Enhanced Multi-Objective Differential Evolutionary Algorithm Based Optimal Power Flow Calculation for Integrated Electricity and Gas Systems

被引：0

作者：

Liu M. ^{[1
]}

Wang Z. ^{[1
]}

Xing Y. ^{[1
]}

机构：

[1] College of Information Science and Engineering, Northeastern University, Shenyang

来源：

Diangong Jishu Xuebao/Transactions of China Electrotechnical Society | 2021年 / 36卷 / 11期

关键词：

Differential evolution; Enhanceddominant relationship of non-dominant solution; Integrated energy system; Multi-objective optimization; Optimal power flow;

D O I：

10.19595/j.cnki.1000-6753.tces.200405

中图分类号：

学科分类号：

摘要：

With the development of integrated energy system, the connection between power grid and natural gas network is getting closer. In order to ensure the safety and economic operation of the integrated electricity and gas systems, it is necessary to carry out the joint planning for the system. Therefore, firstly, a multi-objective optimal scheduling model of the electricity-gas energy interconnection system is proposed according to the system's large-scale, multi-dimensional, non-convex, and nonlinear characteristics. Secondly, in order to deal with the problem of poor population convergence in the solving algorithm of high-dimensional objective function, anenhanced multi-objective differential evolution algorithm is proposed to strengthen the dominant relation of non-dominant solutions. Finally, IEEE 30-node power system and Belgium 20-node natural gas system are used to show the effectiveness of the proposed algorithm. The simulations show that the present algorithm can produce a better distribution of Pareto optimal front of the objective function under consideration. Meanwhile, a set of better optimization solutionscan be obtained from the high-dimensional target solving, which can meet the operating requirements of the system under different working conditions. © 2021, Electrical Technology Press Co. Ltd. All right reserved.

引用

页码：2220 / 2232

页数：12

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