SEARCH WITHIN CONTENT
Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 2, Issue 4, Pages 661-675, DOI: https://doi.org/10.21307/ijssis-2017-374
License : (CC BY-NC-ND 4.0)
Published Online: 03-November-2017
The paper presents a Field Programmable Gate Array (FPGA) based tracker to accurately track the maximum power point (MPP) of a photovoltaic (PV) array. The tracking logic realized on FPGA is based on a modified version of Adaptive Perceptive Particle Swarm Optimization (APPSO) technique. Photovoltaic generation systems use MPP tracker because the photovoltaic array exhibits multiple maxima in the power voltage characteristic under partially shaded conditions. Compared to PSO, the APPSO offers flexibility in the motion dynamics of the particle in the search space through variation in perception radius, number of sampling points per directions, and the number of sampling directions. The APPSO algorithm has been suitably modified to suit to the slight changes in the maximum power point at around the maximum power point. The proposed technique uses only one pair of sensors to control multiple PV arrays. This results in lower cost, higher accuracy and also the algorithm is simple. The implementation of the algorithm on a reconfigurable architecture like FPGA ensures hardware based flexibility in the motion dynamics presented by APPSO. A comparative study is performed to compare the performance of PSO and APPSO with respect to MPP tracking. Compared to PSO that track to the MPP under partial shading conditions and reaches the MPP with 96.41% accuracy, the APPSO can track to the MPP with 97.95% accuracy. The algorithm when realized on an Altera Cyclone EP1C6Q240C8 FPGA consumes 5967 logic blocks.
 E. Koutroulis, K. Kalaitzakis, and N. C. Voulgaris, “Development of a microcontroller-based photovoltaic maximum power point tracking control system,” IEEE Transactions on Power Electronics, vol. 16, no. 1, pp. 46–54, Jan. 2001.
 K. H. Hussein and I. Muta, “Maximum photovoltaic power tracking: An algorithm for rapidly changing atmospheric conditions,” Proceedings of IEE Generation, Transmission and Distribution, vol. 142, no. 1, pp. 59–64, Jan. 1995.
 S. Jain and V.Agarwal, “A new algorithm for rapid tracking of approximate maximum power point in photovoltaics systems,” IEEE Power Electronics Letters, vol. 2, no. 1, pp. 16–19, Mar. 2004.
 G. Walker, “Evaluating MPPT converter topologies using a MATLAB PV model”, Journal of Electrical and Electronics Engineering, Australia, Vol. 21, No.1, pp. 16-19, Mar. 2001.
 M.C. Alonso-Gracia, J.M. Ruiz, F. Chenlo, “Experimental study of mismatch and shading effects in the I–V characteristic of a photovoltaic module”, Solar Energy Materials and Solar Cells, Vol. 90, No. 3, pp. 329-340, Feb. 2006.
 H. Kawamura, K. Naka, N. Yonekura, S. Yamanaka, H. Ohno, K. Naito, “Simulation of the I-V characteristics of a PV module with PV shaded PV cells”, Solar Energy Materials and Solar Cells, Vol. 75, No. 3-4, pp. 613-621, Feb. 2003.
 M. Shechter, J. Appelbaum and G. Yekutieli, “Quality factor of solar cell arrays”, Solar Cells, 9(1983) 295-309.
 H. Saha, G. Bhattacharya, D. Mukherjee, “Mismatch losses in series combinations of silicon solar cell modules”, Solar Cells, 25(1988) 143-153.
 T.J. Lambarski, D.L. Kadle, C.B. Rogers, “Effects of cell sorting and module matching on array output”, Proceedings of 15th Photovoltaic Specialist Conference, pp. 841, Florida, New York, 1981.
 E.C. Kern, E.M. Gulachenski, G.A. Kern, “Cloud effects on distributed photovoltaic generation: Slow transients at the Gardner, Masachusetts photovoltaic experiment”, IEEE Transactions on Energy Conversion, Vol. 4, No. 2, pp. 184-190, Jun. 1989.
