Electricity load and price forecasting with influential factors in a deregulated power industry

With the emergence of smart power grid and distributed generation technologies in recent years, there is need to introduce new advanced models for forecasting. Electricity load and price forecasts are two primary factors needed in a deregulated power industry. The performances of the demand response...

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Main Authors: Hassan, S., Khosravi, A., Jaafar, J., Raza, M.Q.
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.32026 /
Published: Institute of Electrical and Electronics Engineers Inc. 2014
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84908614947&doi=10.1109%2fSYSOSE.2014.6892467&partnerID=40&md5=0a6e161e4834d9fa9ec25c37f78b36ac
http://eprints.utp.edu.my/32026/
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spelling utp-eprints.320262022-03-29T04:06:48Z Electricity load and price forecasting with influential factors in a deregulated power industry Hassan, S. Khosravi, A. Jaafar, J. Raza, M.Q. With the emergence of smart power grid and distributed generation technologies in recent years, there is need to introduce new advanced models for forecasting. Electricity load and price forecasts are two primary factors needed in a deregulated power industry. The performances of the demand response programs are likely to be deteriorated in the absence of accurate load and price forecasting. Electricity generation companies, system operators, and consumers are highly reliant on the accuracy of the forecasting models. However, historical prices from the financial market, weekly price/load information, historical loads and day type are some of the explanatory factors that affect the accuracy of the forecasting. In this paper, a neural network (NN) model that considers different influential factors as feedback to the model is presented. This model is implemented with historical data from the ISO New England. It is observed during experiments that price forecasting is more complicated and hence less accurate than the load forecasting. © 2014 IEEE. Institute of Electrical and Electronics Engineers Inc. 2014 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84908614947&doi=10.1109%2fSYSOSE.2014.6892467&partnerID=40&md5=0a6e161e4834d9fa9ec25c37f78b36ac Hassan, S. and Khosravi, A. and Jaafar, J. and Raza, M.Q. (2014) Electricity load and price forecasting with influential factors in a deregulated power industry. In: UNSPECIFIED. http://eprints.utp.edu.my/32026/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description With the emergence of smart power grid and distributed generation technologies in recent years, there is need to introduce new advanced models for forecasting. Electricity load and price forecasts are two primary factors needed in a deregulated power industry. The performances of the demand response programs are likely to be deteriorated in the absence of accurate load and price forecasting. Electricity generation companies, system operators, and consumers are highly reliant on the accuracy of the forecasting models. However, historical prices from the financial market, weekly price/load information, historical loads and day type are some of the explanatory factors that affect the accuracy of the forecasting. In this paper, a neural network (NN) model that considers different influential factors as feedback to the model is presented. This model is implemented with historical data from the ISO New England. It is observed during experiments that price forecasting is more complicated and hence less accurate than the load forecasting. © 2014 IEEE.
format Conference or Workshop Item
author Hassan, S.
Khosravi, A.
Jaafar, J.
Raza, M.Q.
spellingShingle Hassan, S.
Khosravi, A.
Jaafar, J.
Raza, M.Q.
Electricity load and price forecasting with influential factors in a deregulated power industry
author_sort Hassan, S.
title Electricity load and price forecasting with influential factors in a deregulated power industry
title_short Electricity load and price forecasting with influential factors in a deregulated power industry
title_full Electricity load and price forecasting with influential factors in a deregulated power industry
title_fullStr Electricity load and price forecasting with influential factors in a deregulated power industry
title_full_unstemmed Electricity load and price forecasting with influential factors in a deregulated power industry
title_sort electricity load and price forecasting with influential factors in a deregulated power industry
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2014
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84908614947&doi=10.1109%2fSYSOSE.2014.6892467&partnerID=40&md5=0a6e161e4834d9fa9ec25c37f78b36ac
http://eprints.utp.edu.my/32026/
_version_ 1741197676304662528
score 11.62408

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