In the generator characteristics data, it can include: The minimum value of the output power, Maximum value, average value, Calorific value, Operating cost per calorie, The calorific value per unit time. The generator characteristic data is used for the production of the constraints and objective functions of the optimization problem described later. The operational limit data is information indicating the limitations associated with the operation of the generator. E.g, The time taken after the generator is temporarily stopped until it can be started is one of the operational limitations. The operation limit data is used as a restriction condition for the optimization problem described later. The electricity demand data is a representation of the power requirements for the generator or generator group. The electricity demand data is also used as a limiting condition for the optimization issues described below. also, The generator group is a group of one or more generators. The operational restrictions imposed on the generator set are applied to all of the generators belonging to the generator group. also, One generator can belong to a plurality of generator groups. also, Imagine the information needed to develop a plan of operation, Obtained from an external device or system designated by the input/output device 200. In Figure 1, As an example of the source of the required information, The display has: Generator characteristic data management device 300, Operation limit data management device 400, And a power demand forecasting device 500. It is assumed that the generator characteristic data is obtained from the generator characteristic data management device 300, The operation restriction data is obtained from the operation restriction data management device 400, The power demand data is obtained from the power demand forecasting device 500. Explain the proposed operational plan. The operating state of each generator and the output power of each generator are displayed in the programmed operation plan. Figure 3 is a diagram showing an example of a programmed operation plan. The graph of the broken line represents the output power. The vertical axis represents the value of the output power. The horizontal axis represents time. The generator is based on the programmed operation plan, Stop, Startup, etc., However, it takes time to accept the stop instruction until the generator is actually stopped. identically, It takes time to accept the start-up instruction until the output of the generator actually reaches a certain value. The generator that will accept the indication of the stop is actually disconnected from the power system as a disassociation. also, Connecting the generator to the power system will be accepted as a parallel indication. In Figure 3, The blackened triangle (▲) that meets the horizontal axis indicates the timing of the disassembly. The white triangle (△) indicates the timing of the juxtaposition. The time from self-solving to juxtaposition is called the stop period of the generator. also, Here, The operating state of the generator during the stop period is described as a stopped state. The operation state other than the stop state is described as the startup state. that is, Here, The operating state of the generator is divided into two types: the starting state and the stopping state. In Figure 3, The operating state of the generator during this period is displayed below the horizontal axis. Shows a stop state between unwrapping and juxtaposition, It is displayed as a startup state in other parts. The output power continues to drop after the generator receives the instruction to stop. The de-column is performed when the output power becomes zero. The graph of the portion where the output power is lowered is referred to as a stop curve. also, The output power of the generator after the gradual increase gradually Stable after reaching a certain output value. The graph in which the output power rises is referred to as a start curve. The starting curve has a stepped shape as shown in FIG. So, In order to develop a plan of operation, It is necessary to solve the operating state of the generator and the output power of the generator. therefore, The operation plan drawing device 100 is based on generator characteristic data, Operational restriction data, The power demand data is subjected to an operation state determination process and an output power determination process. The operation state determination processing determines the timing at which the operation state of the generator is changed. The operation state determination process is a process of determining the value of the output power of the generator. The components of the operation plan drawing device 100 will be described. First, the flow of processing of the components of the operation plan drawing device 100 will be described. Fig. 4 is a view showing an example of a schematic flow chart of the overall processing of the operation plan drawing device of the first embodiment. The input unit 101 obtains the material required for the processing (S101). The obtained data is memorized in the memory unit 102 (S102). The operation state determination unit 104 is based on the data stored in the storage unit 102. The operation state determination process is executed (S103). The operation state correction unit 105 corrects the operation state calculated by the operation state determination process (S104). then, The output power determination unit 106 is based on the operating state of the generator. The output power determination process is executed (S105). With this, An operational plan is developed that includes the operating state of the generator and the output power of the generator. then, The output unit 103 outputs an operation plan (S106). also, The illustrated flow chart is an example. Just get the results you need, Can do other processing, It is also possible to change the order of processing and the like. E.g, After the processing of each component, The output unit 103 sequentially outputs the processing result. also, It is feasible that The processing results of the respective processes are sequentially memorized in the memory unit 102. Each component refers to the memory unit 102 to obtain a processing result. The flow chart described thereafter is also the same. The input unit 101 obtains information necessary for the processing of the operation planning device 100 from an external device. also, It is also possible to receive information other than the information required for the instructions of each component of the operation planning device 100. The input unit 101 transmits the input information to a specific recipient. The recipient is not particularly limited. Here, It is passed to the memory unit 102. The memory unit 102 memorizes the information received by the input unit 101. also, The processing results of the components of the operation plan drawing device 100 can also be memorized. For example, the operational plan developed. The memory unit 102 can be either a memory or a storage device. Can also be a plurality of memories or storage devices. It can also be a combination of memory or storage. The memory destination can be distinguished based on the information being memorized. The data being memorized can be managed as a database (DB). E.g, As shown in Figure 1, The memory unit 102 can include: Generator characteristic data management DB, It manages the characteristics of the generator; Operation limit data DB, Its management operation limit information; And power demand data management DB, It manages electricity demand data. The output unit 103 outputs the prepared operation plan. The output destination is assumed to be an input/output device 200, However, the output destination is not limited. also, The output unit 103 can output data other than the operation plan. E.g, Can output information for the operation plan, The results of each processing until the processing plan is developed. also, The information output can be obtained from each component. It can also be obtained from the memory unit 102. The output mode of the output unit 103 is not particularly limited. The output unit 103 displays the processing result as an image on the screen. It can also be saved as a file. The operation state determining unit 104 determines the timing of the disengagement and the parallelization of the generator by performing the operation state determination process. in particular, By solving constraints based on constraints, And the optimization of the objective function determines the timing of the disassociation and juxtaposition. The operating state is determined based on the calculated disarrangement of the generator and the timing of the parallel arrangement. The processing performed by the operation state determining