Supplier side optimal bidding strategy for electricity market using bacterial foraging optimization algorithm

L Udaysriram, S. Raju, Chandram Karri
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Abstract

In this article, bacterial foraging optimization (BFO) algorithm is developed for single side optimal bidding strategy in an electricity market. Optimal bidding strategy is one of the important functions in the electricity market along with forecasting of the electricity price and the profit based unit commitment. The prime objective of generating company (Genco) is to maximize their profit when they participate in the bidding process. The BFO algorithm has been used to maximize the probability density function (pdf). In the second stage the BFO algorithm is again applied to maximize the profit of the suppliers. The Proposed algorithm is developed in MATLAB (Version, 2019) and tested on standard test case available in the literature. Also, the simulation results are presented and compared. It is noticed that the proposed method yields the best results in terms of profit.
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基于细菌觅食优化算法的电力市场供方最优竞价策略
针对电力市场中的单边最优竞价策略,提出了细菌觅食优化算法。最优竞价策略与电价预测和基于利润的机组承诺是电力市场的重要功能之一。发电公司(Genco)的主要目标是在参与投标过程中实现利润最大化。BFO算法被用来最大化概率密度函数(pdf)。在第二阶段,再次应用BFO算法使供应商的利润最大化。提出的算法在MATLAB (Version, 2019)中开发,并在文献中可用的标准测试用例上进行了测试。最后给出了仿真结果并进行了比较。结果表明,本文提出的方法在利润方面的效果最好。
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