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  <doc>
    <id>9045</id>
    <completedYear/>
    <publishedYear>2015</publishedYear>
    <thesisYearAccepted/>
    <language>jpn</language>
    <pageFirst>267</pageFirst>
    <pageLast>272</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="jpn">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（多目的最適化におけるK-ベスト解の探索）</title>
    <title language="eng">Optimization of Energy Supply Systems in Consideration of Hierarchical Relationship Between Design and Operation (Search for K-Best Solutions in Multiobjective Optimization)</title>
    <abstract language="eng">A mixed-integer linear programming method utilizing the hierarchical relationship between design and operation variables proposed to solve the optimal design problem of energy supply systems efficiently is extended to search K-best solutions in multiobjective optimization: At the upper level, the optimal values of design variables are searched by the branch and bound method with operation variables relaxed to continuous ones; At the lower level, the values of operation variables are optimized independently at the respective periods set for variations in energy demands by the branch and bound method with the values of design variables given tentatively during the search at the upper level. A weighting method is employed for multiobjective optimization, and a weighted sum of the annual total cost and primary energy consumption is adopted as the objective function to be minimized. A practical case study on the optimal design of a cogeneration system is conducted. The validity and effectiveness of the proposed method are clarified, and the trade-off relationship between the annual total cost and primary energy consumption is confirmed.</abstract>
    <parentTitle language="jpn">エネルギー・資源学会第31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</parentTitle>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="SubmissionStatus">in press</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Shusuke Taniguchi</author>
    <submitter>Yuji Shinano</submitter>
    <author>Ryohei Yokoyama</author>
    <author>Yuji Shinano</author>
    <author>Masashi Ohkura</author>
    <author>Tetsuya Wakui</author>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>9041</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>jpn</language>
    <pageFirst>169</pageFirst>
    <pageLast>174</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="jpn">エネルギー供給システムの    設計と運用の階層的関係を考慮した最適化 (運用を考慮した期間クラスタリングによるモデル縮約)</title>
    <title language="eng">Optimization of Energy Supply Systems in Consideration of Hierarchical Relationship Between Design and Operation (Model Reduction by Clustering Periods in Consideration of Operation)</title>
    <abstract language="eng">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 multi-period 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 has also been proposed to search design solution candidates efficiently in the relaxed optimal design problem at the upper level. In this paper, by utilizing features of the hierarchical MILP method, a method of clustering periods is proposed based on the optimal operational strategies of energy supply systems obtained by solving the relaxed optimal design problem. As a case study, the method is applied to the optimal design of a gas turbine cogeneration system, and it is clarified that the method is effective to enhance the computation efficiency in comparison with a conventional method of clustering periods regularly.</abstract>
    <parentTitle language="jpn">エネルギー・資源学会第35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</parentTitle>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="SubmissionStatus">in press</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Kotaro Takeuchi</author>
    <submitter>Yuji Shinano</submitter>
    <author>Ryohei Yokoyama</author>
    <author>Yuji Shinano</author>
    <author>Tetsuya Wakui</author>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>9042</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>jpn</language>
    <pageFirst>163</pageFirst>
    <pageLast>168</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="jpn">混合整数線形モデルによる エネルギー供給システムのロバスト最適設計    (階層的最適化手法の適用)</title>
    <title language="eng">Robust Optimal Design of Energy Supply Systems Based on a Mixed-Integer Linear Model (Application of a Hierarchical Optimization Method)</title>
    <abstract language="eng">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. However, this method takes a long computation time, and thus it can be applied only to small-scale problems. In this paper, mixed-integer linear programming method in consideration of the hierarchical relationship between design and operation variables is applied to parts of the robust optimal design method which take long computation times to solve problems efficiently. In a case study, this revised method is applied to the robust optimal design of a cogeneration system with a simple configuration, and the validity and effectiveness of the method are ascertained.</abstract>
    <parentTitle language="jpn">エネルギー・資源学会第35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</parentTitle>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="SubmissionStatus">in press</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Hiroki Kamada</author>
    <submitter>Yuji Shinano</submitter>
    <author>Ryohei Yokoyama</author>
    <author>Yuji Shinano</author>
    <author>Tetsuya Wakui</author>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>9047</id>
    <completedYear/>
