Multi-objective Combined Heuristic-SPSO for Power Loss and Congestion Mitigation in Distribution Networks

C. Iraklis
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Abstract

Renewable energy sources and distributed power generation units already have an important role in electrical power generation. A mixture of different technologies penetrating the electrical grid, adds complexity in the management of distribution networks. High penetration of distributed generation (DG) units creates node over-voltages, increased power losses, unreliable power management, reverse power flow and congestion. This paper presents an optimization algorithm capable of reducing congestion and power losses, both described as a function of weighted sum. Two factors that describe congestion are being proposed. An upgraded selective particle swarm optimization algorithm (SPSO) is used as a solution focusing on the technique of network reconfiguration. T he u pgraded S PSO a lgorithm is achieved with the addition of a heuristic algorithm specializing in reduction of power losses, with several scenarios being simulated. Results show significant i mprovement in m inimization of losses and congestion while achieving very small calculation times.
配电网损耗与拥塞缓解的多目标联合启发式- spso算法
可再生能源和分布式发电机组已经在电力生产中发挥了重要作用。不同技术的混合渗透电网,增加了配电网管理的复杂性。分布式发电(DG)机组的高渗透率会造成节点过电压、功率损耗增加、不可靠的电源管理、反向潮流和拥塞。本文提出了一种能够减少拥塞和功率损耗的优化算法,两者都被描述为加权和函数。人们提出了两个描述拥堵的因素。采用一种改进的选择性粒子群优化算法(SPSO)作为解决方案,重点关注网络重构技术。在升级后的S PSO算法中,增加了一种专门用于降低功率损耗的启发式算法,并模拟了几种场景。结果表明,在实现非常小的计算时间的同时,在最小化损失和拥塞方面有了显着的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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