A long-term swarm intelligence hedging tool applied to electricity markets

• Autor(es): Azevedo, Filipe ; Vale, Zita
• Data: 2009
• Identificador Persistente: http://hdl.handle.net/10400.22/1483
• Origem: Repositório Científico do Instituto Politécnico do Porto
• Assunto(s): Electricity markets; Particle swarm optimization; Genetic algorithm
• Tipo de Documento: Documento de conferência
• Idioma: Inglês

Descrição

This paper proposes a swarm intelligence long-term hedging tool to support electricity producers in competitive electricity markets. This tool investigates the long-term hedging opportunities available to electric power producers through the use of contracts with physical (spot and forward) and financial (options) settlement. To find the optimal portfolio the producer risk preference is stated by a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance estimation and the expected return are based on a forecasted scenario interval determined by a long-term price range forecast model, developed by the authors, whose explanation is outside the scope of this paper. The proposed tool makes use of Particle Swarm Optimization (PSO) and its performance has been evaluated by comparing it with a Genetic Algorithm (GA) based approach. To validate the risk management tool a case study, using real price historical data for mainland Spanish market, is presented to demonstrate the effectiveness of the proposed methodology.