Anfis-fuzzy logic based UPQC in interconnected microgrid distribution systems: Modelling, simulation and implementation

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Renduchintala, Udaya Kishan
Pang, Chengzong

This study focuses on the improvement of the power quality in interconnected power distribution systems using connected microgrids. The power quality issues at the secondary distribution level are addressed using a unified power quality conditioner (UPQC), which aids in controlling voltage imbalances and current harmonics. Further, a power control method, adaptive neuro-fuzzy inference system (ANFIS), is proposed as a global solution by installing independent compensating devices at the point of common coupling. The proposed strategy can improve the power quality in traditional installations because the proposed UPQC method maximizes power utilization and improves the efficiency of the system. The microgrids integrate renewable energy sources, which generate green energy with low loss. Case studies, a prototype, and simulations via MATLAB/Simulink are used to validate the proposed method, and the results prove the enhancement in power quality control. The proposed control strategy had a response time of 0.3 s, reduced peak voltage distortions, and restored the voltage at the interconnecting point to a normal level. The total harmonic distortion of currents decreased from 21.13% to 14.74% when a PI technique was used to control the UPQC-P, and the proposed ANFIS-based UPQC-P reduced the harmonic content to 2.43% from 21.13%.

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Thesis (Ph.D.)-- Wichita State University, College of Engineering, Dept. of Electrical Engineering & Computer Science