Optimal Ultra-Local Model Control Integrated with Load Frequency Control of Renewable Energy Sources Based Microgrids

Since renewable energy sources (RESs) have an intermittent nature, conventional secondary frequency control, i.e., load control (LFC), cannot mitigate the effects of variations in system frequency. Thus, this paper proposes incorporating ultralocal model (ULM) into LFC to enhance microgrid (µG) stability. ULM controllers are regarded as model-free that yield high rejection rates for disturbances caused by load/RES uncertainties. Typically, parameters set using trial-and-error methods, which makes it difficult determine optimal values will provide best performance and To address issue, African vultures optimization algorithm (AVOA) was applied fine-tune parameters, thereby stabilizing despite different disturbances. The proposed controller compared with traditional based on integral prove its superior performance. For several contingencies, simulation results demonstrated coupled could significantly promote RESs µG.