    <publishedYear>2014</publishedYear>
    <thesisYearAccepted/>
    <language>jpn</language>
    <pageFirst>183</pageFirst>
    <pageLast>188</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="jpn">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）</title>
    <title language="eng">Optimization of Energy Supply Systems in Consideration of Hierarchical Relationship Between Design and Operation (Proposal of Optimization Method)</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="jpn">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</parentTitle>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="SubmissionStatus">in press</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Ryohei Yokoyama</author>
    <submitter>Yuji Shinano</submitter>
    <author>Yuji Shinano</author>
    <author>Syusuke Taniguchi</author>
    <author>Masashi Ohkura</author>
    <author>Tetsuya Wakui</author>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>9046</id>
    <completedYear/>
    <publishedYear>2014</publishedYear>
    <thesisYearAccepted/>
    <language>jpn</language>
    <pageFirst>1</pageFirst>
    <pageLast>4</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="jpn">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）</title>
    <title language="eng">Optimization ofEnergy Supply Systems in Consideration of Hierarchical Relationship Between Design and Operation (Search for K-Best Solutions)</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="jpn">日本機械学会第11回最適化シンポジウム2014講演論文集</parentTitle>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="SubmissionStatus">in press</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Ryohei Yokoyama</author>
    <submitter>Yuji Shinano</submitter>
    <author>Yuji Shinano</author>
    <author>Syusuke Taniguchi</author>
    <author>Masashi Ohkura</author>
    <author>Tetsuya Wakui</author>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>9043</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>jpn</language>
    <pageFirst>259</pageFirst>
    <pageLast>260</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="jpn">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)</title>
    <title language="eng">Optimal Design and Operation of Energy Supply Systems by Hierarchical Optimization (Model Reduction by Clustering Periods and Its Effect)</title>
    <abstract language="eng">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.&#13;
Through acase study on the optimaldesign of a cogeneration system, ti is clarified how the model reduction si effective ot enhance the computation efficiency.</abstract>
    <parentTitle language="jpn">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</parentTitle>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="SubmissionStatus">in press</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Yuki Wakayama</author>
    <submitter>Yuji Shinano</submitter>
    <author>Ryohei Yokoyama</author>
    <author>Yuji Shinano</author>
    <author>Tetsuya Wakui</author>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>9040</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>jpn</language>
    <pageFirst>109</pageFirst>
    <pageLast>114</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="jpn">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)</title>
    <title language="eng">Optimization of Energy Supply Systems in Consideration of Hierarchical Relationship Between Design and Operation (Comparison of Time-Period Clustering Methods for Model Reduction)</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="jpn">第38回エネルギー・資源学会研究発表会講演論文集</parentTitle>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="SubmissionStatus">in press</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Ryohei Yokoyama</author>
    <submitter>Yuji Shinano</submitter>
    <author>Yuji Shinano</author>
    <author>Kotaro Takeuchi</author>
    <author>Tetsuya Wakui</author>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>9037</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>jpn</language>
    <pageFirst>724</pageFirst>
    <pageLast>729</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="jpn">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)</title>
    <title language="eng">Optimization of Energy Supply Systems in Consideration of Hierarchical Relationship Between Design and Operation (Application of Model Reduction to Multiobjective Optimal Design)</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="jpn">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</parentTitle>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="SubmissionStatus">in press</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Kotaro Takeuchi</author>
    <submitter>Yuji Shinano</submitter>
    <author>Ryohei Yokoyama</author>
    <author>Yuji Shinano</author>
    <author>Tetsuya Wakui</author>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>9035</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>jpn</language>
    <pageFirst>398</pageFirst>
    <pageLast>403</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="jpn">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)</title>
    <title language="eng">Optimization of Energy Supply Systems in Consideration of Hierarchical Relationship Between Design and Operation (Application to Systems With Energy Storage Units)</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="jpn">第40回エネルギー・資源学会研究発表会講演論文集</parentTitle>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="SubmissionStatus">in press</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Ryohei Yokoyama</author>
