Electricity Load Prediction Using Artificial Neural Network By Back Propagation

Authors : Joe Joseph, Nithin James, Sebastian Sachin, Varkey Vincent, Sminu Izudheen

Volume/Issue : Volume 2 - 2017, Issue 9 - September

Google Scholar : https://goo.gl/DF9R4u

Scribd : https://goo.gl/W6rEM7

Thomson Reuters ResearcherID : https://goo.gl/3bkzwv

This paper presents a data mining approach to forecast the power consumption of a geographical region based on the meteorological data. Artificial Neural Network using Back Propagation is the data mining approach adopted here. The research is conducted using meteorological and load consumption data in Kerala region over the period of 2011- 2012. The historical data containing temperature, humidity, public holidays and the daily load consumption values are used for training the system. A predictive model is then built which gather information from the training data set and generates knowledge for predicting the demand of the region. Results on statistical significance tests assert that the proposed method can be used as an effective model to study the load consumption pattern which in turn helps to forecast the electricity demand of a region.

Keywords : Data Mining;Artificial Neural Network;Back Propagation.


Paper Submission Last Date
31 - August - 2022

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