基于磷虾群算法的解除管制电力市场双向最优竞价策略

L. Uday Kiran, S. Sivanagaraju, Chandram Karri
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引用次数: 0

摘要

本文利用Krill herd (KH)算法求解了放松管制下电力市场的双边最优竞价策略问题。投标系数和市场出清价格(MCP)是决定消费者和供应商利润的主要因素。在放宽规制的情况下,发电公司和配电公司以利润最大化为目标进行投标。首先采用KH算法在概率命运函数(pdf)的最大值处寻找投标系数,然后使用相同的算法评估最优投标参数,以使消费者和供应商的利润最大化。在确定最优投标系数的过程中,上述两步是相互依存的。KH算法的代码在IEEE 30总线系统上用MATLAB(2019版)开发并执行。给出了输出功率、投标系数等仿真结果。将该方法的结果与传统方法、启发式方法和混合方法进行了比较。结果表明,所提出的算法在相当长的计算时间内可获得最佳收益。该方法也可用于电力市场的实时运行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Double Side Optimal Bidding Strategy In Deregulated Electricity Market Using Krill Herd Algorithm
In this article, double side optimal bidding strategy (DSOBS) for electricity market in deregulation has been solved using Krill herd (KH) algorithm. Bidding coefficients and market clearing price (MCP) are the prime factors to decide the profit of the consumers and suppliers. In the deregulation, the generating companies and distribution companies submit their bids for maximizing the profit. Initially, The KH algorithm is applied to find the bidding coefficients at the maximum value of probability destiny function (pdf), and then the same algorithm is used for evaluating the optimal bidding parameters to maximise the profit of consumers and suppliers. In the process of determining the optimal bidding coefficients, the above two steps are interdependent. Code of the KH algorithm is developed and executed on IEEE 30 bus system in MATLAB (2019 version). Simulation results such as output powers, bidding coefficients are presented. Outcome results of the suggested method are compared with the conventional, heuristic and hybrid methods. It has been found that the suggested algorithm provides the best profits within considerable computational time. Also the proposed method can be suggested for the real time operation of electricity markets.
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