unit 104 will be described together with the flowchart. FIG. 5 is a view showing a flowchart of an operation state determination process of the operation state determination unit. The operation state determining unit 104 obtains the required information from the storage unit 102, that is: Generator characteristics data, Operational restriction data, And power demand information (S201). Secondly, The operation state determination unit 104 performs an objective function setting process (S202). The objective function setting processing formulates the objective function of the optimization problem. The objective function setting process can be performed by a well-known method. The objective function can be set arbitrarily. E.g, It is possible to minimize the operating cost of a single generator or a generator group containing a plurality of generators. It is also possible to make the running cost close to a specific target value as an objective function. The specific target value can be arbitrarily set. also, The operating cost is only the cost of the operation of the generator. Can include items needed for the operation of the generator, people, Or the cost of the service. The items required for the operation of the generator can be used as a power source for power generation such as fuel. It can also be cooling water other than the power source. Catalyst, etc. The power source is also not particularly limited. E.g, Can be fossil fuel, Wood fuel, Nuclear fuel. It can also be stored in levees and other water. It may also be a chemical substance such as methylcyclohexane used in hydrogen power generation. also, It can also include the cost of running the generator. E.g, It may also contain limestone for removing chemical substances contained in exhaust gas generated by power generation, The cost of liquid ammonia. Secondly, The operation state determination unit 104 performs restriction condition setting processing (S203). The constraint setting process formulates the constraints of the optimization problem. The restriction setting process can be performed by a well-known method. The restrictions imposed can be the constraints of the generator stand-alone, Or the constraints of the generator group. The limiting condition of the generator group can be the total power generation of the generator group, The overall limit of the generator group for the fuel usage of the generator group as a whole. or, It can be the limit condition of each generator of the generator group. At last, The operation state determining unit 104 solves the objective function set based on the target function setting process (S202), And an optimization problem of the operation limitation set in the restriction condition setting process (S203). As a solution method, 2 plans can be used, Well-known optimization problem solving methods such as linear schemes. also, In order to solve the problem, Use a dedicated program, You can also use the well-known solution. With this, Determine the timing of the disengagement and juxtaposition of the generator. then, The operation state determination unit 104 is based on the calculated timing of the disassociation and the parallelization. Develop information on the time and the operational status of the generator. E.g, Information on the operational status may be displayed for each of the plurality of intervals determined during the planning period. So, The operation state determining unit 104 determines the operating state of the generator. but, When there are too many operational restrictions, This leads to an increase in processing load and calculation time. therefore, The operation state determining unit 104 regards the stop period of one of the operation restrictions as a uniform and determines the optimal timing. E.g, It is assumed that the limit of the length of the generator during the stop period is only one, and the operating state of the generator is determined. or, The restrictions relating to the lengths of the respective stop periods of the plurality of generators are all made common. And determining the operating state of each of the plurality of generators. With this, Although reducing the load and calculation time of the solution processing of the optimization problem, But the granularity of the operational plan has become rough. therefore, Go on like this, Due to the deviation from the actual situation, Therefore, the economy is damaged. The operation state correction unit 105 corrects the operation state of each of the generators determined by the operation state determination unit 104. E.g, The operation state correcting unit 105 corrects the length of the stop period of the generator based on the limit relating to the length of the stop period of the generator. With this, The operating state of the generator determined by the operating state determining unit can be corrected. therefore, Consider the various limitations of each generator associated with the stop period, It can reduce the deviation from the actual situation. FIG. 6 is a view for explaining a correction process of the operation state correcting unit. In Fig. 6(A) to Fig. 6(C), A schematic diagram showing an operation plan at the time when the operation state correcting unit 105 performs each process. The operation state correcting unit 105 creates a stop curve as shown in FIG. 6(A) at the timing of the disengagement. The production of the stop curve is based on the information contained in the generator characteristic data for the production of the stop curve. Secondly, The operation state correcting unit 105 confirms the timing of the parallel connection of the generators. The stop period is calculated as shown in Fig. 6(B). then, The operation state correction unit 105 is based on individual operation restrictions related to the stop period determined for each of the generators. The stop period is corrected as shown in Fig. 6(C). Fig. 7 is a view showing an example of the operation limitation during the stop period determined for the generator. In Figure 7, There are two examples of stop periods. In the table shown on the left, The stop period is represented by a discrete value. that is, Indicates that the stop period is any of the values of the table shown on the left side, The timing of any of these values during the stop period may be juxtaposed. In the table shown on the right, The allowable range of the stop period is displayed. that is, It is displayed that if the stop period is within the allowable range, it may be juxtaposed. also, In Figure 7, it is divided into two tables. However, the operational limit during the stop period may also be a combination of both the discrete value and the allowable range. E.g, It is assumed that the stop period based on the timing of the disassociation and the parallel determination determined by the operation state determining unit 104 is 500. In this case, In the table on the left side of Figure 7, Number 480 of number 3 is less than 500 and the closest discrete value. therefore, When using the table on the left side of Figure 7, The operation state correcting unit 105 selects the operation limit of No. 3, In order to set the stop period to 400, the timing of the parallel is corrected. also, The correction is performed in a manner that is shorter than the corrected stop period before the correction. This is due to the lengthening period, Then it is unable to meet the power demand and there is a shortage of power. In the table on the right side of Figure 7, The stop period of 500 is within the range of number 2. therefore, When using the table on the right side of Figure 7, The operation state correcting unit 105 does not correct the timing of the parallel arrangement. So, The operation state correcting unit 105 corrects the length of the stop period of the generator so as to match any of the plurality of allowable values. or, The length of the stop period of the generator is corrected in such a manner as to be included in any of a plurality of allowable ranges. also, In the above, Select one value from a plurality of values or ranges. However, different values or ranges can be determined for each generator. The numbering of the table of Figure 7 can be an individual limitation for each generator. E.g, The value and range of the number 1 of the table of Figure 7 can be assigned to the generator 1, Assign the value and range of number 2 to generator 2. So, The operation state correcting unit 105 can be used for each of a plurality of generators. The respective operating states of the plurality of generators are corrected using individual limits associated with the length of the stop period. on the other hand, When the operation state determining unit 104 determines the respective operating states of the plurality of power generators, The restrictions relating to the lengths of the