Economic Dispatch with Integrated Wind-thermal using Particle Swarm Optimization

R. Saravanan, S. Subramanian, V. Dharmalingam, S. Ganesan
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引用次数: 2

Abstract

The Economic dispatch is an important optimization task in power system. Thermal power plants are the major electrical energy producers. Need for renewable energy occurs due to the extinction of fossil fuels. Hence, it is necessary to operate these renewable plants with the thermal plants. In India, especially in Tamilnadu, Wind is the renewable plant which is widely available. The problem with the wind plant is its unpredictability.Hence, better wind thermal coordination economic dispatch method is necessary to integrate wind power reliably and efficiently. In this paper, Particle swarm optimization (PSO) technique is utilized to coordinate the wind and thermal generation dispatch and to minimize the total production cost. Ten units of thermal system incorporating wind power plant is utilized for numerical simulation. Different simulations with and without wind power production are simulated. Simulation result shows the effectiveness of wind power generation in reducing total fuel cost when compared with the genetic algorithm.
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基于粒子群优化的风热综合经济调度
经济调度是电力系统中一项重要的优化任务。火力发电厂是主要的电能生产者。对可再生能源的需求是由于化石燃料的消失而产生的。因此,有必要将这些可再生能源发电厂与热电厂一起运行。在印度,特别是在泰米尔纳德邦,风能是一种可再生能源,广泛使用。风力发电厂的问题在于它的不可预测性。因此,需要更好的风热协调经济调度方法来实现风电的可靠高效整合。本文利用粒子群优化(PSO)技术来协调风电和热电发电的调度,以使总生产成本最小化。利用10台含风电场的热力系统进行数值模拟。在有和没有风力发电的情况下进行了不同的模拟。仿真结果表明,与遗传算法相比,风力发电在降低总燃料成本方面是有效的。
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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