Model reduction by time aggregation for optimal design of energy supply systems by an MILP hierarchical branch and bound method

Ryohei Yokoyama, Yuji Shinano, Yuki Wakayama and Tetsuya Wakui

Energy, 2019, vol. 181, issue C, 782-792

Abstract: Mixed-integer linear programming (MILP) methods have been applied widely to optimal design of energy 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 proposed 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 accordance 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.

Keywords: Energy supply; Optimal design; Mixed-integer linear programming; Hierarchical optimization; Model reduction; Time aggregation (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:181:y:2019:i:c:p:782-792

DOI: 10.1016/j.energy.2019.04.066

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