respective stop periods of the plurality of generators can be set to be common to all. E.g, When there are 3 generators, The operation state determining unit 104 assumes that the first number of the table on the left side of FIG. 7 is the limit of the generator 1, No. 2 is the limitation of generator 2, No. 3 is the limitation of generator 3. In this case, The operation state determining unit 104 may use the limit of No. 1 together with the three generators. With this, The operating state determined by the operating state determining unit 104 deviates from the actual situation, However, since the correction by the operation state correcting unit 105 is performed, The result is that the operating plan does not deviate from the actual situation. on the other hand, Since the restriction is set to be common, the complexity of the optimization problem is reduced. Therefore, the time taken for the processing of the operation state determining unit 104 becomes short. Secondly, The operation state correcting unit 105 is at the timing of the parallel operation. The starting curve of Fig. 6(D) was produced based on the information contained in the generator characteristic data for the production of the starting curve. At last, After confirming the necessity of correcting the timing of the disassociation, the operation state correcting unit 105 Fix the timing of the disassociation. If the stop period is corrected as shown in Fig. 6(C), Then the timing of the juxtaposition is advanced. But at the time of being juxtaposed in advance, There may be cases where the parallel operation cannot be advanced due to operational limitations such as inspection of the generator. In such a situation, As shown in Figure 6(E), Correspond by pushing the timing of the unwinding. So, Formulate a plan of operation. The resulting stop curve and start curve are determined based on the operating limits of the generator and the stop period. E.g, Short during the stop period, There is heat residue in the turbine of the generator, The output power value can be increased in a short time. on the other hand, If the stop period is long, It is not possible to set the desired output power value once. It includes a period during which the output power does not rise. therefore, As shown in Figure 6(D), The starting curve is stepped. The operation state correcting unit 105 creates a stop curve and a start curve. Use the data used to create the stop curve and the start curve. The data is recorded as a curve data. The curve data is the value and time of the output power for each mode of the generator and generator. The mode of the generator is an indicator for distinguishing the type of the shape of the start curve or the stop curve of the generator, which is changed corresponding to the stop period. Fig. 8 is a view showing an example of a curve data. The table at the top of Figure 8 shows the relationship between the mode of the generator and the generator and the characteristics of the curve. The unit number indicates the number used to distinguish each generator. The mode number indicates the relative number attached to each generator in order to distinguish the modes. The order is indicated by its unit number and its mode number. The order of changes in the characteristics of the curve. E.g, In the table at the top of Figure 8, If the mode number of the generator of unit number 1 is 1, Then as shown in order 1, The time to output 0 is 0. Secondly, As shown in order 2, The time to output 0 lasts 170. And, As shown in order 3, The time of output 500 continues for 200. on the other hand, It can be seen that if the mode of the generator is 2, The start curve is different from when the generator mode is 1. So, The start or stop curve can be switched depending on the mode. The table at the bottom of Figure 8 shows a table of criteria for the mode of each generator. The column indicates the unit number, The line indicates the mode number. The values in the table indicate the upper limit of the stop period of the corresponding column of the generator in the corresponding row mode. E.g, When the generator of the unit number 1 is given a stop period, The upper limit of the mode in which the nth (n is a positive integer)-1 is exceeded when the cessation period is given, And when it is below the upper limit of the nth mode, The generator is judged to be in the nth mode based on the table of the table at the lower part of FIG. Since the start curve is affected by the stop period, Therefore, by using such a curve data, The operation state correcting unit 105 not only corrects the stop period, And it can be based on the stop period after the correction of the operating state, Make a start curve and a stop curve. Fig. 9 is a view showing a flowchart of a correction process of the operation state correcting unit. It is envisaged that a series of processing of this process will be carried out for each interval determined during the planning period. E.g, After the processing of the nth interval, The processing of the n+1th interval is performed. also, Information on the time created by the operating state determining unit 104 and the operating state of the generator is used. The operation state correcting unit 105 is based on the information of the time and the operating state of the generator. It is confirmed whether or not the operating state of the generator in the target section currently being processed has changed since the last target section (S301). If it is the same operating state (No in S302), Then move to the next object interval, The processing of S301 is performed again. If it is in different operating states (S302 is), The difference is handled by the operation state of the generator in the target section. When the generator is in the stop state (S303 is in the stopped state), Due to the timing of the disassociation under the currently processed object interval, Therefore, the operation state correcting unit 105 creates a stop curve as shown in FIG. 6(A) at the timing of the disengagement (S304). After the production of the stop curve, When the target section to be processed is the last target section (Yes in S311), Since the processing has been completed for all planning periods, Therefore, the process ends. When it is not the last target interval (No in S311), Transfer to the next object interval, The processing of S301 is performed again. When the generator is in the startup processing operation state (the startup state of S303), Due to the timing of the juxtaposition in the currently processed object interval, Therefore, the operation state correcting unit 105 calculates a stop period based on the timing of the parallelism and the timing of the decommissioning confirmed in S304 (S305). then, When the calculated stop period satisfies the operation limit of the stop period as shown in FIG. 7 (Yes in S306), The operation state correcting unit 105 creates a start curve at the timing of the parallel connection (S310). then, It is confirmed whether it is the last target section in the operation plan (S311), Or transfer to the next object interval (No in S311), Or the process ends (Yes in S311). If the calculated stop period does not satisfy the operation limit of the stop period (No in S306), The operation state correcting unit 105 determines whether or not the timing can be juxtaposed in advance. If the timing of the parallel is advanced (S307 is), The stop period is corrected by timing in advance (S308). If the timing of the parallel is not possible (No in S307), The stop period is corrected by the timing of the push-back unpacking (S309). also, By pushing back the timing of the disassociation, as shown in Fig. 6(E), Move the finished stop curve. So, A new stop period that satisfies the operation limit during the stop period is calculated. then, The operation state correcting unit 105, at the timing of the new parallelism generated by the correction, A start curve is created (S310). also, As mentioned above, Determining the mode of the generator based on a new stop period resulting from the correction, The operation state correcting unit 105 creates a start curve based on the mode of the generator at a new parallel position. then, It is confirmed whether it is the last target section in the operation plan (S311), Or transfer to the next object interval (No in S311), Or the process ends (Yes in S311). The above process is performed for all generators. When there is no generator to execute the object, The processing of the operation state correcting unit 105 is completed. The output power determination unit 106 performs an output power determination process of determining the value of the output power per unit period of each of the generators. in particular, The value of the output power of each generator is calculated by solving an optimization problem