A novel PSO strategy for improving dynamic change partial shading photovoltaic maximum power point tracker

ABSTRACT

Photovoltaic (PV) energy systems are very important electric generation sources in modern power systems. The generated power from the PV array is a function in its terminal voltage. Tracking the maximum power needs a DC/DC converter to control the PV array terminal voltage. The boost converter is used in this paper for this purpose. Due to the multiple peaks in the power versus voltage (P-V) characteristics of PV array a smart optimization technique is required to work as a maximum power point tracker (MPPT). The particle swarm optimization (PSO) is a superior technique to track the global peak (GP) and avoid getting trapped in one of the local peaks (LPs). Despite the superiority of PSO, it suffers from some shortcomings in the application of MPPT of PV systems such as its sluggishness convergence, its inability to catch the new GP in case of acute change in shading pattern, and the possibility of getting trapped in one of the LPs. All these shortcomings are solved in this paper using a new adaptive PSO (NA-PSO) strategy. This new strategy solved these problems by starting the duty ratio at an equal distance between each other and force the particles with lower generated power to work around the one with the highest generated power. This newly proposed technique reduced the convergence time by 50% and reduced the failure rate to zero. Also, the generated energy is increased by 10.4% compared to the conventional PSO. The results collected from the NA-PSO strategy show its superiority in reducing the convergence time and failure rate and increasing the generated power, and the system efficiency, especially in the dynamic variation of the shading pattern compared to the conventional PSO.

KEYWORDS:

• Global peak
• initialization
• MPPT
• partial shading
• particle swarm optimization
• photovoltaic

Acknowledgments

The authors extend their appreciation to the Deanship of Scientific Research at King Saud University, Riyadh, Saudi Arabia for funding this work through research group No (RG-1439-66).

Nomenclatures

Symbol	=	Discretions
i	=	Is a counter number to represent iteration of the PSO
it	=	Total iteration number
PG(i)	=	The global peak at the iteration i
ε	=	The predefined tolerance to reinitialize the particles
d	=	The duty ratio of boost converter
VDC	=	DC link voltage
VPV	=	Terminal voltage of PV array
IPV	=	PV output current
ω	=	The inertia weight
cl	=	The self-experience parameter
cg	=	The ocial experience parameter
SS	=	The swarm-size
k	=	Is a counter number to represent particle number
${v_i}^k$	=	Velocity of particle k in iteration i
${d_i}^k$	=	Position of particle k in iteration i
${P_i}^k$	=	Value of particle k in iteration i
G	=	The global best position
	=	Particle k best position
$P_{best}^k$	=	Particle k best value
rl and rg	=	Random values in between [0 1],
VOC	=	The open circuit voltage of the PV module in V
ISC	=	The short circuit current of the PV module in A
VMPP	=	The voltage at maximum power point of PV module in V
Pmax	=	The rated maximum power of each module in W
t	=	The simulation time in s

Additional information

Funding

This work was supported by the Deanship of Scientific Research at King Saud University, Riyadh, Saudi Arabia for funding this work through research group No (RG-1439-66).

Notes on contributors

Ali M. Eltamaly

Ali M. Eltamaly (Ph.D. - 2000) is a full professor at King Saud University, Saudi Arabia, and Mansoura University, Egypt. He received the B.Sc (Hons), and M.Sc. degrees in electrical engineering from Al-Minia University, Egypt in 1992 and 1996, respectively. He received his Ph.D. Degree in Electrical Engineering from Texas A&M University in 2000. His current research interests include renewable energy, smart grid, power electronics, motor drives, power quality, artificial intelligence, evolutionary and heuristic optimization techniques, and distributed generation. He published more than 20 books and book chapters and he has authored or co-authored more than 200 refereed journal and conference papers. He published a number of patents in the USA patent office. He has supervised a number of M.S. and Ph.D. theses in many universities in different countries, worked on a number of National/International technical projects. He got distinguish professor award for scientific excellence, Egyptian supreme council of Universities, Egypt, June 2017 and he has awarded many prizes in different universities in Egypt and Saudi Arabia. He is participating as an editor and associate editors in many international journals and chaired many international conferences’ sessions. He is chair professor of Saudi Electricity Company Chair in Power System Reliability and Security, King Saud University, Riyadh, Saudi Arabia. He chaired the Committee for Electrical Engineering Professional Exam for the Kingdom of Saudi Arabia, 2020.

Hassan M. H. Farh

Hassan M. H. Farh was born in Egypt, on January 25, 1984. He received his B.S. (with very good with honor Degree) and M.Sc., in 2006 and 2013 from Zagazig and King Saud University; respectively. He works as a researcher and teaches many electrical courses in Electrical Engineering Department, College of Engineering, King Saud University, Saudi Arabia from Aug. 2015 till now.These Electrical Courses includes Power electronics, Electric drives, Electrical circuits and Lab., Power system operation and control, Electrical machines, Power system protection, Numerical methods in Electrical Engineering. Whereas, he worked from Apr. 2013 to Aug. 2015 as a Research Assistant in College of Engineering Research Center, King Saud University, Riyadh, Saudi Arabia. From Feb. 2009 to Apr. 2013, he worked as Teaching Assistant in Electrical Engineering Department, College of Engineering; King Saud University in Riyadh, Saudi Arabia. His current research interests focused on renewable energy (wind and solar photovoltaic), distributed generation, power quality, power electronics, and smart control technologies (artificial intelligence and metaheuristic optimization techniques). He published more than 20 papers in a high impact journals and International Conferences papers. In addition, he authored and coauthored many book chapters. Also, He has reviewed many papers for many refereed journals in these interest areas.He worked in many technical projects and researches related to electrical power quality and renewable energy applications. Award-winning of Excellence in Scientific Research, college of Engineering, King Saud University in 2013.

Ahmed G. Abokhalil

A. G. Abokhalil received the Bachelor and Master of Science in An engineering degree from Assiut University, Egypt, and the Ph.D. degree from the School of Electrical and Computer Engineering, yeungnam University, South Korea, in 2007. In 2008, He joined Rensselaer Polytechnic Institute, NY, USA, as a Postdoc researcher and I worked on a renewable energy project. From 2009 to 2010, he was a Postdoctoral Research Fellow in the Korean Institute of Energy Research, Daejeon, South Korea, working on Photovoltaic power conversion systems. In 2010, I moved to Assiut University, Egypt, as an assistant professor. He works now as an associate professor with the Department of Electrical Engineering, Majmaah University, Almajmaah, Kingdom of Saudi Arabia.