Mathematical Modeling and Peak Load Optimization of a Two-Level Adaptive Energy Management System (A-EMS) Algorithm for PV-BESS Hybrid Microgrids

In the era of the global energy transition, the need for intelligent dispatch strategies arises when photovoltaic (PV) systems and battery energy storage systems (BESS) are connected. Traditional rule-based controllers (RBC) cannot consider economic signals and advanced model predictive controllers (MPC) have exponential computational complexity, hindering their adoption. This paper proposes a deterministic algorithm of a dual-objective adaptive energy management system (Dual-Objective A-EMS) to solve the energy-balancing problem under multi-tier tariff structures with complexity O(1). The algorithm adjusts its approach to maximize self-consumption and aggressively remove peak loads from the external grid dynamically. The algorithm was successfully validated by MATLAB simulations, which showed that the algorithm was able to store excess solar energy during the summer period, to fully satisfy the evening peak demand; in winter, the algorithm was able to prevent suboptimal cycling of the batteries due to the grid. Proposed logic will keep state of charge (SOC) in a safe electrochemical range of 20%–95%, which will reduce degradation of LiFePO4 cathode chemistry. Implementing the A-EMS system entirely avoids penalties for exceeding maximum power limits, and shortens the payback period of the PV-BESS system from 10-12 years (with standard RBC) to 7.5-8 years.