A study of particle swarm technique for renewable energy power systems

N. Phuangpornpitak, W. Prommee, S. Tia, W. Phuangpornpitak
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引用次数: 41

Abstract

Renewable power system is an innovative option for electricity generation as it is a clean energy resource. Noting the climate change becomes an important issue the whole world is currently facing, the ever-increasing price of petroleum products (now about US$ 80 a barrel) and the reduction in cost of renewable energy power systems, opportunities for renewable energy systems to address electricity generation seems to be increasing. However, to achieve commercialization and widespread use, an efficient energy management strategy of system needs to be addressed. Recently, particle swarm optimization (PSO) has been successfully applied to the various fields of power system including economic dispatch problems. This paper presents the survey of PSO in solving optimization problems in electric power systems. The introductory sections provide the new way to implement renewable energy power system using particle swarm technique. Subsequent sections cover recent trends of PSO development in renewable energy power systems. This technique would be useful to determine the powerful energy management strategy so as to meet the required load demand at minimum operating cost while satisfying system equality and inequality constraints.
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粒子群技术在可再生能源发电系统中的应用研究
可再生能源作为一种清洁能源,是一种创新的发电选择。注意到气候变化成为全世界目前面临的一个重要问题,石油产品价格不断上涨(现在每桶约80美元)和可再生能源电力系统成本的降低,可再生能源系统解决发电问题的机会似乎正在增加。然而,为了实现商业化和广泛使用,需要解决一个有效的系统能源管理策略。近年来,粒子群算法已成功地应用于电力系统的各个领域,包括经济调度问题。本文综述了粒子群算法在解决电力系统优化问题中的应用。引言部分提供了利用粒子群技术实现可再生能源电力系统的新途径。随后的章节介绍了可再生能源电力系统中PSO发展的最新趋势。该技术将有助于确定强大的能量管理策略,以最小的运行成本满足所需的负荷需求,同时满足系统的等式和不等式约束。
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