Microgrid Optimization with MILP-based Demand Side Management

Abstract

The integration of renewable energy sources in microgrids introduces significant operational challenges due to their intermittent nature and the mismatch between generation and demand patterns. Effective demand response (DR) strategies are crucial for maintaining system stability and economic efficiency, particularly in microgrids with high renewable penetration. This paper presents a comprehensive mixed-integer linear programming (MILP) framework for optimizing DR operations in a microgrid with solar generation and battery storage systems. The framework incorporates load classification, dynamic price thresholding, and multi-period coordination for optimal DR event scheduling. Analysis across seven distinct operational scenarios demonstrates peak load reduction of 5–10% while achieving energy cost savings ranging from 7.5% to 24.5%. The highest performance was observed in scenarios with high solar generation, where the framework achieved 24.49% energy cost reduction through optimal coordination of renewable resources and DR actions. The results validate the framework’s effectiveness in managing diverse operational challenges while maintaining system stability and economic efficiency.