Efficient Photovoltaic System Maximum Power Point Tracking Using a New Technique

Mehdi Seyedmahmoudian, Ben Horan, Rasoul Rahmani, Aman Maung Than Oo and Alex Stojcevski
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Mehdi Seyedmahmoudian: School of Engineering, Deakin University, Waurn Ponds, VIC 3216, Australia
Ben Horan: School of Engineering, Deakin University, Waurn Ponds, VIC 3216, Australia
Rasoul Rahmani: School of Software and Electrical Engineering, Swinburne University of Technology, Hawthorn, VIC 3122, Australia
Aman Maung Than Oo: School of Engineering, Deakin University, Waurn Ponds, VIC 3216, Australia
Alex Stojcevski: Centre of Technology, RMIT University, Ho Chi Minh 70000, Vietnam

Energies, 2016, vol. 9, issue 3, 1-18

Abstract: Partial shading is an unavoidable condition which significantly reduces the efficiency and stability of a photovoltaic (PV) system. When partial shading occurs the system has multiple-peak output power characteristics. In order to track the global maximum power point (GMPP) within an appropriate period a reliable technique is required. Conventional techniques such as hill climbing and perturbation and observation (P&O) are inadequate in tracking the GMPP subject to this condition resulting in a dramatic reduction in the efficiency of the PV system. Recent artificial intelligence methods have been proposed, however they have a higher computational cost, slower processing time and increased oscillations which results in further instability at the output of the PV system. This paper proposes a fast and efficient technique based on Radial Movement Optimization (RMO) for detecting the GMPP under partial shading conditions. The paper begins with a brief description of the behavior of PV systems under partial shading conditions followed by the introduction of the new RMO-based technique for GMPP tracking. Finally, results are presented to demonstration the performance of the proposed technique under different partial shading conditions. The results are compared with those of the PSO method, one of the most widely used methods in the literature. Four factors, namely convergence speed, efficiency (power loss reduction), stability (oscillation reduction) and computational cost, are considered in the comparison with the PSO technique.

Keywords: photovoltaic systems; maximum power point tracking; partial shading conditions; soft computing methods; energy efficiency; stability; computational cost (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: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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