Predicting Power Consumption of Individual Household using Machine Learning Algorithms

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Sobhana M
Smitha Chowdary Ch
D.N.V.S.L.S. Indira
Gaddameedi Dinesh Kumar


Climate change, as known, is the dangerous environmental effect we are going to face in the near future and electricity contributes the majority of its part in overcoming climate change as per the trends. Usage of electricity is widely increasing all over the world mainly as an alternative to the use of fossil fuels. In households the usage is rapidly increasing day by day, owing to the increase in the number of devices running on electricity. As we have observed mainly after the relaxation of the lockdown the bills received by households, especially in cities were unhappy and have left most of the people aghast. It is evident that users have no idea about the power they consume. In this work, a model to forecast the electricity bill of household users based on the previous trends and usage patterns by making use of machine learning techniques has been proposed. The historical data of the user is studied and the learning is done iteratively to improve the accuracy of the model. The model can then be used to forecast the consumption beforehand.

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How to Cite
M, S. ., S. C. . Ch, D. . Indira, and G. D. . Kumar. “Predicting Power Consumption of Individual Household Using Machine Learning Algorithms”. International Journal on Recent and Innovation Trends in Computing and Communication, vol. 11, no. 3s, Mar. 2023, pp. 247-52,


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