Intelligent photovoltaic farms for robust frequency stabilization in multi-area interconnected power system based on PSO-based optimal Sugeno fuzzy logic control

•We apply the PV farms to stabilize the system frequency fluctuation.•We design the PV controller by optimal Sugeno fuzzy control.•The Sugeno fuzzy controller is tuned by particle swarm optimization.•The control effect of the proposed optimal fuzzy control is confirmed.

Currently, the grid-connected large PV farms are extensively installed in power systems. Nevertheless, in addition to the load change, the intermittent power output of PV farms may lead to the serious problem of the system frequency fluctuation. To handle this problem, this paper proposes a new design of Sugeno fuzzy logic controller based on particle swarm optimization (PSO-SFLC) of intelligent PV farms for the frequency stabilization in a multi-area interconnected power system. To handle various scenarios, the frequency deviations and solar insolations are used as input signals of the PSO-SFLC. The output signal of the PSO-SFLC is a command signal for adjusting PV output power. The output power of PV is controlled by the PSO-SFLC to meet the load demand so that the system frequency fluctuation can be suppressed. Without the difficulty of trial and error, the optimal input and output membership functions, and control rules of PSO-SFLC are automatically achieved by PSO. Simulation study in a three-area loop interconnected power system with large PV farms elucidates that the frequency stabilizing performance and robustness of the PV equipped with the PSO-SFLC is much superior to that of the PV with the SFLC and the PV with the maximum power point tracking control in scenarios with various solar insolations and loading conditions.