A Short-Term Electricity Price Forecasting Scheme for Power Market

Abstract

Electricity price forecasting has become an important aspect of promoting competi-tion and safeguarding the interests of participants in electricity market. As market participants, both producers and consumers intent to contribute more efforts on de-veloping 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 pre-diction outcomes. The data of historical prices are obtained from UK three-month Reference Price Data from April 1st to July7th 2010.