Electrical load distribution forecasting utilizing support vector model (SVM)

Abstract

The significance of electrical load forecasting on the electrical distribution network has become eminent with the entry of energy sector and electrical market. This paper of research comprehends a model for forecasting the electrical load distribution. This paper highlights the forecasting on the electrical distribution system by taking into account the load ambiguities. Support Vector Machine (SVM), which is a machine learning algorithm is the prediction or forecasting model utilized in the proposed paper for forecasting the electrical load distribution. The ambiguities that impact the electrical load distribution are; cooling loads, indoor heat gains and cooling parameters are taken into account during the prediction. The demand for electrical load is impacted by many factors starting from the climatic conditions to the economic-socio influences. The proposed load prediction model is reliable, beneficial and an enhancing model for the conservation of electrical energy in the distribution network.