Two-stage superstructure model for optimization of distributed energy systems (DES) part I: Model development and verification

被引:7
作者
Liu, Liuchen [1 ,2 ]
Cui, Guomin [1 ]
Chen, Jiaxing [1 ]
Huang, Xiaohuang [1 ]
Li, Di [1 ]
机构
[1] Univ Shanghai Sci & Technol, Sch Energy & Power Engn, Shanghai 200093, Peoples R China
[2] Tech Univ Munich, Chair Energy Syst, Boltzmannstr 15, D-85748 Garching, Germany
基金
中国国家自然科学基金;
关键词
Distributed energy system (DES); Renewable energy; MINLP; Superstructure model; Random walk algorithm with compulsive evolution (RWCE); RANDOM-WALK ALGORITHM; COMBINED HEAT; MULTIOBJECTIVE OPTIMIZATION; COMPULSIVE EVOLUTION; NETWORK; SOLAR; SIMULATION; STORAGE; STRATEGY; LIBRARY;
D O I
10.1016/j.energy.2022.123227
中图分类号
O414.1 [热力学];
学科分类号
摘要
The optimization of distributed energy systems (DES) is challenging because of the diversity of the types of energies involved and the complexity of the structure. Mathematically, the optimization of DES is a mixed-integer non-linear programming problem (MINLP). The optimal tradeoff between precision and computational efficiency, to find the global optimal solution, is a core issue that needs to be solved. This present work proposes a two-stage superstructure model which is solved by the random walk algorithm with compulsive evolution (RWCE), to better approximate the global optimal solution of the MINLP. The paper is divided into two parts; the first focuses on the modeling methodology and model solving strategy. Moreover, to confirm the applicability and effectiveness of the recommended method, DESs for three case studies, i.e., business park, residential building, and hotel, were optimized from system planning point of view. On comparison with literatures, it was found that the proposed method had positive effects on further improving the economy of the system at different scales and configurations. The resulting decrease in the total annual cost of the three systems was 12%, 36%, and 2%, respectively. Further research on system operation optimization will be published as the second part of this paper. (C) 2022 Elsevier Ltd. All rights reserved.
引用
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页数:14
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