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

被引:2
作者
Vieira, Miguel [1 ]
Faia, Ricardo [2 ]
Lezama, Fernando [2 ]
Vale, Zita [2 ]
机构
[1] Polytech Porto IPP, Sch Engn ISEP, Porto, Portugal
[2] Polytech Porto ISEP IPP, GECAD, Porto, Portugal
来源
2022 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2022年
关键词
Local electricity markets; Particle Swarm Optimization; Peer-to-Peer transactions; Sensitivity analysis; Swarm intelligence; PEER-TO-PEER;
D O I
10.1109/CEC55065.2022.9870290
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页数:7
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