Research on Photovoltaic Array's GMPPT Technology Based on Quantum-behaved Particle Swarm Optimization Algorithm
- DOI
- 10.2991/mmebc-16.2016.229How to use a DOI?
- Keywords
- photovoltaic array, partial shade, GMPPT, QPSO algorithm.
- Abstract
On the problem of Global maximum power point tracking (GMPPT) caused by partially shaded in photovoltaic system, many scholars' search methods are always judged by their ability of static search, and dynamic performances when irradiance suddenly changes. But these methods neglect the dynamic performance when irradiance changes frequently. This article proceeded from the changes of maximum power point, which are according to the local approximate output characteristic in the process of illumination changes, analyzed the reason of the dead zone caused by the conventional optimization algorithms and combined optimization algorithm, and illustrated the necessity of the global optimization in the whole process. Then, according to the request of the whole and global optimization strategy, this article proposed a Quantum-behaved Particle Swarm Optimization (QPSO) to increase the diversity of the particles, the search velocity and convergence precision. Finally, the method was simulated by Maltab/SimScape and compared with the standard particle swarm optimization algorithm, showing the superiority of the algorithm in solving the problem of GMPPT caused by partially shaded.
- Copyright
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Lian Huang AU - Pu Wang AU - Suliang Ma AU - Mingxuan Chen AU - Jianwen Wu PY - 2016/06 DA - 2016/06 TI - Research on Photovoltaic Array's GMPPT Technology Based on Quantum-behaved Particle Swarm Optimization Algorithm BT - Proceedings of the 2016 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer PB - Atlantis Press SP - 1114 EP - 1117 SN - 2352-5401 UR - https://doi.org/10.2991/mmebc-16.2016.229 DO - 10.2991/mmebc-16.2016.229 ID - Huang2016/06 ER -