Short-Term Load Forecasting Using the Time Series and Artificial Neural Network Methods
Forecasting of electrical load is very crucial to the effective and efficient operation of any power system. This is achieved by obtaining the most accurate forecast which help in minimizing the risk in decision making and reducesthe costs of operating the power plant. Therefore, the comparative study of time series and artificial neural network methods for short term load forecasting is...
Published at Journal of Electrical and Electronics Engineering (IOSR-JEEE)
Published in 2016
Isaac Samuel, Tolulope Ojewola, Ayokunle Awelewa, Peter Amaize
Samuel Isaac » R. Engr. Isaac A. Samuel obtained his Ph.D degree from Covenant University, March 2017. He is a researcher and faculty at the Department of Electrical and Information Engineering, College of Engineering, Ota, Ogun State. He obtained his PGD and M Eng. degree in Electrical Engineering and obtained a PGD in Management from Bayero University, Kano. He is a Registered Engineer with COREN. He has a... view full profile
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