    <submitter>Yuji Shinano</submitter>
    <author>Yuji Shinano</author>
    <author>Tetsuya Wakui</author>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>9034</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>jpn</language>
    <pageFirst>468</pageFirst>
    <pageLast>473</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="jpn">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)</title>
    <title language="eng">Derivation and Evaluation of Approximate Optimal Design Solutions of Energy Supply Systems by Time Aggregation (Evaluation of Design Solutions Using Hierarchical Optimization)</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="jpn">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</parentTitle>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="SubmissionStatus">in press</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Ryohei Yokoyama</author>
    <submitter>Yuji Shinano</submitter>
    <author>Yuji Shinano</author>
    <author>Tetsuya Wakui</author>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>9033</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>jpn</language>
    <pageFirst>144</pageFirst>
    <pageLast>148</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="jpn">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)</title>
    <title language="eng">Derivation and Evaluation of Approximate Optimal Design Solutions of Energy Supply Systems by Time Aggregation (Approximate Optimal Design Using Hierarchical Optimization)</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="jpn">第41回エネルギー・資源学会研究発表会講演論文集</parentTitle>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="SubmissionStatus">in press</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Ryohei Yokoyama</author>
    <submitter>Yuji Shinano</submitter>
    <author>Yuji Shinano</author>
    <author>Tetsuya Wakui</author>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>9039</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>jpn</language>
    <pageFirst>730</pageFirst>
    <pageLast>735</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="jpn">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</title>
    <title language="eng">Robust Optimal Design of Energy Supply Systems With Aid of a Hierarchical Optimization Method</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="jpn">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</parentTitle>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="SubmissionStatus">in press</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Hiroki Kamada</author>
    <submitter>Yuji Shinano</submitter>
    <author>Ryohei Yokoyama</author>
    <author>Yuji Shinano</author>
    <author>Tetsuya Wakui</author>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>9036</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>jpn</language>
    <pageFirst>1</pageFirst>
    <pageLast>4</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="jpn">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)</title>
    <title language="eng">Optimization of Energy Supply Systems in Consideration of Hierachical Relationship Between Design and Operation (Application of Time-Period Clustering Based on k-Medoids Method)</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="jpn">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</parentTitle>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="SubmissionStatus">in press</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Kotaro Takeuchi</author>
    <submitter>Yuji Shinano</submitter>
    <author>Ryohei Yokoyama</author>
    <author>Yuji Shinano</author>
    <author>Tetsuya Wakui</author>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>9038</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>jpn</language>
    <pageFirst>1</pageFirst>
    <pageLast>4</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="jpn">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</title>
    <title language="eng">Evaluating Robustness of Energy Supply Systems Using a Hierarchical Optimization Method</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="jpn">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</parentTitle>
    <enrichment key="PeerReviewed">no</enrichment>
    <enrichment key="SubmissionStatus">in press</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Hiroki Kamada</author>
    <submitter>Yuji Shinano</submitter>
    <author>Ryohei Yokoyama</author>
    <author>Yuji Shinano</author>
    <author>Tetsuya Wakui</author>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>9023</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1112</pageFirst>
    <pageLast>1117</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Evaluation of Design Alternatives for a Gas Turbine Cogeneration Plant Based on Multiobjective K-Best Solutions</title>
    <abstract language="eng">To realize the best performance in energy supply, it is an important task to determine types, capacities, and numbers of energy conversion equipment appropriately. It is also necessary to take account of seasonal and hourly variations in energy demands and corresponding operational strategies of equipment. The mixed-integer linear programming (MILP) method has been utilized widely to derive the optimal solution for such a design problem. From the design viewpoint, it is important to generate not only the optimal solution but also suboptimal ones which follow the optimal one without omission, what are called K-best solutions. In this paper, an MILP method utilizing the hierarchical relationship between design and operation variables is applied along with some strategies to efficiently drive K-best solutions of a multiobjective optimal design problem of a gas turbine cogeneration system for district energy supply. The annual total cost and primary energy consumption are adopted as the objective functions to be minimized. A case study is conducted, and K-best solutions with an allowable increase in the value of the combined objective function are derived for each value of the weight for the annual total cost. Through the study, it is clarified how the weight affects the computation time, the number of the K-best solutions, and the design specifications and the values of the objective functions for the K-best solutions.</abstract>
