ADAPTIVE FUZZY-LOGIC ENERGY MANAGEMENT FOR HYBRID SOLAR–WIND MICROGRIDS: A SIMULATION-ORIENTED STUDY

Author

Hrunali I. Dhobale, Ankur R. Ramteke, Shrawani E. Gajbhe, Bhushan M. Bhagat , Prof. L.M.Bopche

Abstract

 Hybrid solar–wind microgrids can improve the availability of renewable electricity because solar photovoltaic (PV) generation and wind generation respond differently to changing weather conditions. Their output, however, is variable, and the mismatch between generation and load can cause energy shortages, unnecessary battery cycling, or renewable-energy curtailment. This paper proposes a simulation-oriented fuzzy-logic energy-management framework for a hybrid solar–wind microgrid with battery storage. The controller uses solar power, wind power, load demand, and battery state of charge (SOC) as decision inputs and determines a suitable power-allocation action. The proposed workflow includes input scaling, linguistic membership functions, an interpretable IF–THEN rule base, fuzzy inference, defuzzification, and evaluation of power balance. Unlike controllers that depend on a precise mathematical model, fuzzy logic can represent operational knowledge through understandable rules. The paper establishes a reproducible evaluation plan using MATLAB/Simulink or an equivalent simulation environment. Since the project simulation and measured outputs are not supplied in the source material, numerical performance improvements are not claimed; they are identified as quantities to be tested in future work. The framework is intended to support systematic comparison of solar-only, wind-supported, and combined solar–wind–battery operation.

Keywords

hybrid microgrid, solar photovoltaic, wind energy, fuzzy logic controller, energy management, battery state of charge, power balancing.

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References

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