Nowadays, a country’s economy development is estimated from tracking light from space at night. Therefore, electricity has become a major factor in determining national economy. Accurate models have become necessary to help electricity companies to forecast load in advance so that electricity is always present in every corner of a country. In this paper, we have made an attempt to review electricity load forecasting techniques. This review paper overviews the existing electricity demands prediction approaches such as traditional approaches, statistical approaches and machine learning based approaches. It further presents the pros and cons of various techniques. It also presents the challenges of this predictive analysis.

Prediction, smart grid, artificial neural network, short-term load forecasting

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