Day-ahead price forecasting in restructured power systems using artificial neural networks

Over the past 15 years most electricity supply companies around the world have been restructured from monopoly utilities to deregulated competitive electricity markets. Market participants in the restructured electricity markets find short-term electricity price forecasting (STPF) crucial in formula...

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Veröffentlicht in:	Electric power systems research Jg. 78; H. 8; S. 1332 - 1342
Hauptverfasser:	Vahidinasab, V., Jadid, S., Kazemi, A.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.08.2008 Elsevier
Schlagworte:	Applied sciences Artificial neural networks Electrical engineering. Electrical power engineering Electrical power engineering Electricity price forecasting Exact sciences and technology Fuzzy clustering method Levenberg–Marquardt algorithm Miscellaneous Operation. Load control. Reliability Power networks and lines Sensitivity analysis Electricity price forecasting Sensitivity analysis Levenberg–Marquardt algorithm Fuzzy clustering method Artificial neural networks Short term Automatic classification Deregulation Profitability Power system economics Restructuration Daily variation Neural network Risk analysis Implementation Electrical network Levenberg Marquardt algorithm Pricing Power markets Economic aspect Open market Risk management Learning algorithm Comparative study Levenberg-Marquardt algorithm
ISSN:	0378-7796, 1873-2046
Online-Zugang:	Volltext
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