based on the operation limit and the objective function. The unit period means that the planning period of the operation plan is divided into the minimum period of the plurality of periods. The unit period is called a mesh. In the restriction condition of the optimization problem calculated by the output power determination unit 106, The restriction condition related to the operating state of the generator corrected by the operation state correcting unit 105 is included. With this, The correction of the operation state correcting unit 105 is reflected in the prepared operation plan. The process of determining the value of the output power of each of the generators by the output power determination unit 106 will be described together with the flowchart. Fig. 10 is a view showing a flowchart of an output power determination process of the output power determination unit. The output power determination unit 106 obtains necessary information from the storage unit 102, That is, the characteristics of the generator, Operational restriction data, And power demand data (S401). In the operational limit information obtained, The operating state of the generator corrected by the operating state correcting unit 105 is included. that is, contain: The timing of the unwinding, The timing of juxtaposition, Start curve, Stop the curve. Secondly, The output power determination unit 106 performs an objective function setting process (S402). then, The output power determination unit 106 performs restriction condition setting processing (S403). The objective function setting processing and the restriction condition setting processing may be the same as the processing of the operation state determining unit 104. At last, The output power determination unit 106 solves the objective function set based on the target function setting process (S402), And an optimization problem of the operation limitation set in the restriction condition setting process (S403) (S404). This processing may be the same as the processing of the operation state determining unit 104. With this, The operation plan is prepared by calculating the value of the output power of each generator during the plan period. The operational plan so formulated is different from the operational plan that considers only the minimum stop period. E.g, Even if the value and time of the output power of the starting curve are determined by each generator in response to the stop period, It is still possible to develop operational plans that take into account such operations. also, The limit during the stop period is even 4 hours. 8 hours, 14 hours of discrete value, Or a continuous time of 4 hours to 16 hours can still correspond. With this, The operation plan can be made to match the actual situation. As mentioned above, According to this embodiment, Ability to develop operational plans that consider multiple stop periods. also, When the optimization problem performed by the operation state determining unit 104 is performed based on a single stop period, The solution time is shorter than considering the optimization problem in a plurality of stop periods. With this, It can shorten the time taken for the development of the operational plan corresponding to the actual situation. also, The above embodiment is an example. One of the components of the above embodiment may be located outside the device. E.g, The above embodiment has an operation state determining unit 104. However, the operation state determining unit 104 may be located in an external device. In this case, The input unit 101 can obtain the timing of unpacking and juxtaposition from an external device. And it is transmitted to the operation state correction unit 105. also, The planning device can also be constructed from a plurality of devices that can communicate data by communication or electrical signals. E.g, The first device having the operation state determining unit 104 and the operating state correcting unit 105 can be classified into And a second device having the output power determination unit 106. (Second Embodiment) In the second embodiment, Before the optimization problem of the operation state determining unit 104 is solved, Adjust the information used for the operation plan. E.g, With this adjustment, data with time changes will be developed. As shown in the generator characteristics data shown in Figure 2, The value of the characteristics of the generator is often set to be constant for each generator. however, In fact, There may be a case where the value of the characteristics of the generator changes depending on the environment around the generator and the like. therefore, The value that is set to a certain characteristic during the planning period of the operation plan is adjusted for each unit period during the planning period. A more realistic operational plan can be developed. also, In this embodiment, For example, new operational limit data can be created based on existing operational limit data. There may be even if not solved by optimization problems, The operation state of the generator or the output of electric power is determined based on the operation restriction. therefore, Based on existing operational restrictions, Calculate the operating state of the generator or output power, New operational constraints related to the calculated operational status and so on. With this, There should be fewer combinations to explore on optimization issues. The time for preparing the operation plan can be shortened compared to the first embodiment. Fig. 11 is a block diagram showing an example of a schematic configuration of an operation plan drawing system including the operation plan drawing device of the second embodiment. The system of the operation plan drawing device 100 shown in FIG. 11 further includes an environmental data management device 600. The operation plan preparing device 100 according to the second embodiment shown in FIG. 11 further includes a data adjusting unit 107 in the first embodiment. In the second embodiment, The operation plan drawing device has a situation in which information corresponding to the time is changed. The data that changes according to time is recorded as time variation data. As shown in Figure 11, Here, It is assumed that the operation plan drawing device 100 obtains environmental data from the environmental data management device 600 as time variation data. Environmental data such as temperature, Air pressure, Weather-related information related to the environment surrounding the generator, The values of these values vary according to time. therefore, Environmental information is equivalent to time-varying data. The obtained environmental data is memorized in the memory unit 102 in the same manner as other materials. also, When the operation limit or the like changes due to maintenance, etc., The changed operational limits are also equivalent to time-varying data. E.g, In the generator group, In normal times, Even when the number of startup states has been determined, However, there may be cases where the number of units changes due to maintenance. Such operational limitations due to time are also equivalent to time-varying data. also, When obtaining an operational limit equivalent to time-varying data, No environmental information is required. The components of the operation plan drawing device 100 of the second embodiment will be described. Descriptions will be omitted from the same points as the present embodiment. The data adjustment unit 107 before the operation state determination unit 104 executes the operation state determination process, The adjustment processing of the data used for each processing is carried out. Fig. 12 is a view showing an example of a schematic flow chart of the overall processing of the operation plan drawing device of the second embodiment. Compared with the schematic flow chart of the overall processing of the operation plan drawing device of the first embodiment, The data adjustment processing of the material adjustment unit 107 is added before the processing of S103 (S501). Fig. 13 is a view showing a flow chart of the data adjustment processing of the data adjustment unit. also, In this process, For the normal confirmation of the input data (S602), Performing data processing for the generator unit period (S603), Generator group unit period data production processing (S604), Generator output fixed processing (S605), The case of the four processes of the operation limit interpolation process (S606) will be described. however, Generator unit period data production processing (S603), Generator group unit period data production processing (S604), Generator output fixed processing (S605), The operation limit interpolation processing (S606) is independent of each other. therefore, It is not necessary to perform all four such