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