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首页> 外文期刊>Renewable & Sustainable Energy Reviews >Assessment of optimization algorithms capability in distribution network planning: Review, comparison and modification techniques
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Assessment of optimization algorithms capability in distribution network planning: Review, comparison and modification techniques

机译:配电网规划中优化算法能力的评估:审查,比较和修改技术

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摘要

Optimal expansion of medium-voltage power networks because of load growth is a combinatorial problem which is important from technical and economic points of view. The planning solutions consist of installation and/or reinforcement of high voltage/medium voltage (HV/MV) substations, feeder sections, distributed generation (DG) and storage units to expand the capacity of the network. The cost objective function of the system should be minimized subject to the technical constraints. Due to the complicacy and the complexity of the problem, it should be solved by modern optimization algorithms. In this paper, the most famous optimization algorithms for solving the distribution network planning problem are reviewed and compared, and some points are proposed to improve the performance of the algorithms. In order to compare the algorithms in practice, and verify the proposed improvement points, the numerical studies on three test distribution networks are presented. The results show that every algorithm has its own advantages and disadvantages in specific conditions. However, in general manner, the hybrid Tabu search/genetic algorithm (TS/GA) and the improved particle swarm optimization (PSO) algorithm proposed in this paper are the best choices for optimal distribution network planning. (C) 2016 Elsevier Ltd. All rights reserved.
机译:由于负载的增长,中压电网的最佳扩展是一个组合问题,从技术和经济角度来看,这是很重要的。规划解决方案包括安装和/或加固高压/中压(HV / MV)变电站,馈线部分,分布式发电(DG)和存储单元,以扩展网络的容量。该系统的成本目标功能应在技术限制的前提下最小化。由于问题的复杂性和复杂性,应通过现代优化算法解决。本文对解决配电网规划问题最著名的优化算法进行了综述和比较,并提出了一些改进算法的要点。为了在实践中比较算法,并验证所提出的改进点,对三个测试配电网进行了数值研究。结果表明,每种算法在特定条件下各有优缺点。然而,从总体上讲,本文提出的混合禁忌搜索/遗传算法(TS / GA)和改进的粒子群优化(PSO)算法是最优配电网规划的最佳选择。 (C)2016 Elsevier Ltd.保留所有权利。

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