基于改进粒子群算法的混合可再生能源系统优化调度

Subrat Bhol, N. C. Sahu, A. Nanda
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摘要

混合电力系统有望成为下一次电力革命的重要组成部分,为偏远地区提供电力,这些地区在成本和地理位置方面几乎不可能获得电网供电。分布式混合可再生能源电力系统可以为这些地区的并网和离网供电。本文关注的是可再生能源与现有供电系统相结合的发电系统价格的最小化问题。考虑了太阳能光伏、风能和火电混合发电系统的经济调度问题。提出了一种改进的粒子群优化(MPSO)方法,使发电成本最小化。该算法对调度问题具有很高的求解效率。本文的主要意图不仅是降低价格,而且是最好地利用当地可用的可再生能源,从而控制碳排放和全球变暖。
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Optimal Dispatch of a Hybrid Renewable Energy System Using Modified PSO Algorithm
Hybrid power system is expected to be major part of next electricity revolution for supplying power to remote areas where the grid power supply is almost impossible in term of cost and geographical location. Distributed hybrid renewable energy power system could afford power supply to these areas under grid and off grid connections. Here in this paper attention has given to minimize the price of generation system integrating the renewable energy sources with the existing power supply system. A solar PV, wind hybrid system with thermal power generation has been considered for economical dispatch of power. A modified Particle swarm optimization (MPSO) method has been applied to minimize the cost of power generation. This algorithm proves highly efficient for the dispatch problems. The main intention of this paper is not only to reduce the price but also the best use of renewable sources locally available, so that the carbon emission and global warming can be controlled.
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