Risk assessment due to electricity price forecast uncertainty in UK electricity market

Gao, Gao and Lo, Kwoklun and Lu, Jianfeng; (2017) Risk assessment due to electricity price forecast uncertainty in UK electricity market. In: 2017 52nd International Universities Power Engineering Conference (UPEC). IEEE, GRC. (https://doi.org/10.1109/UPEC.2017.8231903)

[thumbnail of Gao-etal-UPEC2017-Risk-assessment-due-to-electricity-price-forecast-uncertainty]
Preview
 Text. Filename: Gao_etal_UPEC2017_Risk_assessment_due_to_electricity_price_forecast_uncertainty.pdf
Accepted Author Manuscript
Download (474kB)| Preview

Abstract

This paper illustrates the risk assessment on electricity price forecast uncertainty. The high-risk periods under different time have been indicated. Autoregressive integrated moving average (ARIMA) models and artificial neural network (ANN) techniques are introduced to forecast electricity prices in UK electricity market. Also, this paper investigates the risk index of electricity prices due to forecast uncertainties in the competitive power market through two aspects – daily and seasonal. This risk index is calculated using the errors of short-term electricity price forecast. The input data of forecasting models is divided into weekday and weekend profiles and this is done to observe the different electricity price dynamic risks between weekdays and weekends.

ORCID iDs

Gao, Gao ORCID logoORCID: https://orcid.org/0000-0002-2320-9371, Lo, Kwoklun and Lu, Jianfeng ORCID logoORCID: https://orcid.org/0000-0002-7855-1668;
CORE (COnnecting REpositories)