    <parentTitle language="eng">International Conference on Power Engineering-2019</parentTitle>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Ryohei Yokoyama</author>
    <submitter>Yuji Shinano</submitter>
    <author>Yuji Shinano</author>
    <author>Tetsuya Wakui</author>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>9022</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1937</pageFirst>
    <pageLast>1948</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Evaluation of robustness in multiple performance criteria for designing energy supply systems based on a mixed-integer linear model</title>
    <abstract language="eng">In designing energy supply systems, it is important to consider the uncertainty in energy demands, evaluate the robustness in some performance criteria, and heighten the robustness. A robust optimal design method has been previously proposed to maximize the robustness in a single performance criterion against the uncertainty in energy demands based on a mixed-integer linear model. In this paper, as a preliminary step toward multiobjective robust optimal design, a method of evaluating robustness in multiple performance criteria against the uncertainty in energy demands is proposed based on a mixed-integer linear model. The problems of evaluating the robustness in the performance criteria are formulated as bilevel mixed-integer linear programming (MILP) ones. They are solved by evaluating lower and upper bounds for the maximum regrets in the performance criteria alternately and repeatedly with the aid of a solution method based on reformulation and decomposition. In addition, for the purpose of applying the proposed method to practical problems, a hierarchical MILP method is used to efficiently solve some MILP problems in the solution process. Through a case study on a cogeneration system, the robustness in the annual total cost and primary energy consumption is evaluated and its trade-off relationship is clarified. As a result, it turns out how the values of these performance criteria are close to the optimal ones in relation to the uncertainty in energy demands. This work will be an important step toward developing a multiobjective robust optimal design method.</abstract>
    <parentTitle language="eng">The 35th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2022)</parentTitle>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="PeerReviewed">yes</enrichment>
    <author>Ryohei Yokoyama</author>
    <submitter>Yuji Shinano</submitter>
    <author>Yuto Hiramatsu</author>
    <author>Yuji Shinano</author>
    <author>Tetsuya Wakui</author>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>9019</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>45</pageFirst>
    <pageLast>57</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>184</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Search for K-best solutions in optimal design of energy supply systems by an extended MILP hierarchical branch and bound method</title>
    <abstract language="eng">For the purpose of making a decision in the optimal design of an energy supply system, it is important to investigate not only the optimal solution but also suboptimal ones which follow the optimal one without any omissions, what are called K-best solutions. In this paper, a mixed-integer linear programming method utilizing the hierarchical relationship between design and operation variables proposed previ- ously is extended to search the K-best solutions very efficiently. In addition, methods for updating the incumbents are incorporated into the extended method for three options for the criterion set newly in deriving the K-best solutions. This extended method is implemented into open and commercial MILP solvers, and is applied to illustrative and practical case studies, respectively, on the optimal design of cogeneration systems. Through the studies, it turns out that the proposed method is much superior in terms of solution optimality and computation efficiency to a conventional method, and that the computation efficiency to derive one of the K-best solutions by the proposed method increases with the number of K-best solutions. In addition, features of the K-best solutions in the value of objective function are clarified.</abstract>
    <parentTitle language="eng">Energy</parentTitle>
    <identifier type="doi">https://doi.org/10.1016/j.energy.2018.02.077</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Ryohei Yokoyama</author>
    <submitter>Yuji Shinano</submitter>
    <author>Yuji Shinano</author>
    <author>Syusuke Taniguchi</author>
    <author>Tetsuya Wakui</author>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>8981</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1937</pageFirst>
