Forecasting of Domestic Electricity Consumption in Assam, India

Authors

  • Ruma Talukdar Department of Statistics, Cotton University, Panbazar, Guwahati, Assam, India.
  • Nibedita Mahanta Department of Statistics, Bhattadev University, Pathsala, Bajali, Assam, India,

DOI:

https://doi.org/10.32479/ijeep.14509

Keywords:

Assam, ARIMA, Domestic electricity consumption, Forecasting, Growth Curve, Multiple Linear Regression.

Abstract

Though the power supply scenario in Assam is not comparable with other developed states of India, yet it is improving gradually. With increasing household electrification rate, increasing income and technological development, the share of Domestic electricity consumption in the state is experiencing a rapid growth in comparison to the other sectors like Industry, Commerce, Agriculture etc. and therefore the forecasting of domestic electricity consumption become very important to meet the power needs of the consumer. The aim of this study is to suggest the best forecasting model for domestic electricity consumption in Assam. For this purpose, three models viz. Multiple Linear Regression considering the effects of population and per capita income; ARIMA and Growth curves viz Linear, Quadratic, Cubic, Exponential, Logarithmic and Inverse are used considering the time period 1980-2018. When growth curves are compared in terms of diagnostic criteria- Adjusted R2, RMSE, AME and MAPE, then it is found that exponential model fits the data better than the other growth models. After that, comparisons are made among the models Multiple Linear Regression, ARIMA and Exponential by considering their average relative error and found the efficiency of ARIMA the highest followed by Exponential and Multiple Linear Regression models. Therefore, forecasting of domestic electricity consumption in Assam has been done with ARIMA model for the next 10 years.

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Published

2023-09-16

How to Cite

Talukdar, R., & Mahanta, N. (2023). Forecasting of Domestic Electricity Consumption in Assam, India. International Journal of Energy Economics and Policy, 13(5), 229–235. https://doi.org/10.32479/ijeep.14509

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Articles