| 引用本文: | 张义坤,何英杰,刘进军.面向供需侧多利益主体的电压暂降治理设备定制化配置方法研究[J].电力系统保护与控制,2025,53(16):108-119.[点击复制] |
| ZHANG Yikun,HE Yingjie,LIU Jinjun.Research on customized allocation method for voltage sag mitigation equipment considering multiple stakeholders on the supply and demand sides[J].Power System Protection and Control,2025,53(16):108-119[点击复制] |
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| 摘要: |
| 针对当前配电网电压暂降治理方案难以协调供需侧多利益主体差异化诉求的问题，提出面向多利益主体的动态电压恢复器(dynamic voltage restorers, DVR)与配电网静止同步补偿器(distribution static synchronous compensator, D-STATCOM)定制化配置方法。首先，基于暂降事件的不均匀分布特性，分析治理效果与投资成本之间存在的不可量化的非线性关系，明确多目标优化配置方案的必要性。然后，提出主体间治理-投资诉求差异化、主体内诉求统一化的配置策略，并建立计及投资成本与治理效果的多目标暂降治理设备优化配置模型。其次，针对所提模型高度非凸的特点，提出基于精英反向学习策略的多目标蛇优化算法求解模型，得到帕累托最优解集，并利用模糊决策方法筛选配置方案。最后，基于IEEE34节点系统进行算例分析，结果表明所提方法能够有效整合各利益主体在治理与投资方面的差异化诉求，协同定制暂降治理设备最优配置方案。 |
| 关键词: 电压暂降 动态电压恢复器 配电网静止同步补偿器 优化配置 多目标蛇优化算法 精英反向学习 |
| DOI：10.19783/j.cnki.pspc.241543 |
| 投稿时间：2024-11-19修订日期：2025-03-18 |
| 基金项目:国家自然科学基金项目资助(51777158); 陕西省科学家工程师项目资助(2024QCY-KXJ-138) |
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| Research on customized allocation method for voltage sag mitigation equipment considering multiple stakeholders on the supply and demand sides |
| ZHANG Yikun,HE Yingjie,LIU Jinjun |
| (School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China) |
| Abstract: |
| To address the challenge of aligning the diverse interests of multiple stakeholders on both the supply and demand sides in grid voltage sag mitigation strategies for distribution networks, this paper proposes a customized allocation method for dynamic voltage restorers (DVR) and distribution static synchronous compensators (D-STATCOM) oriented toward multiple stakeholders. First, based on the heterogeneous distribution characteristics of voltage sag events, the unquantifiable and nonlinear relationship between mitigation effectiveness and investment cost is analyzed, demonstrating the necessity of a multi-objective optimized configuration scheme. Second, an allocation strategy is then proposed to reconcile inter-stakeholder differences in mitigation-investment preferences while ensuring intra-stakeholder demand consistency. A multi-objective optimization model is developed that incorporates both investment cost and mitigation performance. Given the high non-convexity of the proposed model, a multi-objective snake optimization algorithm enhanced by an elite opposition-based learning strategy is employed to obtain the Pareto optimal solution set, and a fuzzy decision-making method is used to select the final configuration scheme. Finally, case studies are performed on the IEEE 34-bus system, and the results confirm that the proposed method effectively integrates the diverse interests of various stakeholders, enabling a coordinated and customized optimal configuration of voltage sag mitigation devices. |
| Key words: voltage sag dynamic voltage restorer distribution static synchronous compensator (D-STATCOM) optimal allocation multi-objective snake optimization algorithm elite opposition-based learning |
