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

Gao Gao; Kwoklun Lo; Jianfeng Lu

doi:10.1109/UPEC.2017.8231903

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

Gao Gao, Kwoklun Lo, Jianfeng Lu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

4 Citations (Scopus)

144 Downloads (Pure)

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.

Original language	English
Title of host publication	2017 52nd International Universities Power Engineering Conference (UPEC)
Place of Publication	Piscataway, NJ
Publisher	IEEE
Number of pages	6
DOIs	https://doi.org/10.1109/UPEC.2017.8231903
Publication status	Published - 21 Dec 2017
Event	52nd International Universities' Power Engineering Conference - T.E.I. of Crete, Heraklion, Crete, Greece Duration: 29 Aug 2017 → 1 Sept 2017 http://www.upec2017.com/

Conference

Conference	52nd International Universities' Power Engineering Conference
Abbreviated title	UPEC 2017
Country/Territory	Greece
City	Heraklion, Crete
Period	29/08/17 → 1/09/17
Internet address	http://www.upec2017.com/

Keywords

electricity market
electricity price forecasting
risk assessment
risk index

Access to Document

10.1109/UPEC.2017.8231903

Gao-etal-UPEC2017-Risk-assessment-due-to-electricity-price-forecast-uncertaintyAccepted author manuscript, 463 KB

Cite this

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title = "Risk assessment due to electricity price forecast uncertainty in UK electricity market",

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. ",

keywords = "electricity market, electricity price forecasting, risk assessment, risk index",

author = "Gao Gao and Kwoklun Lo and Jianfeng Lu",

note = "{\textcopyright} 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.; 52nd International Universities' Power Engineering Conference, UPEC 2017 ; Conference date: 29-08-2017 Through 01-09-2017",

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AU - Lo, Kwoklun

AU - Lu, Jianfeng

N1 - © 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.

PY - 2017/12/21

Y1 - 2017/12/21

N2 - 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.

AB - 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.

KW - electricity market

KW - electricity price forecasting

KW - risk assessment

KW - risk index

UR - https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8171422

U2 - 10.1109/UPEC.2017.8231903

DO - 10.1109/UPEC.2017.8231903

M3 - Conference contribution book

BT - 2017 52nd International Universities Power Engineering Conference (UPEC)

PB - IEEE

CY - Piscataway, NJ

T2 - 52nd International Universities' Power Engineering Conference

Y2 - 29 August 2017 through 1 September 2017

ER -

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

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