基于遗传算法模型的风电厂电源规划
Generation expansion planning in the presence of wind power plants using a genetic algorithm model
摘要：
电力系统规划的一个重要方面是电源扩展规划（GEP）。GEP的目的是加强建设规划，降低安装不同类型发电厂的成本。提出了一种基于遗传算法（GA）的风电场GEP优化方法。由于它是希望整合最大可能的风力发电GEP中，将不同水平的风能发电的约束条件进行了全面的研究。这将允许在网络中获得最大合理的风力穿透量。此外，由于存在不同的风况，强，弱风对GEP的渗透进行了评估。结果表明，最大限度地利用风力发电容量可以增加更强大的风况的开发。考虑到风电产业的发展和风电场建设成本的降低，研究了GEP对风电场建设成本变化的敏感性。结果进一步表明，对于10%的风力发电厂的初始投资成本减少，所提出的模型估计，总成本将被最小化。
英文摘要：
One of the essential aspects of power system planning is generation expansion planning (GEP). The purpose of GEP is to enhance construction planning and reduce the costs of installing different types of power plants. This paper proposes a method based on Genetic Algorithm (GA) for GEP in the presence of wind power plants. Since it is desired to integrate the maximum possible wind power production in GEP, the constraints for incorporating different levels of wind energy in power generation are investigated comprehensively. This will allow obtaining the maximum reasonable amount of wind penetration in the network. Besides, due to the existence of different wind regimes, the penetration of strong and weak wind on GEP is assessed. The results show that the maximum utilization of wind power generation capacity could increase the exploitation of more robust wind regimes. Considering the growth of the wind farm industry and the cost reduction for building wind power plants, the sensitivity of GEP to the variations of this cost is investigated. The results further indicate that for a 10% reduction in the initial investment cost of wind power plants, the proposed model estimates that the overall cost will be minimized.
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