Abstract
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.
Highlights
Due to the random change of load in a power system, electrical energy varies continuously
This is defined as the Load Frequency Control (LFC) or Automatic Generation Control (AGC), which plays an important role in power system operation and control
The response results of the system are compared with the Genetic Algorithm tuned PI (GA-PI) [16], Bacterial Foraging Optimization Algorithm tuned PI (BFOA PI) [16], BFOA-PSO optimized PI controller [17], fuzzy PI controller [18], and Fractional PID (FPID) [19]
Summary
Due to the random change of load in a power system, electrical energy varies continuously. The LFC strategy aims to continuously monitor the system frequency and the tie-line power It calculates net changes of these two parameters from their nominal values, which is known as Area Control Error (ACE), in order to control the valve settings of prime movers with a goal of forcing ACE signals to acceptable values. In [1], the authors designed a fuzzy-PI controller to control the load frequency for a six-area power system with non-reheat turbines. In [4], a fuzzy controller was proposed to find the optimal parameters for the PID frequency controller of a three-area power system. In order to stabilize the frequency in an interconnected power system, many problems arising in the system affect its control quality These include devices with nonlinear system components such as: GDB (Governor Dead Band), GRC (Generation Rate Constraint), time delay in the system, changes of parameters of electrical equipment, and varying operating loading conditions. The response results of the system are compared with the Genetic Algorithm tuned PI (GA-PI) [16], Bacterial Foraging Optimization Algorithm tuned PI (BFOA PI) [16], BFOA-PSO optimized PI controller [17], fuzzy PI controller [18], and Fractional PID (FPID) [19]
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