As global energy demand escalates due to the proliferation of electric vehicles and smart infrastructure, the necessity for optimal grid scheduling becomes paramount. The stochastic nature of electricity consumption complicates the synchronization of generation and demand. This paper proposes a four-step predictive framework comprising data collection, feature extraction, characteristic analysis, and final application to improve power generation utilization. Accurate load forecasting is established as the primary mechanism for ensuring safe, reliable, and cost-effective grid operations.