Fuzzy assisted optimal tilt control approach for LFC of renewable dominated micro-grid: A step towards grid decarbonization

Grid decarbonization is very crucial for the energy transition. The massive penetration of renewables in conventional power networks is the essential step for decarbonization but at the cost of complex control architecture. Due to the stochastic behaviour of renewables, load frequency control (LFC) is a very tedious task. This paper addresses the LFC issue in a standalone micro-grid (S-μG) via wild horse optimizer (WHO) assisted intelligent fuzzy tilt integral derivative with filter – one plus integral (FTIDF-(1 + I)) controller. The proposed S-μG consists of a solar photovoltaic (PV), wind turbine (WT) generator (WTG), and diesel engine generator (DEG) as power generating units and a flywheel as the energy storage unit (ESU). A nonlinear WTG model is used to extract the power from varying wind speeds, and a variable step size incremental conductance (V-InC) maximum power point (MPP) tracking (MPPT) technique is considered to harvest the optimal power from PV. To replicate the practical scenarios, nonlinearities of the governor, turbine, and flywheel are also considered in this work. The proposed intelligent WHO-FTIDF-(1 + I) controller can handle huge uncertainties and nonlinearities of the considered μG. FTIDF-(1 + I) controller prominence has been established over TIDF and FTIDF controllers. The effectiveness of WHO has been demonstrated over particle swarm optimization (PSO) and grey wolf optimization (GWO). From the obtained results, it is perceived that the reduction in maximum frequency deviation Δf with the proposed controller as compared to WHO-TIDF, WHO-FTIDF, PSO-FTIDF-(1 + I), and GWO-FTIDF-(1 + I) are 99.75%, 97.71%, 94.87% and 33.34% respectively. Finally, detailed robustness analysis, stability evaluation and real-power system validation via the IEEE 39 bus system of the proposed controller are also performed.