Power Efficiency Optimization in a Nanogrid Using a Nash Bargaining-Based Power Management Strategy

This paper presents a cooperative power management strategy for nanogrids using the Nash Bargaining Solution (NBS) to optimize energy flow between photovoltaic arrays, batteries, and loads. The approach frames the nanogrid control problem as a bargaining game that prioritizes system efficiency. Two key objectives are modeled as utility functions: maximizing the direct use of renewable energy and minimizing system losses. A simple yet effective NBS-based optimization algorithm computes hourly power setpoints, ensuring the solution lies on the Pareto-optimal front. The proposed strategy is validated through 24 -hour MATLAB/Simulink simulations, which incorporate varying solar irradiance and load demand profiles. The results demonstrate robust DC bus voltage regulation, high renewable penetration, and reduced power losses. The battery state of charge remains within healthy limits, improving its useful lifespan. Compared to traditional optimization approaches, the NBS framework enables fair and efficient resource allocation with minimal computational complexity.