A Short-Term Electricity Price Forecasting Scheme for Power Market - World Journal of Engineering and Technology

WJET > Vol.4 No.3, October 2016

A Short-Term Electricity Price Forecasting Scheme for Power Market ()

HTML XML

Download as PDF (Size: 312KB) PP. 58-65

DOI: 10.4236/wjet.2016.43D008 1,645 Downloads 3,299 Views Citations

Author(s)

Gao Gao, Kwoklun Lo, Jianfeng Lu, Fulin Fan

Affiliation(s)

Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK.

ABSTRACT

Electricity price forecasting has become an important aspect of promoting competition and safeguarding the interests of participants in electricity market. As market participants, both producers and consumers intent to contribute more efforts on developing appropriate price forecasting scheme to maximize their profits. This paper introduces a time series method developed by Box-Jenkins that applies autoregressive integrated moving average (ARIMA) model to address a best-fitted time-domain model based on a time series of historical price data. Using the model’s parameters determined from the stationarized time series of prices, the price forecasts in UK electricity market for 1 step ahead are estimated in the next day and the next week. The most suitable models are selected for them separately after comparing their prediction outcomes. The data of historical prices are obtained from UK three-month Reference Price Data from April 1st to July7th 2010.

KEYWORDS

Box-Jenkins Method, ARIMA Models, Electricity Markets, Electricity Prices, Forecasting

Share and Cite:

Gao, G. , Lo, K. , Lu, J. and Fan, F. (2016) A Short-Term Electricity Price Forecasting Scheme for Power Market. World Journal of Engineering and Technology, 4, 58-65. doi: 10.4236/wjet.2016.43D008.

Journals Menu

Follow SCIRP

	+1 323-425-8868
	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Journals Menu

Home

About SCIRP

Service

Policies