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Hybrid approach based on particle swarm optimization for electricity markets participation

DOI:https://doi.org/10.1186/s42162-018-0066-7 In many large-scale and time-consuming problems, the application of metaheuristics becomes essential, since these methods enable achieving very close solutions to the exact one in a much shorter time. In this work, we address the problem of portfolio optimization applied to electricity markets negotiation. As in a market environment, decision-making is carried out in very short times, the application of the metaheuristics is necessary. This work proposes a Hybrid model, combining a simplified exact resolution of the method, as a means to obtain the initial solution for a Particle Swarm Optimization (PSO) approach. Results show that the presented approach is able to obtain better results in the metaheuristic search process.
This work has received funding from the European Union's Horizon 2020 research and innovation programme under project DOMINOES (grant agreement No 771066) and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2019 and Ricardo Faia is supported by FCT Funds through and SFRH/BD/133086/2017 PhD scholarship.
- University of Salamanca Spain
- Polytechnic Institute of Porto Portugal
- International Student Exchange Programs United States
- "UNIVERSIDAD DE SALAMANCA Spain
- International Student Exchange Programs United States
Particle swarm optimization, Portfolio optimization, Metaheuristic search, Energy industries. Energy policy. Fuel trade, HD9502-9502.5, Particle swarm optimization and portfolio optimization, Hybrid model
Particle swarm optimization, Portfolio optimization, Metaheuristic search, Energy industries. Energy policy. Fuel trade, HD9502-9502.5, Particle swarm optimization and portfolio optimization, Hybrid model
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