@article{YokoyamaShinanoTaniguchietal.2014, author = {Yokoyama, Ryohei and Shinano, Yuji and Taniguchi, Syusuke and Ohkura, Masashi and Wakui, Tetsuya}, title = {エネルギー供給システムの設計および運用の階層的関係を考慮した最適化(手法の提案)}, journal = {第33回エネルギー・資源学会研究発表会講演論文要旨集・講演論文集}, pages = {183 -- 188}, year = {2014}, abstract = {A mixed-integer linear programming (MILP) method utilizing the hierarchical relationship between design and op- eration variables is proposed to solve the optimal design problem of energy supply systems efficiently: At the upper level, the optimal values of design variables are searched by the branch and bound method; At the lower level, the values of operation variables are optimized by the branch and bound method under the values of design variables given tentatively during the search at the upper level; Lower bounds for the optimal value of the objective function are evaluated, and are utilized for the bounding operations at both the levels. This method is implemented into open and commercial MILP solvers. Illustrative and practical case studies on the optimal design of cogeneration systems are conducted, and the validity and effectiveness of the proposed method are clarified.}, language = {ja} } @article{YokoyamaShinanoTaniguchietal.2014, author = {Yokoyama, Ryohei and Shinano, Yuji and Taniguchi, Syusuke and Ohkura, Masashi and Wakui, Tetsuya}, title = {エネルギー供給システムの設計および運用階層的関係を考慮した最適化(K-ベスト解の探索)}, journal = {日本機械学会第11回最適化シンポジウム2014講演論文集}, pages = {1 -- 4}, year = {2014}, abstract = {A mixed-integer linear programming methodutilizing the hierarchical relationship between design and operation variables proposed ot solve the optimal design problem of energy supply systems efficiently is extended ot search K-best solutions: At the upper level, the optimal values ofdesign variables are searched with operation variables relaxed to continuous ones; At the lower level, the values of operation variables are optimized with the values of design variables given tentatively; The obtained solution is used to renew K-best incumbent solutions, and the upper bound for the value of the objective function for K-best solutions is replaced correspondingly. A practical case study is conducted, and the validity and effectiveness of the proposed method are clarified.}, language = {ja} } @article{WakayamaYokoyamaShinanoetal.2018, author = {Wakayama, Yuki and Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {階層的最適化によるエネルギ ー供給システムの最適設計・運用 (期間のクラスタリングに よるモデル縮約とその効果)}, journal = {日本機械学会関西支部第93期定時総会講演会講演論文集}, pages = {259 -- 260}, year = {2018}, abstract = {Ahierarchical mixed-integer linear programmingmethod has been proposed to solve optimal design problems of energy supply systems efficiently. In this paper, a method of reducing model by clustering periods is proposed to search design solution candidates efficiently in the relaxed optimal design problem at the upper level. This method is realized only by clustering periods and averaging energy demands for clustered periods, while it guarantees to derive the optimal solution. Through acase study on the optimaldesign of a cogeneration system, ti is clarified how the model reduction si effective ot enhance the computation efficiency.}, language = {ja} } @article{YokoyamaShinanoTakeuchietal.2019, author = {Yokoyama, Ryohei and Shinano, Yuji and Takeuchi, Kotaro and Wakui, Tetsuya}, title = {エネルギー供給システムの設計および運用の 階層的関係を考慮した最適化 (モデル縮約のための期間クラスタリング手法の比較)}, journal = {第38回エネルギー・資源学会研究発表会講演論文集}, pages = {109 -- 114}, year = {2019}, abstract = {Mixed-integer linear programming (MILP) methods have been applied widely to optimal design of energy supply systems. A hierarchical MILP method has been proposed to solve such optimal design problems efficiently. In addition, some strategies have been proposed to enhance the computation efficiency furthermore. As one of the strategies, a method of reducing model by time aggregation has been proposed to search design candidates efficiently in the relaxed optimal design problem at the upper level. In this paper, three clustering methods are applied to time aggregation and compared with one another in terms of the computation efficiency. Especially, the k-medoids method is applied newly in addition to the time-series and operation-based methods applied previously. A case study is conducted on the optimal design of a gas turbine cogeneration system for district energy supply. Through the study, it turns out the k-medoids method is effective to shorten the computation time as compared with the time-series method, although it is necessary to set the number of clusters artifically in both the methods. It also turns out that the operation-based method is more effective than the k-medoids method in terms of the computation efficiency even with the number of clusters set automatically.