Abstract
This study develops and implements a design of the Fuzzy Proportional Integral Derivative with filtered derivative mode (Fuzzy PIDF) for Load Frequency Control (LFC) of a two-area interconnected power system. To attain the optimal values of the proposed structure’s parameters which guarantee the best possible performance, the Bees Algorithm (BA) and other optimisation tools are used to accomplish this task. A Step Load Perturbation (SLP) of 0.2 pu is applied in area one to examine the dynamic performance of the system with the proposed controller employed as the LFC system. The supremacy of Fuzzy PIDF is proven by comparing the results with those of previous studies for the same power system. As the designed controller is required to provide reliable performance, this study is further extended to propose three different fuzzy control configurations that offer higher reliability, namely Fuzzy Cascade PI − PD, Fuzzy PI plus Fuzzy PD, and Fuzzy (PI + PD), optimized by the BA for the LFC for the same dual-area power system. Moreover, an extensive examination of the robustness of these structures towards the parametric uncertainties of the investigated power system, considering thirteen cases, is carried out. The simulation results indicate that the contribution of the BA tuned the proposed fuzzy control structures in alleviating the overshoot, undershoot, and the settling time of the frequency in both areas and the tie-line power oscillations. Based on the obtained results, it is revealed that the lowest drop of the frequency in area one is −0.0414 Hz, which is achieved by the proposed Fuzzy PIDF tuned by the BA. It is also divulged that the proposed techniques, as was evidenced by their performance, offer a good transient response, a considerable capability for disturbance rejection, and an insensitivity towards the parametric uncertainty of the controlled system.
Highlights
Modern large power systems normally comprise multiple interconnected control areas that are based on diverse energy resources
Learning Based Optimisation (TLBO), and Particle Swarm Optimisation (PSO) codes were programmed in (.m files); the examined dual-area power system was built in the MATLAB
The dynamic performance of the system based on the Fuzzy PIDF tuned by the suggested algorithms, the Fuzzy PID optimized by teaching learning based optimization (TLBO), and the PID controller tuned by Lozi map-based Chaotic Optimization Algorithm (LCOA), represented by undershoot, peak overshoot, and settling time in ∆F1, ∆F2, and ∆Ptie, is illustrated in Table 6; the value of the objective function based on each technique is given
Summary
Modern large power systems normally comprise multiple interconnected control areas that are based on diverse energy resources. An optimized fuzzy self-tuning PID controller is proposed for the LFC in two- and three-area interconnected power systems [20]. In view of the above, this work proposes a design of a Fuzzy PID with a derivative filter action (Fuzzy PIDF) employed for the LFC in an unequal two-area interconnected thermal power system. Energies 2022, 15, 657 paper can be summarized as follows: (i) to propose a Fuzzy PIDF optimized by the BA and other two algorithms for load frequency control of a two-area power system and to investigate its dynamic performance; (ii) to assess the supremacy of the proposed technique by comparing the results with those of previously published works based on TLBO tuned Fuzzy PID [21] and Lozi map-based Chaotic Optimization Algorithm (LCOA).
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