 F. Giraud, Z. Salameh, “Analysis of the effects of a passing cloud on a grid interactive photovoltaic system with battery storage using neural networks”, IEEE Transactions on Energy Conversion, Vol. 14, No. 4, pp. 1572-1577, Dec. 1999.
 M.G. Jahoori, M.M. Saied, A.R. Hanafy, “A contribution to the simulation and design optimization of photovoltaic system”, IEEE Transactions on Energy Conversion, Vol. 6, No. 3, pp. 401-406, Sep. 1991.
 O. Wasynzuck, “Dynamic behavior of a class of photovoltaic power systems”, IEEE Transactions on Power Apparatus and Systems, Vol. PAS-102, No. 9, pp. 3031-3037, Sep. 1983.
 P. Huynh, B.H. Cho, “Design and analysis of a microprocessor controlled peak power tracking system”, IEEE Transactions on Aerospace Electronic Systems, Vol. AES-32, No. 1, pp. 182-190, Jan 1996.
 K. Hussein, I. Muta, T. Hoshino, M. Osakada, “Maximum photovoltaic power tracking: an algorithm for rapidly changing atmospheric conditions”, IEE Proceedings of Generation, Transmission and Distribution, Vol. 142, No. 1, pp. 59-64, Jan. 1995.
 Shantharama Rai C. et al, “A novel technique for Photovoltaic Maximum Power Point Tracking System”, in Proceedings of EPE 2005, No. 286, 2005.
 N. Kasa, T. Lida, L. Chen, “Flyback Inverter controlled by Sensorless Current MPPT for Photovoltaic Power System”, IEEE Transactions on Industrial Electronics, Vol. 52, No. 4, pp. 1145-1152, Aug. 2005.
 N. Femia et al, “Optimization of perturb and observe maximum power point tracking method”, IEEE Transaction on Power Electronics, Vol. 20, No. 4, pp. 963-973, 2005.
 M. Veerachary, “Power tracking for non linear PV sources with Coupled Inductor SEPIC Converter”, IEEE Transactions on Aerospace and Electronic Systems, Vol. 41(3), pp. 1019-1029, 2005.
 Joung Hu Park et al, “Dual module based Maximum Power Point tracking control of Photovoltaic systems”, IEEE Transactions on Industrial Electronics, Vol. 53, No. 4, pp. 1036-47, 2006.
 E.V. Solodovnik, S. Liu, and R.A. Dougal, “Power Controller Design for Maximum Power Point Tracking in Solar Insolations”, Vol. 19, No. 5, pp. 1295-1304, Sept. 2004.
 S. Maity, “MPPT tracking of solar cells”, P.G. dissertation, Department of Electronics and Telecommunication, Bengal Engineering and Science University, Shibpur, 2005.
 M. Bodur and M. Ermis, “Maximum Power Point Tracking for Low Power Photovoltaic Solar Panels”, in Proceedings of 7th Mediterranean Electrotechnical Conference, 1994, pp. 758-761.
 K. Kobayashi, I. Takano and Y. Sawada, “A study on a two stage maximum power point tracking control of a photovoltaic system under partially shaded insolation conditions”, in Proceedings of IEEE Power Engineering Society General Meeting 2003, Vol. 4, 2003.
 A. Kajihara and T. Harakawa, “On considerations of equivalent model about PV cell under partial shading” Proceedings of Japan Industry Applications Society Conference IEE of Japan, Vol. 1, No. 71, pp. I 289-292, Fukui, 2005.
 M.A. Abido, “Optimal design of power system stabilizers using particle swarm optimization”, IEEE Transactions on Energy Conversion Vol. 17 No. 3, pp. 406–413, 2002.
 D.K. Agrafiotis and W. Cedeno, “Feature selection for structure–activity correlation using binary particle swarms”, Journal of Medicinal Chemistry Vol. 45 No. 5, pp. 1098–1107, 2002.
 C. Fourie and A.A. Groenwold, “The particle swarm optimization algorithm in size and shape optimization”, Structural Multidisciplinary Optimization Vol. 23, pp. 259–267, 2002.
