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Operation-based time-period clustering for optimal design of energy supply systems by a hierarchical MILP method

  • 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.

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Metadaten
Author:Ryohei Yokoyama, Yuji Shinano, Kotaro Takeuchi, Tetsuya Wakui
Document Type:Article
Parent Title (English):THE 32ND INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS(ECOS 2019)
First Page:527
Last Page:539
Year of first publication:2019
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