Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/3396
Título: Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets
Autor: Canizes, Bruno
Soares, João
Faria, Pedro
Vale, Zita
Palavras-chave: Ancillary services
Artificial neural networks
Electricity markets
Linear programming
Mixed integer non-linear programming
Power systems
Data: 2013
Editora: Elsevier
Relatório da Série N.º: Applied Energy; Vol. 108
Resumo: Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.
Peer review: yes
URI: http://hdl.handle.net/10400.22/3396
ISSN: 0306-2619
Aparece nas colecções:ISEP – GECAD – Artigos

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