treatments. And at least one of the processes can be performed. The data adjustment unit 107 can perform a function corresponding to the processing performed in the four processes. also, The order in which the four processes are performed is not particularly limited. These four processes can be performed in parallel. also, Each process can be performed independently of the constituent elements. E.g, The data adjustment unit 107 can include: Generator unit during the data production department, The data during the production of the generator unit; Generator unit unit data production department, It produces data during the period of the generator unit unit; Predetermination department, It performs fixed processing of generator output; And the interpolating department, It performs operation limit interpolation processing. or, The data adjustment unit 107 can be replaced with a data generation unit period data generation unit, Generator unit unit data production department, Predetermination department, Or the interpolating department. The data adjustment unit 107 obtains the information required for the adjustment (S601). The information required for the adjustment differs according to the four processes described above. The materials required for each of the above four processes are described in each process. Secondly, The data adjustment unit 107 confirms the compliance of the obtained data. When it is judged as non-compliance due to an abnormal value or the like in the obtained data, The process ends. also, The error message can be output to the input/output device 200 via the output unit 103. Secondly, The data adjustment unit 107 grasps the characteristics of the variable generator, Information on the characteristics of the generator per unit period is produced (S603). The data indicating the characteristics of the generator per unit period is recorded as the data of the generator unit period. In the data used to calculate the data for the unit period of the generator, Includes generator characteristics data and time variation data. In Figures 14 and 15, Displays information used to calculate data for the unit period of the generator. Fig. 14 is a view showing an example of generator characteristic data for calculating data of a unit period of a generator. The data shown in Figure 14 is a representation of the relationship between generator output and power generation efficiency. The data indicating the relationship between the generator output and the power generation efficiency in Fig. 14 does not indicate the relationship with time. however, It is known that the power generation efficiency varies depending on the outside of the atmospheric temperature or the like which changes with time. therefore, When an operational plan is prepared using the generator characteristic data of Fig. 14 which does not indicate the relationship with time, There are operational plans that deviate from the actual situation. Fig. 15 is a view showing an example of time variation data for calculating data of a unit period of a generator. The time variation data shown in Fig. 15 is meteorological data indicating the atmospheric temperature per unit period. As mentioned above, It is known that power generation efficiency changes due to external factors. therefore, The value of the power generation efficiency of the generator output is adjusted in consideration of the influence of the atmospheric temperature shown in FIG. E.g, The value of the power generation efficiency is adjusted using a least squares method or the like based on a plurality of measurement results. then, The characteristics of the generator per unit period are calculated based on the value of the adjusted power generation efficiency. Fig. 16 is a view showing an example of the data of the unit period of the generator. In Figure 16, Indicates the characteristics of the generator during each unit period of 30 minutes. As an example of a characteristic that changes in a mesh unit, Displaying a plurality of coefficients included in the second approximation of the characteristic relating to the fuel of the generator, Maximum output, Minimum output, etc. If the output efficiency changes, Then the output power changes, And correspondingly, the fuel consumption amount and the like also vary. also, The unit price of power generation is included in the generator characteristics data as shown in Fig. 2. So, For the second approximation, The characteristics of the generator with the largest output are also the same. It is also possible to add the influence of the atmospheric temperature which varies with time. So, By processing the data during the unit period of the generator, A data on the unit period of the generator indicating the change in the value of each net is produced. So, The data adjustment unit 107 can adjust the values of the generator characteristic data or the operation restriction data having a constant value during the planning period of the operation plan for each of the plurality of intervals in the planning period of the operation plan. then, Develop an operational plan by using time-varying data, It is possible to develop an accurate operational plan that is realistic. Secondly, The data adjustment unit 107 grasps the characteristics of the fluctuating generator group. Information on the characteristics of the generator per unit period is produced (S604). The data indicating the characteristics of the generator group per unit period is recorded as the data of the unit period of the generator group. In the data used to calculate the data during the unit period of the generator group, Includes generator group data and time variation data. The generator group data is the generator data of the generator group. Does not mean the characteristics of the generator stand-alone, It represents the characteristics of the generator group. also, A plurality of features can be determined for one generator group. Fig. 17 is a view showing an example of data for calculating data of a unit period of a generator group. An example of the generator system group data in the upper part of Fig. 17 is shown. Display the number of each generator group, And the number of the generator belonging to the generator group. The lower part of Figure 17 is another example of the generator group data. Indicates the number of units of each generator group that are normally used. Fig. 18 is an example of time variation data. The number of normal operation units shown in the table at the lower part of FIG. 17 is changed from the time when the change is started to the time when the change is completed, and the change value shown in FIG. 18 is changed. that is, The information in Figure 18 is equivalent to the operational limitations of time-varying data. 19 to 21 are diagrams showing the first to third examples of the data of the unit period of the generator group, respectively. Figure 19 shows the data of the unit period of the generator group by using the data for the number of units of the generator group shown in the table at the bottom of Figure 17, It is produced by combining the time-limited operation limit data shown in FIG. The generator group unit period data in Fig. 19 indicates the number of units of operation per grid. therefore, By using the generator group unit period data of Figure 19 as an operational limit, The operation plan of each mesh can be made more in line with the actual situation. also, Figure 20 shows the output range of the generator group per mesh. Figure 21 shows the range of fuel consumption for each grid of generators. The information in Figure 20 and Figure 21 is also an example of the information relating to the generator group for each network. The same is true for such information, By using the usual data based on meteorological data such as temperature, The time variation data of the fuel inventory data such as the moment of fuel transportation is corrected. It can be set as the data for each mesh. So, Through the processing of generator group data, Based on the generator group data and the time variation data, the data of the generator group unit period including the data of each mesh is generated. then, By developing an operational plan based on data from the generator unit period, It can achieve an accurate operation plan that meets the actual situation. Secondly, The data adjustment unit 107 performs a generator output fixing process (S605). The generator output fixed processing is based on at least one of the generator characteristic data and the operation limitation data. The process of determining the state or output power during a specific period of the generator. In the first embodiment, The operation state determining unit 104 calculates the timing of the disengagement and the parallelization for all the generators. however, The solution