Sigmoidal Least-Absolute-Difference-based Control Approach for Standalone Wind-Solar-Battery Hybrid Microgrid

This paper presents a wind-solar PV-battery-based standalone 3-phase microgrid system employing an adaptive sigmoidal least absolute difference  control algorithm for voltage regulation, active/reactive power support, load balancing, and power-quality enhancement under intermittent operating conditions. The system integrates a SEIG-based wind-driven system, a solar PV array with incremental-conductance  MPPT technique, and a bidirectional control-based battery storage system on a common DC-link side of the voltage source converter. To address these limitations, the proposed SLAD algorithm-based controller includes a sigmoidal nonlinear mapping within the absolute-difference learning structure to improve convergence stability, reduce sensitivity to deviations, and improve estimation accuracy under disturbances, and measurement uncertainty has been implemented. Comprehensive simulation and experimental results demonstrate stable DC-link regulation, balanced 3-phase currents, effective harmonic eradication, and robust dynamic performance during load perturbation, intermittency of solar & wind. This article compares least mean square, least absolute difference, second order sequence filter and SLAD-based controllers under steady-state & load perturbation utilizing control system & PQ indices. The proposed SLAD control approach has the fastest rise time (0.03s), low overshoot (2%), and shortest settling time, showing greater dynamic performance. The results confirm that the proposed control architecture ensures reliable standalone operation & improved PQ.