首页> 外文会议>International Conerence on Technologies and Materials for Renewable Energy, Environment and Sustainability >USE OF GENITIC ALGORITHM AND PARTICLE SWARM OPTIMISATION METHODS FOR THE OPTIMAL CONTROL OF THE REACTIVE POWER IN WESTERN ALGERIAN POWER SYSTEM
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USE OF GENITIC ALGORITHM AND PARTICLE SWARM OPTIMISATION METHODS FOR THE OPTIMAL CONTROL OF THE REACTIVE POWER IN WESTERN ALGERIAN POWER SYSTEM

机译:遗传算法及粒子群优化方法在阿尔及利亚电力系统中对无功功率的最优控制

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This paper describes the methodology adopted for controlling the reactive power in western Algerian power system. This Algerian system is in phase of extension because of the strong increase of the request of electricity (+ 5 in 7 % a year), With a population increasing by 1.2 % a year, and which changes these consumer habits using a large number of modern electrical equipments. Our objective is to study this system and to try to solve these problems by the optimization of the reactive powers through Felexible AC Transmission System devices and metaheuristics methods of optimization. Several metaheuristics algorithms have been developed based on Genetic Algorithm approach and the swarm intelligence. Those algorithms try to prove their effectiveness in minimizing the power losses, subject to satisfying system constraints like voltage levels, real and reactive power flow on transmission lines, transformer tap settings and switching of discrete portions of inductors or capacitors.
机译:本文介绍了控制阿尔及利亚电力系统中的无功功率的方法。这一阿尔及利亚系统处于延期阶段,因为电力要求(每年+ 5分)强劲增加,人口每年增加1.2%,并使用大量现代改变这些消费习惯电气设备。我们的目标是研究该系统,并试图通过富有交流传输系统装置的优化反应力和优化方法来解决这些问题。基于遗传算法和群体智能开发了几种半导体算法。这些算法尝试在最小化功率损耗方面证明其有效性,以满足系统限制,如电压电平,实际和无功功率流动,变压器抽头设置和切换电感器或电容的离散部分。

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