A PSO BASED MAXIMUM POWER POINT TRACKING ALGORITHM FOR SOLAR PHOTOVOLTAIC PANELS
Author’s Name : Muhammad Zeeshan khan | Dr Aamir Qamar | Shoaib Bhutta | Saddam Aziz| kashif Sultan
Volume 03 Issue 03 Year 2016 ISSN No: 2349-2503 Page no: 1-9
With the development of social productivity the social demand for energy is growing and energy crisis is increasing with each passing day. In renewable energy solar energy with ample storage, environmental protection and other features, it has been the most potential development energy. But photovoltaic generations exists major problems, firstly the PV Curve Shows multiple peaks curve in a partial shaded environments, traditional methods of maximum power point easy to fall into local optimum mistakes, tracking result was low in accuracy and slow in convergence, secondly because of independent photovoltaic power generation system in which the environment is very bad so the storage part state influencing factors such as illuminations, temperature they are easy to change and the P-V curve of power generation system exhibits multiple peaks which reduces the effectiveness of conventional maximum power point tracking methods This thesis research on MPPT issues the operational characteristics of PV modules are initially investigated in order to explore the impact of solar irradiation conditions on the current–voltage and power–voltage characteristics of PV modules and derive the corresponding operational requirements of a global MPPT algorithm, which is suitable for applications of PV modules.
Partial Shadow Condition (PSC), PSO (particle Swarm optimization, Photovoltaic (PV) Maximum Power point tracking (MPPT).Power generation system (PGS), GMPP Global maximum Power Point Tracking.
- “Sunny Family 2010/2011 – The Future of Solar Technology”, SMA product catalogue,2010.http://download.sma.de/smaprosa/dateien/2485/SOLARKATKUS103936W.
- L. Piegari, R. Rizzo, “Adaptive perturb and observe algorithm for photovoltaic maximum Power point tracking,” Renewable Power Generation, IET, vol. 4, no. 4, pp. 317-328, July 2010.
- D. C. Jones and R. W. Erickson, “Probabilistic analysis of a generalized perturb and observe algorithm featuring robust operation in the presence of power curve traps,” IEEE Trans. Power Electron., vol. 28, no. 6, pp. 2912– 2926, Jun. 2013.
- K. Kobayashi, I. Takano, and Y. Sawada, “A study of a two stage maximum power point tracking control of a photovoltaic system under partially shaded insolation conditions,” Sol. Energy Mater. Sol. Cells, vol. 90, no. 18–19, pp. 2975–2988, Nov. 2006.
- H. Patel and V. Agarwal, “Maximum power point tracking scheme for PV systems operating under partially shaded conditions,” IEEE Trans. Ind. Electron., vol. 55, no. 4, pp. 1689–1698, Apr. 2008.
- L. Gao, R. A. Dougal, S. Liu, and A. P. Iotova, “Parallel-connected solar PV system to address partial and rapidly fluctuating shadow conditions,” IEEE Trans. Ind. Electron., vol. 56, no. 5, pp. 1548–1556, May 2009.
- M. Miyatake, M. Veerachary, F. Toriumi, N. Fujii, and H. KO, “Maximum power point tracking of multiple photovoltaic arrays: A PSO approach.
- K. Ishaque, Z. Salam, M. Amjad, and S. Mekhilef, “An improved particle swarm optimization (PSO)-based MPPT for PV with reduced steady-state oscillation,” IEEE Trans. Power Electron., vol. 27, no. 8, pp. 3627–3638, Aug. 2012
- R. Eberhart and J. Kennedy, “A new optimizer using particle swarm theory,” in Proc. 6th Int. Symp. Micro Mach. Human Sci., 1995, pp. 39–43.
- K. E. Parsopoulos and M. N. Vrahatis, Particle Swarm Optimization and Intelligence: Advances and Applications. Hershey, PA: IGI Global, 2010.
- H. Patel and V. Agarwal, “MATLAB-based modeling to study the effects of partial shading on PV array characteristics,” IEEE Trans. Energy Converters., vol. 23, no. 1, pp. 302–310, Mar. 2008