Short Term Load Forecasting Using ARIMA Technique

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Kuheli Goswami, Dipankar Saha, Sanjoy Chakraborty, Abhilash Sharma

Abstract

This paper discusses a new algorithm of a univariate method, which is vitally important to develop a short-term load forecasting module for planning and operation of distribution system. It has many applications including purchasing of energy, generation and infrastructure development etc. We have discussed different time series forecasting approaches in this paper. But ARIMA has proved itself as the most appropriate method in forecasting of the load profile for West Bengal using the historical data of the year of 2017. Auto Regressive Integrated Moving Average model gives more accuracy level of load forecast than any other techniques. Mean Absolute Percentage Error (MAPE) has been calculated for the mentioned forecasted model.

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How to Cite
, K. G. D. S. S. C. A. S. “Short Term Load Forecasting Using ARIMA Technique”. International Journal on Recent and Innovation Trends in Computing and Communication, vol. 6, no. 7, July 2018, pp. 37-39, doi:10.17762/ijritcc.v6i7.1679.
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