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GAJENDRA SINGH CHAWDA (PhD, IITJ, India) was born in Mandsaur, India, in 1986. He received the Diploma degree in electrical engineering from the Government Polytechnic College, Jaora, India, in 2004, the B.E. degree in electrical and electronics engineering from Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India, in 2008, and the M.Tech. degree in electrical power system from NIT Kurukshetra, Haryana, India, in 2013. He is currently pursuing the PhD degree with the Department of Electrical Engineering, IIT Jodhpur, India. His research interests include power electronics, power quality, custom power devices, renewable energy systems, and smart grid control.
In practical operating conditions, the Solar-Photo Voltaic (SPV) system experiences multifarious irradiation and temperature levels, which generate power with multiple peaks. This is considered as the nonuniform operating condition (NUOC). This requires accurate tracking of global power peaks to achieve maximum power from SPV, which is a challenging task. Hence, this paper presents an incremental Conductance based Particle Swarm Optimization (ICPSO) algorithm for accurate tracking of maximum global power from active power multiple peaks generated by the SPV. The proposed algorithm continuously adjusts the individual particle’s weight component, which depends on its distance from the global best position during the tracking process. The proposed algorithm has the merit of continuous adjustment of weight components which reduces active power oscillations at the optimal global position area. Proposed ICPSO algorithm has been successfully designed and implemented for Solar-photo voltaic (PV) under nonuniform operating condition. It is established that the proposed algorithm enhances the output power of the Solar-PV up to 7% with the maximum power tracking of 0.1 s compared to other maximum power point tracking algorithms.
Gajendra Singh Chawda; Om Prakash Mahela; Neeraj Gupta; Mahdi Khosravy; Tomonobu Senjyu. Incremental Conductance Based Particle Swarm Optimization Algorithm for Global Maximum Power Tracking of Solar-PV under Nonuniform Operating Conditions. Applied Sciences 2020, 10, 4575 .
AMA StyleGajendra Singh Chawda, Om Prakash Mahela, Neeraj Gupta, Mahdi Khosravy, Tomonobu Senjyu. Incremental Conductance Based Particle Swarm Optimization Algorithm for Global Maximum Power Tracking of Solar-PV under Nonuniform Operating Conditions. Applied Sciences. 2020; 10 (13):4575.
Chicago/Turabian StyleGajendra Singh Chawda; Om Prakash Mahela; Neeraj Gupta; Mahdi Khosravy; Tomonobu Senjyu. 2020. "Incremental Conductance Based Particle Swarm Optimization Algorithm for Global Maximum Power Tracking of Solar-PV under Nonuniform Operating Conditions." Applied Sciences 10, no. 13: 4575.
Rapid industrialization and its automation on the globe demands increased generation of electrical energy with more reliability and quality. Renewable energy (RE) sources are considered as a green form of energy and extensively used as an alternative source of energy for conventional energy sources to meet the increased demand for electrical power. However, these sources, when integrated to the utility grid, pose challenges in maintaining the power quality (PQ) and stability of the power system network. This is due to the unpredictable and variable nature of generation by these sources. The distributed flexible AC transmission system (DFACTS) devices such as distributed static compensator (DSTATCOM) and dynamic voltage restorer (DVR) play an active role in mitigating PQ issues associated with RE penetration. The performance of DFACTS devices is mostly dependent on the type of control algorithms employed for switching of these devices. This paper presents a comprehensive review of various conventional and adaptive algorithms used to control DFACTS devices for improvement of power quality in utility grids with RE penetration. This review intends to provide a summary of the design, experimental hardware, performance and feasibility aspects of these algorithms reported in the literature. More than 170 research publications are critically reviewed, classified, and listed for quick reference for the advantage of engineers and academician working in this area.
Gajendra Singh Chawda; Abdul Gafoor Shaik; Om Prakash Mahela; Sanjeevikumar Padmanaban; Jens Bo Holm-Nielsen. Comprehensive Review of Distributed FACTS Control Algorithms for Power Quality Enhancement in Utility Grid With Renewable Energy Penetration. IEEE Access 2020, 8, 107614 -107634.
AMA StyleGajendra Singh Chawda, Abdul Gafoor Shaik, Om Prakash Mahela, Sanjeevikumar Padmanaban, Jens Bo Holm-Nielsen. Comprehensive Review of Distributed FACTS Control Algorithms for Power Quality Enhancement in Utility Grid With Renewable Energy Penetration. IEEE Access. 2020; 8 ():107614-107634.
Chicago/Turabian StyleGajendra Singh Chawda; Abdul Gafoor Shaik; Om Prakash Mahela; Sanjeevikumar Padmanaban; Jens Bo Holm-Nielsen. 2020. "Comprehensive Review of Distributed FACTS Control Algorithms for Power Quality Enhancement in Utility Grid With Renewable Energy Penetration." IEEE Access 8, no. : 107614-107634.