W. A. R, Intan Azmira and T. K. A, Rahman and Zakaria, Zuhainaz and Ahmad, Arfah (2013) Short term electricity price forecasting using neural network. In: 4th International Conference on Computing and Informatics (ICOCI 2013), 28 -30 August 2013, Kuching, Sarawak, Malaysia.

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Abstract

This paper presents neural networks applied for short term electricity price forecasting in Ontario energy market.The accuracy in electricity price forecasting is very crucial for the power producer and consumer.With the accurate price forecasting, power producer can maximize their profit and manage short term operation and long term planning. Meanwhile, consumer can maximize their utilities efficiently. The objective of this research is to develop models for day ahead price forecasting using back-propagation neural network during summer.Six models were developed representing six types of inputs. The result shows that 24 models representing 24 hours ahead price forecasting with price and demand inputs gives better result compared to other five models due to unique model developed for each hour rather than a model for a day with mean absolute percentage error (MAPE) of 18.74%.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	ISBN: 9789832078791 Organized by: Universiti Utara Malaysia
Uncontrolled Keywords:	short term electricity price forecast, neural network, day ahead forecast, MAPE
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Divisions:	College of Arts and Sciences
Depositing User:	Mrs. Norazmilah Yaakub
Date Deposited:	24 Aug 2014 02:42
Last Modified:	24 Aug 2014 02:42
URI:	https://repo.uum.edu.my/id/eprint/11974

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