Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/17117
Título: Strategic Particle Swarm Inertia Selection for Electricity Markets Participation Portfolio Optimization
Autor: Faia, Ricardo
Pinto, Tiago
Vale, Zita
Corchado, Juan Manuel
Palavras-chave: Artificial Intelligence
Electricity Market
Inertia Parameter
Particle Swarm Optimization
Portfolio Optimization
Data: 2018
Editora: Taylor and Francis
Resumo: The portfolio optimization is a well-known problem in the areas of economy and finance. This problem has also become increasingly important in electrical power systems, particularly in the area of electricity markets, mostly due to the growing number of alternative/complementary market types that are being introduced to deal with important issues, such as the massive integration of renewable energy sources in power systems. The optimization of electricity market players’ participation portfolio comprises significant time constraints, which cannot be satisfied by the use of deterministic techniques. For this reason, meta-heuristic solutions are used, such as particle swarm optimization. The inertia is one of the most important parameter in this method, and it is the main focus of this paper. This paper studies 18 popular inertia calculation strategies, by comparing their performance in the portfolio optimization problem. A strategic methodology for the automatic selection of the best inertia calculation method for the needs of each optimization is also proposed. Results show that the proposed approach is able to automatically adapt the inertia parameter according to the needs in each execution.
URI: http://hdl.handle.net/10400.22/17117
DOI: 10.1080/08839514.2018.1506971
Versão do Editor: https://www.tandfonline.com/doi/full/10.1080/08839514.2018.1506971
Aparece nas colecções:ISEP – GECAD – Artigos

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