Implementing “R” Programming for Time Series Analysis and Forecasting of Electricity Demand for Texas, USA

This paper is aimed at implementing the programming language R to analyze and forecast electricity supply-demand for Texas. Historical weekly electricity supply-demand data for Texas, September 2016 through August 2017 was used to forecast future electricity demand. One year of electricity supply demand data was retrieved from the Electric Reliability Council of Texas (ERCOT) data bank and arranged in a per day electricity supply-demand, allocated over a twelve month period to give one data point per day. The formulated model was processed and implemented in the R programming environment for stochastic analysis and future electricity demand prediction. The predicted model was compared with the actual electricity supply-demand, September 2017 through June 2018. Time series forecasting of electricity demand provides information about future electricity demand to utility operators, who can make decisions on when to implement peak shaving.