This study focuses on designing an effective intelligent control method to stabilize the net frequency against load variations in multi-control-area interconnected power systems. Conventional controllers (e.g. Integral, PI, and PID) achieve only poor control performance with high overshoots and long settling times. They could be replaced with intelligent regulators that can update controller parameters for better control quality. The control strategy is based on fuzzy logic, which is one of the most effective intelligent strategies and can be a perfect substitute for such conventional controllers when dealing with network frequency stability problems. This paper proposes a kind of fuzzy logic controller based on the PID principle with a 49-rule set suitable to completely solve the problem of load frequency control in a two-area thermal power system. Such a novel PID-like fuzzy logic controller with modified scaling factors can be applied in various practical scenarios of an interconnected power system, namely varying load change conditions, changing system parameters in the range of ±50%, and considering Governor Dead-Band (GDB) along with Generation Rate Constraint (GRC) nonlinearities and time delay. Through the simulation results implemented in Matlab/Simulink software, this study demonstrates the effectiveness and feasibility of the proposed fuzzy logic controller over several counterparts in dealing with the load-frequency control of a practical interconnected power system considering the aforesaid conditions.

Modern era power systems may include not only traditional primary energy sources like hydro or thermal energy, but also a variety of Renewable Energy (RE) sources such as solar and/or wind power. This leads to the complexity of the electrical networks related to their design and construction as well as system stability and control issues. Considered to be one of the most crucial control issues, Load Frequency Control (LFC), must be continuously improved in order to ensure the control goals. For an interconnected power system, the control purposes are to maintain the net frequency at nominal value, e.g. 50 or 60Hz as well as to ensure that tie-line power flows are stable at scheduled values. This work proposes a novel LFC strategy applying Particle Swarm Optimization (PSO) ~ PID – like fuzzy logic–based controllers. PSO is one of the most effective optimization techniques. It is used to optimally determine four scaling factors for each LFC proposed in this study. A three-area power network consisting of a hydraulic station, a non-reheat plant, and a reheat unit along with RE sources such as wind and solar power are taken into consideration. The control performance of the proposed control strategy is compared to those of existing controllers, i.e. Genetic Algorithm (GA), Bacteria Foraging Optimization Algorithm (BFOA), Fractional Order-PID (FPID), and fuzzy logic-based PI controllers for the same interconnected power grid model with various case studies of load changes along with nonlinearities and different RE source conditions. Simulation results implemented in MATLAB/Simulink demonstrate the feasibility and applicability of the proposed control strategy.

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In this paper, we deal with the problem of how to achieve stability for a complex system in which the subsystems are stable, but the non-linear interaction between the subsystems may cause instability. We assume that the uncertainties with which we know the parameters of the system are bounded, but that these bounds are not known. For such systems, we propose a new control method: a decentralized robust control with fuzzy estimation of the bounds of uncertainties, implemented as a combination of conventional and fuzzy controllers. The use of fuzzy control is motivated by the equivalent dynamic fuzzy state-space model of the system consisting of interconnected uncertain subsystems.