    <pageLast>1948</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Evaluation of robustness in multiple performance criteria for designing energy supply systems based on a mixed-integer linear model</title>
    <abstract language="eng">In designing energy supply systems, it is important to consider the uncertainty in energy demands, evaluate the robustness in some performance criteria, and heighten the robustness. A robust optimal design method has been previously proposed to maximize the robustness in a single performance criterion against the uncertainty in energy demands based on a mixed-integer linear model. In this paper, as a preliminary step toward multiobjective robust optimal design, a method of evaluating robustness in multiple performance criteria against the uncertainty in energy demands is proposed based on a mixed-integer linear model. The problems of evaluating the robustness in the performance criteria are formulated as bilevel mixed-integer linear programming (MILP) ones. They are solved by evaluating lower and upper bounds for the maximum regrets in the performance criteria alternately and repeatedly with the aid of a solution method based on reformulation and decomposition. In addition, for the purpose of applying the proposed method to practical problems, a hierarchical MILP method is used to efficiently solve some MILP problems in the solution process. Through a case study on a cogeneration system, the robustness in the annual total cost and primary energy consumption is evaluated and its trade-off relationship is clarified.</abstract>
    <parentTitle language="eng">Proceedings of the 35th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2022)</parentTitle>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="SubmissionStatus">in press</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Ryohei Yokoyama</author>
    <submitter>Yuji Shinano</submitter>
    <author>Yuto Hiramatsu</author>
    <author>Yuji Shinano</author>
    <author>Tetsuya Wakui</author>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>9024</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>527</pageFirst>
    <pageLast>539</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Operation-based time-period clustering for optimal design of energy supply systems by a hierarchical MILP method</title>
    <abstract language="eng">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, a method of clustering periods has been proposed based on the optimal operational strategies of the systems to avoid a large decrease in the lower bound for the optimal value of the objective function by model reduction. This method has been realized only by solving the relaxed optimal design problem at the upper level in advance. The method can decrease the number of operation variables and constraints at the upper level, and thus can 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 proposed clustering method is effective to enhance the computation efficiency in comparison with the conventional one which clusters periods regularly in time series.</abstract>
    <parentTitle language="eng">THE 32ND INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS(ECOS 2019)</parentTitle>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Ryohei Yokoyama</author>
    <submitter>Yuji Shinano</submitter>
    <author>Yuji Shinano</author>
    <author>Kotaro Takeuchi</author>
    <author>Tetsuya Wakui</author>
    <collection role="persons" number="shinano">Shinano, Yuji</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>9013</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>169</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2023-09-17</completedDate>
    <publishedDate>2023-09-17</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Effect of inertia force on the interface stability of a tangential-velocity discontinuity in porous media</title>
    <abstract language="eng">The present study investigates the stability of a tangential-velocity discontinuity in porous media during the withdrawing and injecting processes of natural gases from and into an underground gas storage. The focus is placed on analyzing the impact of inertia forces on the interface stability using the Forchheimer equations. Other publications have relied primarily on Darcy's law to describe flow stability in porous media. However, Darcy's law only adequately describes flows in which viscous forces dominate over inertia forces. As the flow rate increases, the significance of inertia forces becomes more pronounced, and Darcy's law becomes insufficient for considering such flows. Our findings indicate that even a slight consideration of the inertia effect leads to permanent destabilization of the discontinuity interface, regardless of the fluid viscosity or the Mach number. In contrast, when the inertia effect is neglected, the interface is stabilized across the entire Mach number range if the fluid viscosity is strong enough.</abstract>
    <parentTitle language="eng">International Journal of Multiphase Flow</parentTitle>
    <identifier type="doi">10.1016/j.ijmultiphaseflow.2023.104612</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="SourceTitle">International Journal of Multiphase Flow</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Thi Thai Le</author>
    <submitter>Thi Thai Le</submitter>
    <author>Thorsten Koch</author>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="Mathematical Algorithmic Intelligence">Mathematical Algorithmic Intelligence</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="persons" number="le">Le, Thi Thai</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
</export-example>
