Implementation of an ADALINE-Based Adaptive Control Strategy for an LCLC-PV-DSTATCOM in Distribution System for Power Quality Improvement

Soumya Mishra, Sreejith Rajashekaran, Pavan Kalyan Mohan, Spoorthi Mathad Lokesh, Hemalatha Jyothinagaravaishya Ganiga, Santanu Kumar Dash () and Michele Roccotelli ()
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Soumya Mishra: Department of Electrical Engineering, MVJ College of Engineering, Bengaluru 560067, India
Sreejith Rajashekaran: Department of Electrical Engineering, MVJ College of Engineering, Bengaluru 560067, India
Pavan Kalyan Mohan: Department of Electrical Engineering, MVJ College of Engineering, Bengaluru 560067, India
Spoorthi Mathad Lokesh: Department of Electrical Engineering, MVJ College of Engineering, Bengaluru 560067, India
Hemalatha Jyothinagaravaishya Ganiga: Department of Electrical Engineering, MVJ College of Engineering, Bengaluru 560067, India
Santanu Kumar Dash: TIFAC-CORE, Vellore Institute of Technology, Vellore 632014, India
Michele Roccotelli: Department of Electrical and Information Engineering (DEI), Politecnico di Bari, Via Orabona, 4, 70125 Bari, Italy

Energies, 2022, vol. 16, issue 1, 1-22

Abstract: This study investigated the problem of controlling a three-phase three-wire photovoltaic (PV)-type distribution static compensator (DSTATCOM). In order to model, simulate, and control the system, the MATLAB/SIMULINK tool was used. Different controllers were applied to create switching pulses for the IGBT-based voltage source converter (VSC) for the mitigation of various power quality issues in the PV-DSTATCOM. Traditional control algorithms guarantee faultless execution or outcomes only for a restricted range of operating situations due to their present design. Alternative regulators depend on more resilient neural network and fuzzy logic algorithms that may be programmed to operate in a variety of settings. In this study, an adaptive linear neural network (ADALINE) was proposed to solve the control problem more efficiently than the existing methods. The ADALINE method was simulated and the results were compared with the results of the synchronous reference frame theory (SRFT), improved linear sinusoidal tracer (ILST), and backpropagation (BP) algorithms. The simulation results showed that the proposed ADALINE method outperformed the compared algorithms. In addition, the total harmonic distortions (THDs) of the source current were estimated under ideal grid voltage conditions based on IEEE-929 and IEEE-519 guidelines.

Keywords: ADALINE; BP; DSTATCOM; harmonics; ILST; load-balancing; photovoltaic; reactive power; shunt active filter; SRFT (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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