 C.O. Ourique, E.C. Biscaia and J. Carlos Pinto, “The use of particle swarm optimization for dynamical analysis in chemical processes”, Computers and Chemical Engineering Vol. 26, pp. 1783–1793, 2002.
 K.E. Parsopoulos and M.N. Vrahatis, “Recent approaches to global optimization problems through particle swarm optimization”, Natural Computing Vol. 1 No. 2–3, pp. 235–306, 2002.
 K.E. Parsopoulos and M.N. Vrahatis, “On the computation of all global minimizers through particle swarm optimization”, IEEE Transactions on Evolutionary Computation Vol. 8 No. 3, pp. 211–224, 2004.
 K.E. Parsopoulos, E.I. Papageorgiou, P.P. Groumpos and M.N. Vrahatis, “Evolutionary computation techniques for optimizing fuzzy cognitive maps in radiation therapy systems”, Lecture Notes in Computer Science Vol. 3102, pp. 402–413, 2004.
 K.E. Parsopoulos and M.N. Vrahatis, “Unified particle swarm optimization in dynamic environments”, Lecture Notes in Computer Science Vol. 3449, pp. 590–599, 2005.
 T. Ray and K.M. Liew, “A swarm metaphor for multiobjective design optimization”, Engineering Optimization Vol. 34 No. 2, pp. 141–153, 2002.
 K.E. Parsopoulos and M.N. Vrahatis, “UPSO: A unified particle swarm optimization scheme”, Proceedings of the International Conference of Computational Methods in Sciences and Engineering ICCMSE 2004, Lecture Series on Computer and Computational Sciences Vol. 1, VSP International Science Publishers, Zeist, The Netherlands, pp. 868–873, 2004.
 K.E. Parsopoulos and M.N. Vrahatis, “Parameter selection and adaptation in Unified Particle Swarm Optimization”, Mathematical and Computer Modelling, Vol. 46, No. 1-2, pp.198-213, 2007.
 R. Kathiravan and R. Ganguli, “Strength design of composite beam using gradient and particle swarm optimization”, Composite Structures, Vol. 81, No. 4, pp. 471-479, 2007.
 S. Suresh, P.B. Sujit and A.K. Rao, “Particle swarm optimization approach for multi-objective composite box-beam design”, Composite Structures, Vol. 81, No. 4, pp. 598-605, 2007.
 H. Feng, C. Chen, F. Ye, “Evolutionary fuzzy particle optimization vector quantization learning in image compression”, Expert Systems with Applications, Vol. 32, pp. 213-222, 2007.
 E. Bonabeau, M. Dorigo and G. Théraulaz, From Natural to Artificial Swarm Intelligence, Oxford University Press, New York, 1999.
 J. Kennedy and R.C. Eberhart, Swarm Intelligence, Morgan Kaufmann, 2001.
 M. Miyatake, F. Toriumi, T. Endo and N. Fuiji, “A novel Maximum Power Point Tracker controlling several converters connected to Photovoltaic arrays with Particle Swarm Optimization”, Proceedings of European Conference on Power Electronics and Applications 2007, pp. 1-10, 2007.
 B. Kaewkamnerdpong and P. Bentley, “Perceptive Particle Swarm Optimization: An investigation”, Proceedings of IEEE Symposium on Swarm Intelligence, IEEE CS Press, Vol. 1, No. 1, pp 8-10, 2005.
 S. Roy Chowdhury, D. Chakrabarti, H. Saha, “Medical Diagnosis using Adaptive Perceptive Particle Swarm Optimization and its hardware realization using Field Programmable Gate Array”, Journal of Medical Systems, Vol. 33, No. 6, pp. 447-465, 2009.
 S. Roy Chowdhury, H. Saha, “Maximum Powerpoint Tracking of Solar Photovoltaic Arrays using Adaptive Perceptive Particle Swarm Optimization Technique”, 18th Photovoltaic Science Exhibition and Conference, PVSEC 18, Kolkata, January 19-23, 2009.