MMC-based PV-Fed STATCOM with Hybrid GA-RBFNN for PQ Enhancement

Abstract

Power quality (PQ) is a consequential factor, which is highly influenced by the functioning of the transmission and distribution network. In the distribution systems, voltage swells, sags, harmonics and flickers are regarded as major power quality issues. The Static Synchronous Compensator (STATCOM) is one among the specialized power devices, which has gained considerable interest for its capacity of enhancing the performance of power systems. This paper analyses the power quality issues of a photovoltaic (PV) system adopting a STATCOM-based five-level Modular Multilevel Converter (MMC). An interleaved quadratic boost converter (QBC) is employed in this work, which escalates the PV output in a wider range. An Adaptive Neuro-Fuzzy Inference System (ANFIS) controller is employed for obtaining the fast, efficient and flexible control of the DC-DC converter. The MMC plays a crucial part in mitigating power quality issues as it has the beneficial impacts such as scalability, power quality and modularity. In this approach, a five-level MMC is implemented, which transfers active power to the load by maintaining the power factor constant. The reference current generation of MMC is carried out by a hybrid Genetic Algorithm-Radial Basis Function Neural Network (GA-RBFNN) algorithm and the pulses of MMC are generated through a hysteresis controller. It provides improved training speed and convergence along with enhanced operating efficiency of the network. The output of five-level MMC is fed to a transformer-coupled LC filter. The simulations are carried out in Matlab and a minimized Total Harmonic Distortion (THD) of 1.12% is obtained.

KEYWORDS:

• ANFIS
• Five-level MMC
• GA-RBFNN
• PCC
• PV system
• Transformer coupled LC filter
• STATCOM

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

C. Umadevi

C Umadevi received her BE degree in electrical and electronics engineering from CSI Institute of Technology, Kanyakumari, India and an ME degree in power electronics and drives from Dr. Sivanthi Aditanar College of Engineering, Tiruchendur, India, in 2014 and 2016, respectively. She has worked as assistant professor for two years and five months in the Department of Electrical and Electronics Engineering, DMI Engineering College, Kanyakumari, India and currently pursuing her PhD in electrical engineering as a regular scholar, the Government College of Engineering, Tirunelveli, Anna University, Chennai, India, since Jan 2019. Her research interests include power converters and custom power devices. Corresponding author. Email: [email protected]; [email protected]

M. Gnana Sundari

M Gnana Sundari received her BE degree in electrical and electronics engineering in 1997 and an ME degree in power electronics and drives in 2005 from Government College of Engineering, Tirunelveli, India affiliated to Anna University Chennai. She received her PhD degree from Anna University, Chennai, in 2016. She is currently a professor in the Government College of Engineering, Tirunelveli. Her research interests include intelligent control techniques, power quality monitoring and power electronic converters. She has published around 10 research articles in national and international journals. Email: [email protected]

P. Subha Karuvelam

P Subha Karuvelam received her BE in electrical and electronics degree from PSG College of Technology, Coimbatore, India in 1996 and an ME degree in power electronics and drives from GCE, Tirunelveli, India 2005. She completed PhD in electrical engineering from Anna University, Chennai, India, in 2015. She is currently professor in the Department of Electrical and Electronics Engineering at the Government College of Engineering, Tirunelveli. Her research interests are in the fields of intelligent control techniques, power quality monitoring, power electronic converters and AC drives. She has published over 20 research articles in national and international journals. Email: [email protected]