Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/1475
Título: ANN based day-ahead spinning reserve forecast for electricity market simulation
Autor: Faria, Pedro
Vale, Zita
Soares, João
Khodr, H. M.
Palavras-chave: Artificial neural networks (ANN)
Ancillary services
Multi-agent systems
Spinning reserve
Electricity markets
Power systems
Simulation
Data: 2009
Editora: IEEE
Relatório da Série N.º: Intelligent System Applications to Power Systems
Resumo: Electricity market players operating in a liberalized environment require adequate decision support tools, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. This paper deals with short-term predication of day-ahead spinning reserve (SR) requirement that helps the ISO to make effective and timely decisions. Based on these forecasted information, market participants can use strategic bidding for day-ahead SR market. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.
URI: http://hdl.handle.net/10400.22/1475
ISBN: 978-1-4244-5097-8
Versão do Editor: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5352930
Aparece nas colecções:ISEP – GECAD – Comunicações em eventos científicos

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