of the combined optimization problem performed by the operational state determining unit 104 is very complicated. therefore, If the object of the optimization problem is set to all generators, The time for the development of the operational plan has grown. therefore, In this embodiment, Before the processing by the operation state determining unit 104. First determine the timing of the disengagement and juxtaposition of some of the generators. The timing at which the generator is determined to be disengaged and juxtaposed is given to the operation state determining unit 104 as an operation restriction. With this, On the combined optimization problem of the operation state determining unit 104, The calculation range is limited, The speed of the development of the operation plan can be realized. In the generator output fixed process, E.g, Specifying the operating state for a particular generator by a plurality of operating limits, When outputting power, etc. A plurality of operational limits are synthesized based on priorities and the like. Fig. 22 is a view for explaining a generator output fixing process. The first operation limit and the second operation limit for the operation limitation of the output electric power for one of the generators are set to the two operation limits. The first graph from top to bottom indicates the first operational limit, The second graph from top to bottom indicates the second operational limit. also, The vertical axis of the graph represents the output power, The horizontal axis represents time. also, The first graphic from top to bottom is set to have a higher priority than the second graphic. also, The output power is not set to 0 during the period in which the graph coincides with the horizontal axis. It means that the operating restrictions are not specified during this period. therefore, During the period of mesh 2 and mesh 3 shown in FIG. 22, Both the first operational limit and the second operational limit are applied. With such two operational limits, The data adjustment unit 107 synthesizes two operation restrictions. The third figure from top to bottom indicates the operational limit after synthesis. In the interval of the net 1, Since the first operational limit is not specified, Therefore, the pattern of the operational limit after the synthesis coincides with the pattern of the second operational limit. In the range of Mesh 2 and Mesh 3, Since it is stipulated that there is a first operational limit with a high priority, Therefore, the pattern of the operational limit after the synthesis coincides with the pattern of the first operational limit. The data adjustment unit 107 thus replaces the two operation limits with one new operation limit. With this, The number of operation restrictions of the operation of the operation state determining unit 104 can be reduced. Fig. 23 is a view showing an example of the operation limitation after the synthesis. Same as the unit period of the generator group unit, Make operational limits for each mesh. also, E.g, When there is an operational limit related to the period of operation of a generator, There may be this operational limit, although it is not directly specified output power, However, the output power is determined to be unique based on the operational limit. therefore, In the absence of optimization issues, When determining the output power of a particular generator for a specific period based on the operating limits of a particular generator, The data adjustment unit 107 can determine a specific generator output power, And it can be used as an operational limit. Fig. 24 is a view showing an example of an operation limitation relating to the output power of the generator calculated based on the operation restriction related to the period of the operation state. Assume there is a time since 3: 00 to 4: During the 30th period, The generator 8 is set to an operation limit in a stopped state. In this assumption, The data adjustment unit 107 determines the value of the output power for each mesh in the same manner as the stop curve and the start curve generated by the operation state correcting unit 105. With this, As shown in Figure 24, Create operational limits related to the output power of each mesh. So, A new operational limit associated with the output power is created based on the operational limit by the generator output fixed process. With this, The combination to be discussed in the combination optimization problem of the operation state determining unit 104 is reduced. The time for preparing the operation plan can be shortened compared to the first embodiment. Secondly, The data adjustment unit 107 performs an operation restriction interpolation process (S606). The operation limit interpolation process is based on a plurality of operational limits associated with the stop period of a particular generator, The processing of the operation limitation related to the new stop period is calculated. Fig. 25 is a view for explaining the operation restriction interpolation processing. Assume that for a certain generator, There are a number of operational limits associated with the stop period. The data adjustment unit 107 is based on the plurality of operational restrictions, As shown in Fig. 25(A), Master the stop period A, Stop period B, And stop period C. Secondly, The data adjustment unit 107 is based on the stop period and the generator characteristic data. Interpolate the operating state between a plurality of stop periods. in particular, Consider the time required for the generator to start, Stop the time required, It is determined whether the generator can be started between the stop periods. E.g, As shown in Figure 25 (B), It is judged that it is possible to start between the stop period A and the stop period B, However, it is determined that the stop period B and the stop period C cannot be started. then, The data adjustment unit 107 sets a period in which it is determined that the startup is impossible, and is a stop period. The plurality of stop periods are combined into one stop period. In Figure 25(C), Since the stop period B and the stop period C become the stop period after the interpolation, It is determined that one stop period D of the stop period B and the stop period C is included. With this, The operation limit associated with the stop period B and the operation limit associated with the stop period C are summarized as the operation limit associated with the stop period D. So, The data adjustment unit 107 is based on the time required for the start of the generator and the time required for the generator to stop. A period between the first stop period of the generator and the second stop period of the generator is taken as a new stop period. With this, The stop period becomes longer, The combination to be discussed in the combination optimization problem of the operation state determining unit 104 is reduced. However, the time for preparing the operation plan can be shortened compared with the first embodiment. also, The data adjustment unit 107 can be based on an operational limit that can be derived during the stop period. The stop period is calculated and the operation limit interpolation processing is performed. The above is a flowchart of the data adjustment processing of the data adjustment unit 107. So, The result calculated in each process of the data adjustment unit 107 is transmitted to the operation state determination unit 104. The operation state determining unit 14 further based on the processing results of the processes, Determine the operating state of the generator. As mentioned above, According to this embodiment, The data used by the operation state determining unit 104 is adjusted by the data adjustment unit 107. With this, For information that has not previously been considered to be due to changes in time, Perform adjustments based on the timeline, It is possible to develop an accurate operational plan that is consistent with the actual application. also, There should be fewer combinations to explore on optimization issues. The time for preparing the operation plan can be shortened compared to the first embodiment. (Third embodiment) In the third embodiment, Before the optimization problem is solved by the operation state determining unit 104, The timing of the disassociation and juxtaposition is calculated based on a part of the operation limit. The timing of the disassociation and the parallelization calculated based on the partial operation limit is described as an initial solution. This initial solution is used to alleviate the combinatorial optimization problem of the operational state determining unit 104. Fig. 26 is a block diagram showing an example of a schematic configuration of an operation plan drawing device according to a third embodiment. The third embodiment