Prediction of the lahore electricity consumption using seasonal discrete grey polynomial model

Abstract

Almost all cities of Pakistan are economically affected by the electricity shortage due to the continuously increasing demand for electricity. To correctly forecast the seasonal fluctuations of the electricity consumption of Lahore city in Pakistan, we proposed the SDGPM(1,1,N) model, which is a seasonal discrete grey polynomial model combined with seasonal adjustment. We conducted an empirical analysis using the proposed model based on the seasonal electricity consumption data of Lahore city in Pakistan from 2014 to 2021. The findings from the SDGPM (1,1,N) model are compared with those collected through the original grey model DGPM(1,1,N) and other eight models. The comparison’s findings demonstrated that the SDGPM(1,1,N) model is indeed capable of correctly identifying seasonal fluctuations of electricity consumption in Lahore city and its prediction accuracy is significantly higher than the original DGPM(1,1,N) model and the other seven models. The SDGPM(1,1,N) model’s forecast findings for Lahore from 2022 to 2025 indicate that the city’s energy consumption is expected to rise marginally, although there will still be significant seasonal fluctuations. It is predicted that the annual electricity consumption from 2022 to 2025 will be 26249, 26749, 27928, and 28136 with an annual growth rate of 7.18%. This forecast can provide policymakers ahead start in planning to ensure that supply and demand are balanced.