基于进化算法与经验规则融合的源

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基于进化算法与经验规则融合的源-网-储协同规划高效求解

DOI:

作者单位:

山东大学电气工程学院，山东省济南市 250061

摘要:

源-网-储协同规划需同时兼顾多个主体，且因其高维度与强非线性特征，求解耗时长，限制了实际应用。为此，提出了一种融合进化算法与经验规则的高效求解方法，以综合利用进化算法的强寻优能力与经验规则的收敛加速特性，显著提升求解效率。首先，针对新型电力系统运行方式的多变特性，构建了内嵌时序生产模拟的源-网-储协同规划模型；然后，归纳提炼专家经验，通过模糊推理工具将其规则化；最后，将经验规则融入带精英保留的非支配排序遗传算法，用于优化初始搜索空间和进化方向，从而形成高效求解算法。以中国某省级电网90节点系统的风光电源及储能选址定容为算例，验证了所提方法在求解效率与优化效果上的显著优势。

关键词:

基金项目:

智能电网重大专项（2030）资助项目（2024ZD0801100）。

Efficient Solution to Source-Grid-Storage Coordinated Planning Based on Integration of Evolutionary Algorithms and Empirical Rules

Author:

ZHANG Jifan

ZHANG Jifan

School of Electrical Engineering, Shandong University, Jinan 250061, China
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ZHANG Hengxu

ZHANG Hengxu

School of Electrical Engineering, Shandong University, Jinan 250061, China
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SHI Xiaohan

SHI Xiaohan

School of Electrical Engineering, Shandong University, Jinan 250061, China
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Affiliation:

School of Electrical Engineering, Shandong University, Jinan 250061, China

Abstract:

The source-grid-storage coordinated planning needs to take into account multiple entities simultaneously. Due to its high dimensionality and strong nonlinearity, the solution process is time-consuming, which limits its practical application. Therefore, an efficient solution method integrating evolutionary algorithms and empirical rules is proposed to fully utilize the strong optimization capability of evolutionary algorithms and the convergence acceleration characteristics of empirical rules, significantly improving the solution efficiency. Firstly, a source-grid-storage coordinated planning model with embedded time-series production simulation is constructed to address the variable operation modes of the new power system. Then, expert experience is summarized and refined, and formalized through a fuzzy reasoning tool. Finally, the empirical rules are integrated into the non-dominated sorting genetic algorithm with elite retention to optimize the initial search space and evolutionary direction, thereby forming an efficient solution algorithm. A case of the 90-bus system of a provincial power grid in China for the siting and sizing of wind and solar power sources and energy storage is used to verify the significant advantages of the proposed method in terms of solution efficiency and optimization effect.

Keywords:

Foundation:

This work is supported by Smart Grid Major Program (2030) (No. 2024ZD0801100).

网址：基于进化算法与经验规则融合的源 https://www.yuejiaxmz.com/news/view/1159470

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