is other than the second embodiment. There is also an initial solution generation unit 108. also, The initial solution generation unit 108 may be added to the first embodiment. Descriptions will be omitted from the same points as the present embodiment. The initial solution generation unit 108 calculates an initial solution of the operation plan based on one of a plurality of operational limits. Because the solution to the optimization problem is very complicated, Therefore, when the operation state determining unit 104 processes all of them, Increase processing load and time to develop. also, The processing capability required by the operation state determining unit 104 becomes high, However, it affects the production cost of the operation plan drawing device 100 and the like. therefore, In the present embodiment, the initial solution generation unit 108 also calculates the timing of the disassociation and the parallelization. but, Since the initial solution generation unit 108 does not consider the operation limitation all, Therefore, the processing capability of the initial solution generation unit 108 can be lower than that of the operation state determining unit 104. also, The solving method may be different from the operating state determining unit 104. So, Since the solution to the optimization problem is divided into a plurality of processes, The processing load of the operation state determining unit 104 can be suppressed, Therefore, the processing capability of the operating state determining unit 104 can also be suppressed. also, The greater the number of operational limits used to calculate the initial solution, The accuracy of the solution calculated by the operation state determining unit 104 can be ensured. Further, the time during which the operation state determining unit 104 obtains the solution can be further shortened. The calculation of the initial solution is not the best combination. Instead, the solution is calculated for each timeline along the forward or reverse direction for the time axis. It can also be calculated based on both the solution calculated in the forward direction and the solution calculated in the reverse direction. also, The solution can be calculated as a whole during the planning period. The solution may be limited to a specific period within the plan period. also, When using the data of each mesh of the data in the unit period of the generator group unit according to the second embodiment, The initial solution generation unit 108 calculates an initial solution for each mesh. E.g, The amount of electricity given to each mesh can be used as an operational limit. Calculated in such a way that the operating cost is the smallest. also, Accumulating the output at the unit price of the power generation determined, When the operating limit cannot be met, The output of a part of the generator can be changed in such a way as to meet the operational limit. The method of accumulating the output until the operation limit is satisfied. also, The initial solution generation unit 108 can use the formulated mathematical programming method in the same manner as the operation state determination unit 104. In this case, Similarly to the operation state determining unit 104, Due to the target function setting process, Restriction setting processing, The solution to the optimal problem can be, Therefore, the description is omitted. Fig. 27 is a view showing an example of a schematic flow chart of the overall processing of the operation plan drawing device of the third embodiment. The initial solution generation unit 108 generates an initial solution (S701) after the data adjustment unit 107 executes the material adjustment processing (S501). Compared with the schematic flow chart of the overall processing of the operation plan drawing device 100 of the second embodiment, The process of generating the initial solution of the initial solution generation unit 108 is added after S501 (S701). also, Similar to the first embodiment, The operation state determination unit 104 executes an operation state determination process (S702). but, Since the operation state determination process of the present embodiment includes the process of using the initial solution, Therefore, some parts are different from the first embodiment. The subsequent processing is the same as the current embodiment. The operation state determination process of the operation state determination unit 104 of the third embodiment will be described. The operation state determination unit 104 of the third embodiment further performs an operation state mode creation process and an operation state mode reduction process. The operation state mode creation processing and the operation state mode reduction processing and the processing flow will be described together. FIG. 28 is a flowchart showing an operation state determination process of the operation state determination unit in the third embodiment. The operation state determining unit 104 is the same as the embodiment as it is. After obtaining the necessary information (S201), The operation state mode creation processing is performed for each of the generators (S802). The operational state mode creation process is an operational state mode in which a combination of candidates of a specific range indicating the operational state of the generator is formulated. The operational state mode is formulated by selecting the timing of the disassociation and juxtaposition from a plurality of specific timing candidates. Fig. 29 is a view for explaining an operational state mode. Candidates for the timing of unwinding and juxtaposition are determined for each mesh. FIG. 29 shows the operational state mode 1 to the operational state mode 3. So, Within a certain range, a candidate for a combined operational state, That is, the start state and the stop state, And a plurality of operating state modes are produced. also, Similar to the first embodiment, The operating limit during the stop period is determined for each generator. also, The operating limit of the startup state determines the minimum startup time. And the time to set the startup state is above the minimum startup time. The minimum start-up time is expressed as the sum of the time required to start the curve and the time required to start the curve immediately after the start curve as the start point of the stop curve. that is, This means the time from the juxtaposition of the generator to the fastest disassociation without the need to stabilize the generator. also, The starting curve is the same as the current implementation. The time required may be different depending on the stop period. or, Nothing about the stop period, The minimum start-up time can be determined by a specific start and stop curve. also, The starting and stopping curves for the calculation of the minimum starting time can be different from the usual starting and stopping curves called the test run curve. also, The production range of the operation state can be as a whole during the planning period. It can also be part of the planning period. A portion of the planning period may be a period created by zoning the planning period based on a particular condition. E.g, One day can be used as the production range of the operating state. Secondly, The operation state determining unit 104 selects whether to use the initial solution or not to use the initial solution (S802). When using the initial solution (Yes in S802), It is determined whether or not the operation state mode reduction processing is performed (S803). When the operation state mode reduction processing is performed (Yes in S803), Based on the initial solution reduction operation state mode created by the initial solution generation unit 108 (S804). The reduction of the operating state mode is based on the initial solution of the timing of the parallel and unraveling. The processing of the mesh that defines the change in the operating state of the generator. If the initial solution is assumed to have a certain precision, Then consider the timing of a positive solution near the timing of the initial solution. therefore, If the conditions in the operating mode are not met, It can reduce the operating mode. E.g, As shown in the bottom of Figure 29, By the initial solution, the timing of the solution is range A, And the timing of juxtaposition is the scope B. In this case, Since the operating state mode 1 is not disjointed in the range A, Therefore, it was cut off. also, Since the operating state mode 3 is not juxtaposed in the range B, Therefore, it was cut off. The operational state mode 2 shown in FIG. 29 is de-listed within the range A, And juxtaposed in range B, Therefore, it is not removed and retained. The operation state determining unit 104 is based on the initial solution as such. The operational