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)
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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: https://orcid.org/0000-0002-2320-9371, Lo, Kwoklun and Lu, Jianfeng ORCID: https://orcid.org/0000-0002-7855-1668;-
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Item type: Book Section ID code: 65761 Dates: DateEvent21 December 2017Published28 August 2017AcceptedNotes: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Subjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering
Faculty of EngineeringDepositing user: Pure Administrator Date deposited: 12 Oct 2018 11:27 Last modified: 19 Dec 2024 01:06 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/65761