Wireless Sliding MPPT Control of Photovoltaic Systems in Distributed Generation Systems

The aim of a photovoltaic (PV) system’s control is the extraction of the maximum power even if the irradiance, the temperature, or the parameters vary. To do that, a maximum power point tracking (MPPT) algorithm is required. In this work, a sliding control is designed to regulate the PV modules’ output voltage and make the panel work at the maximum power voltage. This control is selected to improve the robustness, the transient dynamic response, and the time response of the system under changeable environmental conditions, adjusting the duty cycle of the DC/DC converter. The DC/DC converter connected to the PV module output is a buck-boost converter. This configuration presents the advantage of providing voltages lower or higher than supplied by the photovoltaic modules to provide the required voltage to the load (including the voltages ceded by telecommunication loads, amongst others). In addition, a remote sliding control is developed to make the global supervision of the PV system in distributed generation grids. The designed algorithm is tested in an experimental platform, both locally and remotely connected to the base station, to prove the effectiveness of the sliding control. Thus, the communication effect in the control is also analyzed.

[1]  Xinbo Ruan,et al.  Four Switch Buck-Boost Converter for Telecom DC-DC power supply applications , 2008, 2008 Twenty-Third Annual IEEE Applied Power Electronics Conference and Exposition.

[2]  J. Chauhan,et al.  Comparison of MPPT algorithms for DC-DC converters based photovoltaic systems , 2013, 2013 International Conference on Energy Efficient Technologies for Sustainability.

[3]  Aranzazu D. Martin,et al.  Backstepping Control of Smart Grid-Connected Distributed Photovoltaic Power Supplies for Telecom Equipment , 2015, IEEE Transactions on Energy Conversion.

[4]  Kok Soon Tey,et al.  Modified incremental conductance MPPT algorithm to mitigate inaccurate responses under fast-changing solar irradiation level , 2014 .

[5]  Carlos Andrés Ramos-Paja,et al.  Maximum power point tracking based on the sliding mode control of the average PV admittance , 2014, Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA).

[6]  Carlos Andrés Ramos-Paja,et al.  Sliding-Mode Controller for Maximum Power Point Tracking in Grid-Connected Photovoltaic Systems , 2015 .

[7]  Carlos Andrés Ramos Paja,et al.  Maximum power point tracking of photovoltaic systems based on the sliding mode control of the module admittance , 2016 .

[8]  R. Teodorescu,et al.  On the Perturb-and-Observe and Incremental Conductance MPPT Methods for PV Systems , 2013, IEEE Journal of Photovoltaics.

[9]  Luis Martinez-Salamero,et al.  Impedance Matching in Photovoltaic Systems Using Cascaded Boost Converters and Sliding-Mode Control , 2015, IEEE Transactions on Power Electronics.

[10]  Ebrahim Babaei,et al.  Operational Modes and Output-Voltage-Ripple Analysis and Design Considerations of Buck–Boost DC–DC Converters , 2012, IEEE Transactions on Industrial Electronics.

[11]  Alessandro Costabeber,et al.  Convergence Analysis and Tuning of a Sliding-Mode Ripple-Correlation MPPT , 2015, IEEE Transactions on Energy Conversion.

[12]  J. R. Vazquez,et al.  MPPT in PV systems under partial shading conditions using artificial vision , 2018, Electric Power Systems Research.

[13]  M. Vitelli,et al.  Optimization of perturb and observe maximum power point tracking method , 2005, IEEE Transactions on Power Electronics.

[14]  Fernando Tadeo,et al.  Backstepping sliding mode control for maximum power point tracking of a photovoltaic system , 2017 .

[15]  Chokri Ben Salah,et al.  Comparison of fuzzy logic and neural network in maximum power point tracker for PV systems , 2011 .

[16]  G. Petrone,et al.  A two-steps algorithm improving the P&O steady state MPPT efficiency , 2014 .

[17]  Xin Ke,et al.  Improved Perturb and Observation Method Based on Support Vector Regression , 2019, Energies.

[18]  A. J. Sguarezi Filho,et al.  State feedback control for DC-photovoltaic systems , 2017 .

[19]  Guanghui Sun,et al.  New Developments in Sliding Mode Control and Its Applications , 2014 .

[20]  M. Masoum,et al.  Theoretical and Experimental Analyses of Photovoltaic Systems with Voltage and Current-Based Maximum Power Point Tracking , 2002, IEEE Power Engineering Review.

[21]  Li Zhijun,et al.  Energy Performance and Cost Comparison of MPPT Techniques for Photovoltaics and other Applications , 2017 .

[22]  Mohammad A. S. Masoum,et al.  Closure on "Theoretical and experimental analyses of photovoltaic systems with voltage and current-based maximum power point tracking" , 2002 .

[23]  Radhia Garraoui,et al.  Comparison of MPPT algorithms for DC-DC boost converters based PV systems using robust control technique and artificial intelligence algorithm , 2015, 2015 IEEE 12th International Multi-Conference on Systems, Signals & Devices (SSD15).

[24]  Saad Mekhilef,et al.  Performance Evaluation of Maximum Power Point Tracking Approaches and Photovoltaic Systems , 2018 .

[25]  Umit Ozguner,et al.  Automotive Applications of Sliding Mode Control , 2011 .

[26]  J. R. Vazquez,et al.  Backstepping Control of a Buck-Boost Converter in an Experimental PV-System , 2015 .

[27]  Ahmet Teke,et al.  A Hybrid MPPT method for grid connected photovoltaic systems under rapidly changing atmospheric conditions , 2017 .

[28]  J. R. Vazquez,et al.  Backstepping Controller Design to Track Maximum Power in Photovoltaic Systems , 2014 .

[29]  Carlos Andrés Ramos-Paja,et al.  Sliding-Mode Control of Distributed Maximum Power Point Tracking Converters Featuring Overvoltage Protection , 2018, Energies.

[30]  A. K. Abdelsalam,et al.  Artificial neural network-based photovoltaic maximum power point tracking techniques: a survey , 2015 .

[31]  Boutaib Dahhou,et al.  Adaptive fuzzy controller based MPPT for photovoltaic systems , 2014 .