state pattern conforming to the condition is obtained from the plurality of calculated operational state patterns. also, In FIG. 29, the range of the dissociation shown by the range A and the range B and the width of the range of the juxtaposition can be arbitrarily determined. The width of the range can also be calculated based on the generator characteristic data or the operation limit data. also, The timing of the disengagement and juxtaposition of the previously developed operational plans can also be used as an initial solution. that is, Based on the timing and juxtaposition of the previously developed operational plan, The operation state mode reduction processing is performed. So, By reducing the operating state mode, Further, the time taken for the operation state determination processing of the operation state determining unit 104 can be shortened. When the initial solution is not used (No in S802), When the operation state mode reduction processing is not performed (No in S803), After the operation state mode reduction processing (S804) is performed, The operation state determining unit 104 performs an objective function setting process (S202). The aforementioned operational state pattern consistent with the conditions obtained is also included in the objective function. Since the subsequent processing is the same as the current implementation, Therefore omitted. So, The operation state determining unit 104 further determines the operating state of the generator based on the operating state mode that matches the condition. As mentioned above, According to this embodiment, The initial solution generation unit 108 obtains an initial solution that satisfies at least a part of the operation limit. then, The operation state determination unit 104 reduces the operation state mode based on the initial solution. With this, The range of the optimization problem solved by the operation state determining unit 104 can be limited. therefore, The time taken for the processing of the operation state determining unit 104 becomes short. The solution can be calculated in the time of use. Each process of all embodiments of the present invention can be implemented by software (program). therefore, Each of the embodiments described above can be used, for example, by using a general-purpose computer device as a basic hardware. A central processing unit (CPU: mounted on a computer device) Central Processing Unit, The central processing unit) and the like execute the program. Fig. 30 is a block diagram showing an example of a hardware configuration of an operation plan drawing device according to an embodiment of the present invention. The operation plan drawing device 100 can be implemented by the computer device 700. The computer device 700 is provided with: The processor 701, Main memory device 702, Auxiliary memory device 703, Network interface 704, And device interface 705, And these are connected via bus bar 706. also, The operation plan drawing device 100 can include a general-purpose input device and an output device as the input/output device 200. The operation plan drawing device 100 of the present embodiment can be realized by pre-installing a program executed by each device in the computer device 700. It is also possible to memorize the memory in a memory medium such as a CD-ROM. Or posted via the web, This is achieved by suitably installing on the computer device 700. also, In Figure 30, The computer device has one component, However, the same constituent elements may have plural numbers. also, In Figure 30, a computer device is shown. However, the software can be installed in a plurality of computer devices. A plurality of different parts of the software can be separately processed by the plurality of computer devices, And the processing result is produced. that is, The operation plan drawing device 100 can be configured as a system. The processor 701 is an electronic circuit including a control device of a computer and an arithmetic device. The processor 701 performs arithmetic processing based on data or a program input from each device or the like configured inside the computer device 700. The calculation result and the control signal are output to each device or the like. in particular, The processor 701 executes an OS (operation system) or an application program of the computer device 700, The devices constituting the computer device 700 are controlled. The processor 701 is not particularly limited. As long as the above processing can be performed. The processor 701 can also be, for example: General purpose processor, Central processing unit (CPU), microprocessor, Digital signal processor (DSP), Controller, Microcontroller, Operating state machine, etc. also, The processor 701 can also be an integrated circuit for a specific purpose, Field programmable gate array (FPGA), Programmable logic circuit (PLD), etc. also, The processor 701 can be constructed from a plurality of processing devices. E.g, It can be a combination of DSP and microprocessor. It can also be one or more microprocessors that cooperate with the DSP core. The main memory device 702 is a memory device that memorizes commands executed by the processor 701 and various materials. The information stored in the main memory device 702 is directly read by the processor 701. The auxiliary memory device 703 is a memory device other than the main memory device 702. also, A memory device means any electronic component that can store electronic information. As the main memory device 702, mainly uses RAM, DRAM, Volatile memory such as SRAM for the preservation of temporary information, In an embodiment of the invention, The main memory device 702 is not limited to the volatile memory. The memory device used as the main memory device 702 and the auxiliary memory device 703 can be a volatile memory. It can also be a non-volatile memory. Non-volatile memory with Programmable Read Only Memory (PROM), Erasable programmable read only memory (EPROM), Electrically erasable PROM (EEPROM), Non-volatile random access memory (NVRAM), Flash memory, MRAM and so on. also, As the auxiliary memory device 703, a magnetic or optical data storage can be used. As a data storage, A disk such as a hard disk can be used, CDs such as DVDs, Flash memory such as USB, And tapes, etc. also, If the processor 701 directly or indirectly reads or writes information or the like to the main memory device 702 or the auxiliary memory device 703, It can be said that the memory device is in electrical communication with the processor. also, The main memory device 702 can also be centralized on the processor. The same is true in this case. The main memory device 702 can be said to be in electrical communication with the processor. The network interface 704 is used to interface to the communication network 800 by wireless or wired. The network interface 704 can be used as long as it is suitable for communication specifications. The output result or the like can be transmitted through the network interface 704 to the external device 900 communicatively connected via the communication network 800. The external device 900 can be an external memory medium. Can also be a display device, It can also be a storage for a database or the like. The device interface 705 is an interface of a USB or the like connected to an external memory medium that records an output result or the like. External memory media can be HDD, CD-R, CD-RW, DVD-RAM, DVD-R, BD-ROM, BD-R, BD-RE, SAN (storage area network, Storage area network), Any recording medium such as DAT. It can be connected to a storage or the like via the device interface 705. also, Part or all of the computer device 700, In other words, part or all of the operation plan drawing device 100 can be configured by mounting a dedicated electronic circuit (that is, a hard body) such as a semiconductor integrated circuit of the processor 701 or the like. Dedicated hardware can be RAM, A combination of a memory device such as a ROM is used. also, In Figure 30, Display a computer device, However, the software can also be installed in a plurality of computer devices. A plurality of different parts of the software can be separately processed by the plurality of computer devices, And calculate the processing result. The foregoing describes the embodiments of the present invention. However, these embodiments are presented as examples. It is not intended to limit the scope of the invention. These novel embodiments can be implemented in a variety of other forms. Various omissions may be made without departing from the gist of the invention. Replacement, change. These implementations and their changes, Included in the scope and gist of the invention, It is included in the scope of the invention described in the scope of the patent application and its equivalent.