Hybrid MPPT Algorithm for PV Systems Under Partially Shaded Conditions Using a Stochastic Evolutionary Search and a Deterministic Hill Climbing

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A hybrid maximum power point tracking method has been proposed for the photovoltaic system using a stochastic evolutionary search and a deterministic hill climbing algorithm. The proposed approach employs the particle swarm optimizer (PSO) to solve a dynamic optimization problem related to the control task in a PV system. The position of the best particle is updated by the hill climbing algorithm, and the position of the rest of the particles by the classic PSO rule. The presented method uses the re-randomization mechanism, which places five consecutive particles randomly, but in specified intervals. This mechanism helps track the maximum power point under partially shaded conditions.

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  • [1] Gakkhar N. Soni M.S. Techno-Economic Parametric Assessment of CSP Power Generations Technologies in India 4th Int. Conf. Advances in Energy Research ICAER 2013 En. Proc. 2014 54 152–160.

  • [2] Sufang Z. Yongxiu H. Analysis on the development and policy of solar PV power in China Ren. Sust. En. Rev. 2013 21 393–401.

  • [3] Hosenuzzaman M. Rahim N.A. Selvaraj J. Hasanuzzaman M. Malek A.B.M.A. Nahar A. Global prospects progress policies and environmental impact of solar photovoltaic power generation Ren. Sust. En. Rev. 2015 41 284–297.

  • [4] Kot R. Stynski S. Malinowski M. Hardware methods for detecting global maximum power point in a PV power plant Proc. IEEE Int. Conf. Industrial Technology ICIT 2015 2907–2914.

  • [5] Logeswarana T. Senthilkumarb A. A review of maximum power point tracking algorithms for photovoltaic systems under uniform and non-uniform irradiances 4th Int. Conf. Advances in Energy Research ICAER 2013 India 2013 228–235.

  • [6] Ishaque K. Salam Z. Amjad M. Mekhilef S. An improved particle swarm optimization (PSO)-based MPPT for PV with reduced steady-state oscillation IEEE Trans. Ind. Electron. 2012 60(8) 3627–3638.

  • [7] Ishaque K. Salam Z. A deterministic particle swarm optimization maximum power point tracker for photovoltaic system under partial shading condition IEEE Trans. Power Electron. 2013 27(8) 3195–3206.

  • [8] Balamurugan M. Narendiran S. Sahoo S.K. Das R. Sahoo A.K. Application of particle swarm optimization for maximum power point tracking in PV system 3rd Int. Conf. Electrical Energy Systems (ICEES) India 2016 35–38.

  • [9] Shi J. Zhang W. Zhang Y. Xue F. Yang C.T. MPPT for PV systems based on a dormant PSO algorithm El. Power Syst. Res. 2015 123 100–107.

  • [10] Renaudineau H. Donatantonio F. Fontchastagner J. Petrone G. Spagnuolo G. Martin J.-P. Pierfederici S. A PSO-based global MPPT technique for distributed PV power generation IEEE Trans. Ind. Electron. 2015 62(2) 1047–1058.

  • [11] Liu Y.-H. Huang S.-C. Huang J.-W. Liang W.-C. A particle swarm optimization-based maximum power point tracking algorithm for PV systems operating under partially shaded conditions IEEE Trans. En. Conv. 2012 27(4) 1027–1035.

  • [12] Bouarroudj N. Boukhetala D. Djari A. Rais Y. Benlahbib B. FLC based Gaussian membership functions tuned by PSO and GA for MPPT of photovoltaic system. A comparative study 6th Int. Conf. Systems and Control (ICSC) Algeria 2017 317–322.

  • [13] Yang Z. Duan Q. Zhong J. Mao M. Xun Z. Analysis of improved PSO and perturb and observe global MPPT algorithm for PV array under partial shading condition 29th Chinese Control and Decision Conference China 2017 549–553.

  • [14] Mao M. Duan Q. Zhang L. Chen H. Hu B. Duan P. Maximum power point tracking for cascaded PVconverter modules using two-stage particle swarm optimization Sci. Rep. 2017 7 art. No. 9381.

  • [15] Mao M. Zhang L. Duan Q. Chen H. Oghorada O.J.K. Duan P. Hu B. A two-stage particle swarm optimization algorithm for MPPT of partially shaded PV arrays Sci. Rep. 2017 7 694–702.

  • [16] Koad R.B. Zobaa A.F. El-Shahat A. A novel MPPT algorithm based on particle swarm optimization for photovoltaic systems IEEE Trans. Sust. En. 2017 8(2) 468–476.

  • [17] Ufnalski B. Grzesiak L.M. Plug-in direct particle swarm repetitive controller with a reduced dimensionality of a fitness landscape – a multi-swarm approach Bull. Polish Acad. Sci. Techn. Sci. 2015 63(4) 857–866.

  • [18] Ufnalski B. Grzesiak L.M. A plug-in direct particle swarm repetitive controller for a single-phase inverter Przeg. Elektrotechn. 2014 6 6–11 (in Polish).

  • [19] Ufnalski B. Grzesiak L.M. Plug-in direct multi-swarm repetitive controller for the sine wave inverter – on keeping particles diversified in a dynamic and noisy environment 6th Int. Conf. Power Engineering Energy and Electrical Drives 10th Int. Conf. Compatibility and Power Electronics (CPE-POWERENG) Poland 2016 484–491.

  • [20] Ufnalski B. Małkowski M. Grzesiak L.M. Hybrid repetitive controller using a stochastic evolutionary search and a deterministic iterative learning law 21st Int. Conf. Methods and Models in Automation and Robotics MMAR 2016 Poland 2016 88–93 (in Polish).

  • [21] Ufnalski B. Grzesiak L.M. Małkowski M. Hybridization schemes for particle swarm iterative learning controllers in repetitive systems 19th Eur. Conf. Power Electronics and Applications EPE ’17 ECCE Europe Poland 2017 P.1–P.10.

  • [22] Basinski K. Ufnalski B. Grzesiak L.M. Particle swarm based repetitive spline compensator for servo drives Przegl. Elektrotechn. 2017 2 181–187 (in Polish).

  • [23] Basinski K. Ufnalski B. MPPT for PV using PSO [Online] Available: https://www.mathworks.com/matlabcentral/fileexchange/64629-mppt-for-pv-using-pso

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