基于协同多目标粒子群优化的交直流系统最优潮流

LI Yahui

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基于协同多目标粒子群优化的交直流系统最优潮流

更新时间：2025-08-13

- 基于协同多目标粒子群优化的交直流系统最优潮流
- Automation of Electric Power Systems Vol. 43, Issue 4, Pages: 94-100(2019)
- 作者机构：
  
  东北电力大学电气工程学院,吉林市,吉林省,132012
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- Published：2019
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LI Yahui. [J]. Automation of electric power systems, 2019, 43(4): 94-100.
DOI：

LI Yahui. [J]. Automation of electric power systems, 2019, 43(4): 94-100. DOI：

摘要

为了统一协调经济性和电压偏差，提出一种基于协同多目标粒子群优化(CMOPSO)的含基于电压源型变流器的高压直流(VSC-HVDC)输电的交直流系统多目标最优潮流(MOPF)算法。首先，基于VSC-HVDC稳态模型，以最小化发电成本和电压偏差为目标，构建交直流系统的MOPF模型；然后，采用CMOPSO算法优化该模型，得到具有良好分布的帕累托最优解集；最后，在通过模糊C均值算法将所得解集进行聚类的基础上，采用灰关联投影法计算各决策方案的优属度，确定反映决策者不同偏好的最优折中解。应用于IEEE 14节点和IEEE 118节点系统的测试结果验证了所提方法的有效性。

Abstract

In order to uniformly coordinate economy and voltage deviations

a novel multi-objective optimal power flow(MOPF)algorithm is proposed for an AC/DC system with VSC-HVDC based on cooperative multi-objective particle swarm optimization(CMOPSO). In order to minimize power generation costs and voltage deviations

the MOPF model of the AC/DC system is built based on the VSC-HVDC steady-state model. The CMOPSO is adopted for solving the MOPF model to find well-distributed Pareto-optimal solutions. Then the solutions are divided into different groups via the fuzzy C-means algorithm. Finally

the optimal compromise solutions reflecting decision-makers' different preferences are identified from each group by comparing the priority memberships which are calculated by using the grey relation projection method. The validity of the proposed approach is verified by using the modified IEEE 14-bus and 118-bus systems.

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