Profit Maximization Bidding Strategy for a GENCO using Whale Optimization Algorithm

P. Jain, Akash Saxena
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引用次数: 1

Abstract

In a deregulated environment of electricity mar- ket,all participants of this market have intentions to increase their profit as much as possible in absentia of their competitor’s bid prices. These optimal Bidding strategies are first obtained through some conventional methods but In a recent trend of meta-heuristic approaches,this stochastic optimization problem solved through different meta-heuristic approaches. Due to the popularity of stochastic optimization techniques. deterministic approaches are obsolete due to their inefficiency of solving this bidding problem. In the same line of order, This paper presents the application of recent meta heuristic approach namely, Whale Optimization Algorithm (WOA) to solve strategic bidding problem of a test system having 6 competitors and MCP and profit is obtained after optimization routine. The results confirms the supremacy of WOA over other meta-heuristic approaches.
基于鲸鱼优化算法的发电公司利润最大化竞价策略
在一个放松管制的电力市场环境中,在没有竞争对手出价的情况下,市场的所有参与者都有尽可能增加利润的意图。这些最优投标策略首先是通过一些传统的方法得到的,但在最近的元启发式方法的趋势中,这种随机优化问题通过不同的元启发式方法来解决。由于随机优化技术的普及。确定性方法由于在解决投标问题时效率低下而过时。在相同的顺序下,本文提出了应用最新的元启发式方法鲸鱼优化算法(Whale Optimization Algorithm, WOA)来解决具有6个竞争者和MCP的测试系统的策略投标问题,并在优化程序后获得利润。结果证实了WOA优于其他元启发式方法。
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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