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Article: Electricity price forecasting with confidence-interval estimation through an extended ARIMA approach

TitleElectricity price forecasting with confidence-interval estimation through an extended ARIMA approach
Authors
Issue Date2006
Citation
Iee Proceedings: Generation, Transmission And Distribution, 2006, v. 153 n. 2, p. 187-195 How to Cite?
AbstractAccurate electricity price forecasting is a crucial issue concerned by market participants either for developing bidding strategies or for making investment decisions. Due to the complicated factors affecting electricity prices, accurate price forecasting turns out to be very difficult. The autoregressive integrated moving average (ARIMA) approach has been extended to make hourly market clearing price (MCP) forecasting in electricity spot markets with error correction and confidence interval estimation. The ARIMA model used for forecasting price and the method to implement price forecasting are presented first. Then the ARIMA approach is extended to include error correction for improving accuracy of price forecasting. Moreover, the confidence interval of the forecasted prices is estimated assuming the residual errors are in gaussian or uniform distribution. Hourly MCP forecasting of the Californian Power Market is used as a computer example, and the comparison with conventional ARIMA approach is given. Computer test results show clearly that the suggested extended ARIMA approach for spot price forecasting is very effective with satisfactory accuracy. It can work under very worse market conditions with high price volatility.
Persistent Identifierhttp://hdl.handle.net/10722/73491
ISSN
2008 Impact Factor: 0.868
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorZhou, Men_HK
dc.contributor.authorYan, Zen_HK
dc.contributor.authorNi, YXen_HK
dc.contributor.authorLi, Gen_HK
dc.contributor.authorNie, Yen_HK
dc.date.accessioned2010-09-06T06:51:50Z-
dc.date.available2010-09-06T06:51:50Z-
dc.date.issued2006en_HK
dc.identifier.citationIee Proceedings: Generation, Transmission And Distribution, 2006, v. 153 n. 2, p. 187-195en_HK
dc.identifier.issn1350-2360en_HK
dc.identifier.urihttp://hdl.handle.net/10722/73491-
dc.description.abstractAccurate electricity price forecasting is a crucial issue concerned by market participants either for developing bidding strategies or for making investment decisions. Due to the complicated factors affecting electricity prices, accurate price forecasting turns out to be very difficult. The autoregressive integrated moving average (ARIMA) approach has been extended to make hourly market clearing price (MCP) forecasting in electricity spot markets with error correction and confidence interval estimation. The ARIMA model used for forecasting price and the method to implement price forecasting are presented first. Then the ARIMA approach is extended to include error correction for improving accuracy of price forecasting. Moreover, the confidence interval of the forecasted prices is estimated assuming the residual errors are in gaussian or uniform distribution. Hourly MCP forecasting of the Californian Power Market is used as a computer example, and the comparison with conventional ARIMA approach is given. Computer test results show clearly that the suggested extended ARIMA approach for spot price forecasting is very effective with satisfactory accuracy. It can work under very worse market conditions with high price volatility.en_HK
dc.languageengen_HK
dc.relation.ispartofIEE Proceedings: Generation, Transmission and Distributionen_HK
dc.titleElectricity price forecasting with confidence-interval estimation through an extended ARIMA approachen_HK
dc.typeArticleen_HK
dc.identifier.emailNi, YX: yxni@eee.hku.hken_HK
dc.identifier.authorityNi, YX=rp00161en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1049/ip-gtd:20045131en_HK
dc.identifier.scopuseid_2-s2.0-33645138858en_HK
dc.identifier.hkuros120023en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33645138858&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume153en_HK
dc.identifier.issue2en_HK
dc.identifier.spage187en_HK
dc.identifier.epage195en_HK
dc.identifier.isiWOS:000236684300008-
dc.identifier.scopusauthoridZhou, M=35390426600en_HK
dc.identifier.scopusauthoridYan, Z=7402519416en_HK
dc.identifier.scopusauthoridNi, YX=7402910021en_HK
dc.identifier.scopusauthoridLi, G=8400663800en_HK
dc.identifier.scopusauthoridNie, Y=8905645400en_HK
dc.identifier.citeulike5980602-

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