Abstract: This research presented a improving the power transfer capacity of 11KVA distribution network using artificial neural based demand side management technique. The study was embarked on to address the problem of low profit margin experienced in the distribution companies and also the issues of user dissatisfaction on the quality of power supplied. This was addressed using artificial neural network to develop prediction model using data collected from EEDC and then train. The model was implemented with Matlab and deployed for load forecasting and demand response. The result showed that the load forecast accuracy is 94% while the cost estimated accuracy is 97.6%. The implication of this result showed that the model will accurately provides information for better demand response.
Keyword: Power transfer capacity, artificial neural network, demand side management technique, 11KVA distribution network, Load forecasting, prediction model.
Title: IMPROVING THE POWER TRANSFER CAPACITY OF 11KVA DISTRIBUTION POWER NETWORK USING ARTIFICIAL NEURAL BASED DEMAND SIDE MANAGEMENT
Author: Okechukwu Cletus, J. Eke ., Odeh A.A, J.C. Iyidiobi
International Journal of Electrical and Electronics Research
ISSN 2348-6988 (online)
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