Proceedings of the First International Conference on Computing, Communication and Control System, I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India

Research Article

Novel Control Method on Unified Power Quality Conditioner (UPQC) for Harmonic Distribution Using PSO-Fuzzy Logic

Download167 downloads
  • @INPROCEEDINGS{10.4108/eai.7-6-2021.2308773,
        author={Y. Mallikharjuna Rao and B Sarath Chandra and Dr.N.C.  Kotaiah},
        title={Novel Control Method on Unified Power Quality Conditioner (UPQC) for Harmonic Distribution Using PSO-Fuzzy Logic},
        proceedings={Proceedings of the First International Conference on Computing, Communication and Control System, I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India},
        publisher={EAI},
        proceedings_a={I3CAC},
        year={2021},
        month={6},
        keywords={unified power quality conditioner (upqc); optimal volt-ampere (va) rating/loading; displacement angle control (dac); reactive power sharing; voltage leak and swell},
        doi={10.4108/eai.7-6-2021.2308773}
    }
    
  • Y. Mallikharjuna Rao
    B Sarath Chandra
    Dr.N.C. Kotaiah
    Year: 2021
    Novel Control Method on Unified Power Quality Conditioner (UPQC) for Harmonic Distribution Using PSO-Fuzzy Logic
    I3CAC
    EAI
    DOI: 10.4108/eai.7-6-2021.2308773
Y. Mallikharjuna Rao1,*, B Sarath Chandra1, Dr.N.C. Kotaiah2
  • 1: Assistant Professor, Department of EEE, RVR & JC College of Engineering, Guntur, A.P, India
  • 2: Professor, Department of EEE, RVR & JC College of Engineering, Guntur, A.P, India
*Contact email: ymallieee@gmail.com

Abstract

In this paper novel control method on unified power quality improvement for harmonic distribution using PSO-Fuzzy logic is implemented. There are various types of compensators such as parallel power quality compensator and series power quality compensatorwhichimproves the power quality. In this proposed work, control algorithm is developed on unified power quality conditioner. The entire algorithm is divided into three stages, in stage -1 all the parameters will be initialized and in stage-2 process computing the upper and lower boundary’s of X and Y is done. At last in stage-3 the process of commuting value of z is done and output is obtained. The simulation results show that fuzzy controller based particle swarm optimization will improve the accuracy, effectiveness and superiority.