Chinese Journal of Electrical Engineering ›› 2022, Vol. 8 ›› Issue (4): 79-90.doi: 10.23919/CJEE.2022.000040

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Robust Iteration-dependent Least Mean Square-based Distribution Static Compensator Using Optimized PI Gains*

Sabha Raj Arya*, Rakesh Maurya, Jayadeep Srikakolapu   

  1. Department of Electrical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat 395007, India
  • Received:2021-03-30 Revised:2021-05-30 Accepted:2021-08-11 Online:2022-12-25 Published:2023-01-13
  • Contact: * E-mail: sabharaj79@gmail.com
  • About author:Sabha Raj Arya (M'12-SM'15) received Bachelor of Engineering degree in Electrical Engineering from Government Engineering College Jabalpur, in 2002, Master of Technology in Power Electronics from Motilal National Institute of Technology, Allahabad, in 2004 and Ph.D. degree in Electrical Engineering from Indian Institute of Technology (I.I.T) Delhi, New Delhi, India, in 2014. He is joined as Assistant Professor, Department of Electrical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat. On January 2019, he was promoted as Associate Professor in same institute. His fields of interest include power electronics, power quality, design of power filters and distributed power generation.
    He received two national awards namely INAE Young Engineer Award from Indian National Academy of Engineering, POSOCO Power System Award from Power Grid Corporation of India in the year of 2014 for his research work. He also received Amit Garg Memorial Research Award-2014 for I.I.T Delhi for the high impact publication in a quality journal during the session 2013-2014. At present, he has published more than hundred research papers in internal national journals and conferences in field of electrical power quality.
    He also serves as an Associate Editor for the IET (UK) Renewable Power Generation.
    Rakesh Maurya (M'16) received B.Tech. in Electrical Engineering from the Kamla Nehru Institute of Technology Sultanpur, Uttar Pradesh in 1998 and M.Tech. and Ph.D. in Electrical Engineering from Indian Institute of Technology Roorkee, India, in 2002 and 2014 respectively. Presently, he is serving as faculty member in the Department of Electrical Engineering, Sardar Vallabhbhai National Institute of Technology Surat, Gujarat, India. His fields of interest include design of switching power converters, high power factor AC/DC converters, hybrid output converter, power quality problems, advanced electric drives and applications of real time simulator for the control of power converters.
    Jayadeep Srikakolapu received the Bachelor of Technology (Electrical and Electronics) degree from JNTU, Kakinada, India, in 2010 and M.Tech. degree in Electrical Engineering with specialization in Power Electronics from SGSITS, Indore, India, in 2013. In January 2014, he joined the Department of Electrical Engineering, BVC Engineering College, Odalarevu, India, as an Assistant Professor. Since January 2018, he is doing Ph.D. program in Electrical Engineering Department from Sardar Vallabhbhai National Institute of Technology Surat, India. His research areas include power electronics, power quality and design of custom power devices and wind energy conversion systems.
  • Supported by:
    * Science and Engineering Research Board -New Delhi Project (Extra Mural Research Funding Scheme), Grant No.SB/S3/EECE/030/2016.

Abstract: A robust iteration-dependent least mean square (RIDLMS) algorithm-based fundamental extractor is developed to estimate the fundamental components of the load current for a four-wire DSTATCOM with a nonlinear load. The averaging parameter for calculating the variable step size is iteration dependent and uses variable tuning parameters. Rather than using the current value, the previous learning rate was used in this method to achieve a more adaptive solution. This additional control factor aids in determining the exact learning rate, resulting in reliable and convergent outcomes. Its faster convergence rate and the avoidance of local minima make it advantageous. The estimation of the PI controller gains is achieved through a self-adaptive multi-population algorithm. The adaptive change in the group number will increase exploration and exploitation. The self-adaptive nature of the algorithm was used to determine the subpopulation number needed according to the fitness value. The main advantage of this self-adaptive nature is the multi-population spread throughout the search space for a better optimal solution. The estimated gains of the PI controllers are used for the DC bus and AC terminal voltage error minimization. The RIDLMS-based control with PI gains obtained using the proposed optimization algorithm showed better power quality performance. The considered RIDLMS-supported control was demonstrated experimentally using d-SPACE-1104.

Key words: Least mean square, variable learning, DSTATCOM, local minima, Rao algorithm, reactive power, neutral current