论文标题
使用遗传算法模型存在风力发电厂的生成扩展计划
Generation expansion planning in the presence of wind power plants using a genetic algorithm model
论文作者
论文摘要
电力系统计划的基本方面之一是发电扩展计划（GEP）。 GEP的目的是增强建筑计划并降低安装不同类型的发电厂的成本。本文提出了一种基于风力发电厂存在的GEP遗传算法（GA）的方法。由于希望将最大可能的风能产生整合在GEP中，因此全面研究了将不同水平的风能结合到发电中的约束。这将允许在网络中获得最大合理量的风渗透。此外，由于存在不同的风状态，因此评估了强风在GEP上的渗透。结果表明，风力发电能力的最大利用可能会增加对风度更强大的风格的利用。考虑到风电场行业的增长以及建造风电厂的成本降低，研究了GEP对这种成本变化的敏感性。结果进一步表明，对于风电厂的初始投资成本降低了10％，拟议的模型估计总成本将最小化。
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.
