A Sensitivity Analysis of PSO Parameters Solving the P2P Electricity Market Problem

Miguel Vieira, Ricardo Faia, F. Lezama, Z. Vale
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引用次数: 2

Abstract

Energy community markets have emerged to promote prosumers' active participation and empowerment in the electrical power system. These initiatives allow prosumers to transact electricity locally without an intermediary such as an aggregator. However, it is necessary to implement optimization methods that determine the best transactions within the energy community, obtaining the best solution under these models. Particle Swarm Optimization (PSO) fits this type of problem well because it allows reaching results in short optimization times. Furthermore, applying this metaheuristic to the problem is easy compared to other available optimization tools. In this work, we provide a sensitivity analysis of the impact of different parameters of PSO in solving an energy community market problem. As a result, the combination of parameters that lead to the best results is obtained, demonstrating the effectiveness of PSO solving different case studies.
解决P2P电力市场问题的PSO参数敏感性分析
能源共同体市场的出现促进了产消者在电力系统中的积极参与和赋权。这些举措允许产消者在没有聚合器等中介的情况下在当地进行电力交易。然而,有必要实现确定能源社区内最佳交易的优化方法,在这些模型下获得最佳解。粒子群优化(PSO)很适合这类问题,因为它可以在短时间内达到优化结果。此外,与其他可用的优化工具相比,将这种元启发式方法应用于问题很容易。在这项工作中,我们提供了不同参数的PSO在解决能源社区市场问题的影响的敏感性分析。结果表明,粒子群算法可以有效地解决不同的问题。
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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