An Intelligent Energy Management System for Cost Optimization and Peak Demand Reduction Using Battery-Integrated Smart Dispatch

The increasing penetration of distributed energy resources (DERs), electric vehicles (EVs), and battery energy storage systems (BESS) has introduced new challenges in managing energy costs, demand charges, and grid reliability. Traditional rule-based energy management systems often fail to adapt dynamically to real-time price signals, peak demand events, and operational constraints. This paper presents an intelligent Energy Management System (EMS) prototype that integrates real-time monitoring, predictive analytics, and optimized dispatch planning to reduce operational energy costs and peak demand. The proposed system is demonstrated through a multi-scenario prototype including commercial buildings, EV depots, and residential solar-plus-storage environments. Results from the prototype evaluation show significant reductions in peak demand, improved self-consumption of renewable energy, and measurable cost savings, validating the effectiveness of the proposed approach.