Optimum Localization of Wind Turbine Sites Using Opposition Based Ant Colony Optimization

Farhad Pouladi, Amir Mohammad Gilani, Bahareh Nikpour, H. Salehinejad
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引用次数: 4

Abstract

With recent increase in energy consumption as well as reduction of fossil fuels, employing new methods for generation of green energy in smart grids, such as wind energy, is of great interest for governments. That is why expanding of wind turbine farms is a priority in many countries. One of the most important parameters in design and implementation of such farms is optimum selection of wind turbine farm location in a way that the corresponding constraints are met. This paper introduces a new optimization algorithm based on the opposition based ant colony optimization (OACO) algorithm for this aim. Analyzes of simulation results demonstrate performance of the proposed method for optimum localization of wind turbine farms in Saudi Arabia case study.
基于对抗的蚁群优化风电机位优化定位
随着近年来能源消耗的增加和化石燃料的减少,在智能电网中采用风能等绿色能源的新方法引起了各国政府的极大兴趣。这就是为什么扩大风力涡轮机农场是许多国家的优先事项。风电场的设计和实现中最重要的参数之一是在满足约束条件的情况下对风电场的位置进行优化选择。本文提出了一种基于对立蚁群算法的优化算法。仿真结果验证了该方法在沙特阿拉伯风力发电场优化定位中的有效性。
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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