Multiagent system for adaptive strategy formulation in electricity markets

Pinto, Tiago; Vale, Zita; Rodrigues, Fátima; Praça, Isabel; Morais, H.

http://hdl.handle.net/10400.22/1399

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Resumo(s)

Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is multiagent based, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal.

Palavras-chave

Adaptive learning Data-mining techniques Electricity markets Forecasting methods Multiagent systems

URI

http://hdl.handle.net/10400.22/1399

Editora

IEEE

DOI

10.1109/IA.2011.5953609

Coleções

ISEP – GECAD – Comunicações em eventos científicos

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