张涛, 张东方, 王凌云, 徐雪琴, 周远化, 张晓林. 基于改进小生境粒子群算法的主动配电网优化重构[J]. 信阳师范学院学报(自然科学版), 2018, 31(3): 473-478. DOI: 10.3969/j.issn.1003-0972.2018.03.026
引用本文: 张涛, 张东方, 王凌云, 徐雪琴, 周远化, 张晓林. 基于改进小生境粒子群算法的主动配电网优化重构[J]. 信阳师范学院学报(自然科学版), 2018, 31(3): 473-478. DOI: 10.3969/j.issn.1003-0972.2018.03.026
ZHANG Tao, ZHANG Dongfang, WANG Lingyun, XU Xueqin, ZHOU Yuanhua, ZAHNG Xiaolin. Optimal Reconfiguration of the Active Distribution Network Based on Improved Niche Multi-objective Particle Swarm Optimization Algorithm[J]. Journal of Xinyang Normal University (Natural Science Edition), 2018, 31(3): 473-478. DOI: 10.3969/j.issn.1003-0972.2018.03.026
Citation: ZHANG Tao, ZHANG Dongfang, WANG Lingyun, XU Xueqin, ZHOU Yuanhua, ZAHNG Xiaolin. Optimal Reconfiguration of the Active Distribution Network Based on Improved Niche Multi-objective Particle Swarm Optimization Algorithm[J]. Journal of Xinyang Normal University (Natural Science Edition), 2018, 31(3): 473-478. DOI: 10.3969/j.issn.1003-0972.2018.03.026

基于改进小生境粒子群算法的主动配电网优化重构

Optimal Reconfiguration of the Active Distribution Network Based on Improved Niche Multi-objective Particle Swarm Optimization Algorithm

  • 摘要: 分布式电源(DG)的接入为主动配电网(ADN)的稳定运行带来了挑战,而重构是提高系统稳定性的重要手段.提出了一种改进小生境多目标粒子群算法(INMPSO),建立了考虑网损、电压质量指数(VQI)、开关操作次数的多目标优化函数,对主动配电网的静态重构模型进行求解.全局最优粒子位置通过小生境共享机制来更新,使种群具有多样性和全局平均分布.根据模糊满意度评价决策方法从得到的Pareto解集中选择出最优折衷解,为决策者提供了科学的决策依据.最后以IEEE33节点标准配电系统为例,并与基本多目标粒子群算法(MPSO)的优化结果进行对比,验证所提模型和方法的有效性.

     

    Abstract: It is a challenge to the stable operation of the Active Distribution Network with the distributed generations (DG), and the reconfiguration is an important method to improve the stability of the system. The Improved Niche Multi-objective Particle Swarm Optimization (INMPSO) was proposed to solve the model of active distribution network reconfiguration with DG; the network loss, voltage quality index and the number of switching operation were set up as the multi-objective optimization functions. Through the niche sharing mechanism which maintains the diversity and distribution uniformity of the population to update the global optimal position, the optimal compromise solution was chosen from the Pareto solutions using the fuzzy satisfaction evaluation decision method, which provides a scientific basis for the decision maker. Finally, the optimization results of IEEE33 node distribution system based on MPSO were compared to verify the effectiveness of the proposed model and method.

     

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