}, language = {ja} } @article{TakeuchiYokoyamaShinanoetal.2020, author = {Takeuchi, Kotaro and Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {エネルギー供給システムの 設計および運用の階層的関係を考慮した最適化 (多目的最適設計へのモデル縮約の適用)}, journal = {エネルギー・資源学会第36回エネルギーシステム・経済・環境コンファレンス講演論文集}, pages = {724 -- 729}, year = {2020}, abstract = {To attain the highest performance of energy supply systems, it is necessary to determine design specifications optimally in consideration of operational strategies corresponding to seasonal and hourly variations in energy demands. Mixed-integer linear programming (MILP) methods have been applied widely to such optimal design problems. A hierarchical MILP method has been proposed to solve the problems very efficiently. In addition, by utilizing features of the hierarchical MILP method, a method of reducing model by clustering periods based on the optimal operational strategies of equipment has been proposed to search design solution candidates efficiently in the relaxed optimal design problem at the upper level. In this paper, these methods are applied to the multiobjective optimal design of a cogeneration system by considering the annual total cost and primary energy consumption as the objective functions to be minimized. Through a case study, it turns out that the model reduction by the operation-based time-period clustering is effective in terms of the computation efficiency when importance is given to the first objective function, while it is not when importance is given to the second objective function.}, language = {ja} } @article{YokoyamaShinanoWakui2021, author = {Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {エネルギー供給システムの設計および運用の 階層的関係を考慮した最適化 (蓄エネルギー機器を有するシステムへの適用)}, journal = {第40回エネルギー・資源学会研究発表会講演論文集}, pages = {398 -- 403}, year = {2021}, abstract = {Mixed-integer linear programming (MILP) methods have been applied widely to optimal design of energy supply systems. A hierarchical MILP method has been proposed to solve such optimal design problems efficiently. In addition, some strategies have been proposed to enhance the computation efficiency furthermore. As one of the strategies, a method of reducing model by time aggregation has been proposed to search design candidates efficiently in the relaxed optimal design problem at the upper level. In this paper, the hierarchical MILP method with the strategies has been extendedly applied to the optimal design of energy supply systems with storage units. Especially, the method of re- ducing model is extended by aggregating representative days and sampling times differently in consideration of the characteristics of storage units. A case study is conducted on the optimal design of a gas turbine cogeneration system with a thermal storage unit for district energy supply. Through the study, it turns out the hierarchical MILP method is effective to derive the optimal solution as compared with a conventional method. It also turns out that the model reduction with the special time aggregation is effective to shorten the computation time as compared with that without time aggregation in case that the number of candidates for equipment capacities is relatively small.}, language = {ja} } @article{YokoyamaShinanoWakui2022, author = {Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {時間集約によるエネルギー供給システムの 近似最適設計解の導出および評価 (階層的最適化を援用した設計解の評価)}, journal = {エネルギー・資源学会第38回エネルギーシステム・経済・環境コンファレンス講演論文集}, pages = {468 -- 473}, year = {2022}, abstract = {For the purpose of attaining the highest performance of energy supply systems, it is important to design the systems optimally in consideration of their operational strategies for seasonal and hourly variations in energy demands. An ap- proach to solve such an optimal design problem with a large number of periods efficiently is to derive an approximate optimal design solution by aggregating periods with a clustering method. However, such an approach does not provide any information on the accuracy for the optimal value of the objective function. The purpose of this paper is to provide a time aggregation method for deriving aprroximate optimal design solutions and evaluting their values of the objective function. Especially, a method of evaluating design solutions is presented here using both methods of evaluating the robustness under uncertain energy demands and solving optimal design problems by a hierarchical approach. A case study is conducted for a cogeneration system with a practical configuration, and it turns out that the proposed approach enables one to evaluate effective lower bounds for the optimal value of the objective function as compared with those obtained by a conventional approach.}, language = {ja} } @article{YokoyamaShinanoWakui2022, author = {Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {時間集約によるエネルギー供給システムの 近似最適設計解の導出および評価 (階層的最適化を援用した近似最適設計)}, journal = {第41回エネルギー・資源学会研究発表会講演論文集}, pages = {144 -- 148}, year = {2022}, abstract = {For the purpose of attaining the highest performance of energy supply systems, it is important to design the systems optimally in consideration of their operational strategies for seasonal and hourly variations in energy demands. An ap- proach to efficiently solve such an optimal design problem with a large number of periods for variations in energy de- mands is to derive an approximate optimal design solution by aggregating periods with a clustering method. However, such an approach does not provide any information on the accuracy for the optimal value of the objective function. The purpose of this paper is to propose a time aggregation approach for deriving suitable aprroximate optimal design solutions and evaluting their values of the objective function accurately. This time aggregation approach is realized by combining a robust optimal design method under uncertain energy demands and a hierarchical approach for solving large scale optimal design problems. A case study is conducted for a cogeneration system with a practical configuration, and it turns out that the proposed approach enables one to evaluate effective upper and lower bounds for the optimal value of the objective function as compared with those obtained by a conventional approach.