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  • 2020-2024  (3)
  • 2015-2019  (2)
  • 1985-1989
  • 1915-1919
  • 2022  (3)
  • 2018  (2)
  • 1917
  • Japanese  (5)
Years
  • 2020-2024  (3)
  • 2015-2019  (2)
  • 1985-1989
  • 1915-1919
  • 2020-2023  (1)
Year
Language
  • 1
    Publication Date: 2023-11-03
    Language: Japanese
    Type: proceedings , doc-type:Other
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Publication Date: 2024-04-26
    Description: 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: Japanese
    Type: article , doc-type:article
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    Publication Date: 2024-04-26
    Description: 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: Japanese
    Type: article , doc-type:article
    Library Location Call Number Volume/Issue/Year Availability
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  • 4
    Publication Date: 2023-04-17
    Description: 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: Japanese
    Type: article , doc-type:article
    Library Location Call Number Volume/Issue/Year Availability
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  • 5
    Publication Date: 2023-04-17
    Description: A hierarchical mixed-integer linear programming method to solve optimal design problems of energy supply systems efficiently has been proposed. The original problem is solved by dividing it into a relaxed optimal design problem at the upper level and optimal operation problems which are independent of each other at the lower level. In this paper, a method of reducing model by time aggregation 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. On one hand, the method may decrease the number of design variables and costraints at the upper level, and thus the computation time at the upper level. On the other hand, it may increase the numbers of generated design solution candidates and solved optimal operation problems, and thus the computation time at both the levels. Though a case study on the optimal design of a cogeneration system, it is clarified how the model reduction is effective to enhance the computation efficiency.
    Language: Japanese
    Type: article , doc-type:article
    Library Location Call Number Volume/Issue/Year Availability
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