Intelligent frequency control using optimal tuning and demand response in an AC microgrid

Future smart microgrids need increased flexibility and intelligence in control and optimization to maintain a generation-load balance. This concern becomes more significant today because of lack of conventional Automatic Generation Control (AGC) nd spinning reserves which introduce new issues for providing ancillary services. Moreover, due to increasing renewable energy penetration in power systems, conventional controllers may be unable to maintain the system stability. In response to this issue, this paper presents an intelligent control algorithm using fuzzy logic and particle swarm optimization (PSO). Furthermore, the effect of Demand Response (DR) in continuously balancing generation and demand, when the output from wind and photovoltaic (PV) varies naturally, is proposed. Simulation results are examined on an islanded microgrid case study. The performance of the proposed controller is compared with conventional control design and the effect of DR in fast power compensation is proved.