}, language = {ja} } @article{YokoyamaShinanoWakayamaetal.2019, author = {Yokoyama, Ryohei and Shinano, Yuji and Wakayama, Yuki and Wakui, Tetsuya}, title = {Model reduction by time aggregation for optimal design of energy supply systems by an MILP hierarchical branch and bound method}, volume = {181}, journal = {Energy}, pages = {782 -- 792}, year = {2019}, abstract = {Mixed-integer linear programming (MILP) methods have been applied widely to optimal design of en- ergy supply systems in consideration of multi-period operation. A hierarchical MILP method has been proposed to solve such optimal design problems efficiently. An original problem has been solved by dividing it into a relaxed optimal design problem at the upper level and optimal operation problems which are independent of one another at the lower level. In addition, some strategies have been pro- posed to enhance the computation efficiency furthermore. In this paper, a method of reducing model by time aggregation is proposed as a novel strategy to search design candidates efficiently in the relaxed optimal design problem at the upper level. In addition, the previous strategies are modified in accor- dance with the novel strategy. This method is realized only by clustering periods and averaging energy demands for clustered periods, while it guarantees to derive the optimal solution. Thus, it may decrease the computation time at the upper level. Through a case study on the optimal design of a gas turbine cogeneration system, it is clarified how the model reduction is effective to enhance the computation efficiency in comparison and combination with the modified previous strategies.}, language = {en} } @article{KamadaYokoyamaShinanoetal.2020, author = {Kamada, Hiroki and Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {階層的最適化手法の援用による エネルギー供給システムのロバスト最適設計}, journal = {エネルギー・資源学会第36回エネルギーシステム・経済・環境コンファレンス講演論文集}, pages = {730 -- 735}, year = {2020}, abstract = {A robust optimal design method of energy supply systems under uncertain energy demands has been proposed using a mixed- integer linear model for constituent equipment. A robust optimal design problem has been formulated as a three-level min-max- min optimization one by expressing uncertain energy demands by intervals, evaluating the robustness in a performance criterion based on the minimax regret criterion, and considering hierarchical relationships among design variables, uncertain energy demands, and operation variables. Since this problem must be solved by a special algorithm and is too difficult to solve even using a commercial solver, a hierarchical optimization approach has been applied to solve the problem but its application is limited only to small scale toy problems. In this paper, some strategies are introduced into the hierarchical optimization approach to enhance the computation efficiency for the purpose of applying the approach to large scale practical problems. In a case study, the proposed approach is applied to the robust optimal design of a cogeneration system with a complex configuration, and the validity and effectiveness of the method are ascertained.}, language = {ja} } @article{TakeuchiYokoyamaShinanoetal.2020, author = {Takeuchi, Kotaro and Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {エネルギー供給システムの設計および運用の階層的関係を考慮した最適化 (k-メドイド法に基づく期間クラスタリングの適用)}, journal = {日本機械学会関西支部第95期定時総会講演会講演論文集}, pages = {1 -- 4}, year = {2020}, abstract = {To attain the highest performance of energy supply systems, it is necessary to determine design specifications optimally in consideration of operational strategies corresponding to seasonal and hourly variations in energy demands. A hierarchical mixed-integer linear programming method has been proposed to solve such an optimal design problem efficiently. In this paper, a method of reducing model by clustering periods with the k-medoids method is applied to the relaxed optimal design problem at the upper level. Through a case study, it is clarified how the proposed method is effective to enhance the computation efficiency in a large scale optimal design problem.}, language = {ja} } @article{KamadaYokoyamaShinanoetal.2020, author = {Kamada, Hiroki and Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {階層的最適化手法を用いた エネルギー供給システムのロバスト性評価}, journal = {日本機械学会関西支部第95期定時総会講演会講演論文集}, pages = {1 -- 4}, year = {2020}, abstract = {A robust optimal design method of energy supply systems under uncertain energy demands has been proposed using a mixed-integer linear model for constituent equipment. However, this method takes a long computation time, and thus it can be applied only to small-scale problems. In this paper, a hierarchical optimization method is applied to two types of optimization problems for evaluating robustness to solve them efficiently. In a case study, the proposed method is applied to a cogeneration system with a complex configuration, and the validity and effectiveness of the method are ascertained.}, language = {ja} }