Machine Learning-Based Electricity Load Forecast for the Agriculture Sector

A large section of the population has a source income from agriculture sector, but their share in Indian GDP is low. Thus, there need to forecast energy improve and increase productivity. The main sources are electricity, coal, diesel. Among them, electricity plays an important role land irrigation. Power forecasting also essential for demand response management. any process that dissolves future consumption favorable. This article presents time series-based technique medium-term load agriculture. aim find peak periods power by months seasons using statistical machine learning-based techniques. result shows SARIMA lower RMSE exponential smoothing RMSPE error than random forest LSTM, which makes approach more efficient intelligent historical datasets. season-wise occurs during Rabi season. Finally, five-year ahead sector was determined best models.