An Ensemble Approach for Short-Term Load Forecasting for DISCOMS of Delhi Across the COVID-19 Scenario

Abstract

The Covid-19 has presented unforeseen challenges to the world that has never been experienced before in history. None of the sectors remained unaffected & witnessed various changes in their day-to-day operations. The impact has also been observed in the power sector, which can easily be illustrated with load fluctuations. The balancing of load & supply in the energy sector is itself one of the critical & complex tasks which becomes more vulnerable to deviation in case of these unforeseen events. Despite using advanced systems like machine learning & artificial intelligence for load forecasting, utilities found the task challenging. This paper covers the impact of lockdown on load patterns of the Discoms of Delhi in the year 2020–21. The effect of weather on load is also analysed to demonstrate the critical correlation between them. The performance of the ensemble technique that has been proven beneficial for better load forecasting & has outperformed other existing models, even in the current pandemic situation, has also been analysed & validated through a comparative analysis against popular benchmark models.