An enhanced MPPT based on Integral Sliding Mode Control and Artificial Neural Network for PV Pumping System

RAFIKA ELIDRISSI

Abstract


This paper proposes a maximum power point tracking (MPPT) control method for a photovoltaic (PV) pumping system based on a nonlinear integral sliding mode approach. The system’s power circuit comprises of a solar panel, a boost-up converter and a DC motor feeds a water pump. Two loops are in the control system: the first, provides the reference voltage, that is given by intelligent method based on artificial neural network (ANN), according with the maximum power point (MPP), for the integral sliding mode controller in the second loop that regulates the PV array voltage in MPP. This is done through adjustment of the DC-DC boost converter duty ratio. The proposed approach is compared to the integral backstepping approach. Simulation results depict the proposed regulator effectiveness and robustness in relation to rapidly irradiance and temperature changes.


Keywords


Integral sliding mode; ANN; MPPT; Solar Panel; Boost Converter; Permanent magnet DC motor (PMDC MOTOR)

References


G.K.Singh, "Solar power generation by PV(photovoltaic) technology: a review," Energy, vol. 53, pp. 1-13, 2013.

W.-Y. Choi and L. Change-Goo, "photovoltaic panel integrated power conditioning system using a high efficiency step-up DC--DC converter," Renewable energy, vol. 41, pp. 227--234, 2012.

P. G. Kini, R. C. Bansal and R. S. Aithal, "Performance analysis of centrifugal pumps subjected to voltage variation and unbalance," IEEE transactions on Industrial Electronics, vol. 55, pp. 562-569, 2008.

R. Leyva, P. Artillan, C. Cabal, B. Estibals and C. Alonso, "Dynamic performance of maximum power point tracking circuits using sinusoidal extremum seeking control for photovoltaic generation," International Journal of Electronics, vol. 98, pp. 529-542, 2011.

D. Sera, L. Mathe, T. Kerekes, S. v. Spataru and R. Teodorescu, "On the perturb-and-observe and incremental conductance MPPT methods for PV systems," IEEE journal of photovoltaics, vol. 3, no. 3, pp. 1070--1078, 2013.

S. G. alla, C. Bhende and S. Mishra, "Photovoltaic based water pumping system," in 2011 International Conference on Energy, Automation and Signal, 2011, pp. 1--4.

M. Akbaba, I. Qamber and A. Kamal, "Matching of separately excited DC motors to photovoltaic generators for maximum power output," Solar Energy, vol. 63, no. 6, pp. 375--385, 1998.

V. C. Mummadi, "teady-state and dynamic performance analysis of PV supplied DC motors fed from intermediate power converter," Solar Energy Materials and Solar Cells, vol. 61, no. 4, pp. 365--381, 2000.

S. Singer and J. Appelbaum, "Starting characteristics of direct current motors powered by solar cells," IEEE Transactions on Energy Conversion, vol. 8, no. 1, pp. 47--53, 1993.

T.-F. Wu and Y.-K. Chen., "Wu, Tasi-Fu, and Yu-Kai Chen. "Modeling PWM DC/DC converters out of basic converter units," IEEE transactions on Power Electronics , vol. 13, no. 5, pp. 870-881, 1998.

J. Enrique, E. Durán, M. de-Cardona and J. Andújar, "Theoretical assessment of the maximum power point tracking efficiency of photovoltaic facilities with different converter topologies," Solar Energy, vol. 81, no. 1, pp. 31-38, 2007.

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, 2001.

J.Ahmed and Z.Salam, "An improved perturb and observe (P&O) maximum power point tracking(MPPT) algorithm for higher efficiency," Applied Energy , vol. 150, pp. 97-100, 2015.

A.Harrag and S.Messali, "Variable step size modified P&O MPPT algorithm using GA-based hybrid offline/online PID controller," Renewable and Sustainable Energy Reviews , vol. 491, pp. 247-1260, 2015.

B.Bendib, H. Belmili and F.Krim, "A survey of the most used MPPT methods: Conventional and advanced algorithms applied for photovoltaic systems," Renewable and Sustainable Energy Reviews , vol. 45, pp. 637-648, 2015.

K. Tey and S.Mekhilef, "Modified incremental conductance MPPT algorithm to mitigate inaccurate," Solar Energy, vol. 101, pp. 333-342, 2014.

A.Loukriz, M.Haddadi and S.Messali, "Simulation and experimental design of a new advanced variable step size Incremental Conductance MPPT algorithm for PV systems," ISA Transactions, vol. 62, pp. 30-38, 2016.

H.Boumaaraf, A.Talha and O.Bouhali, "A three phase NPC grid-connected inverter for photovoltaic applications using neural network MPPT," Renewable and Sustainable Energy Reviews, vol. 49, pp. 1171-1179, 2015.

H. Rezk and E.-S. Hasaneen, "A new MATLAB/Simulink model of triple-junction solar cell and MPPT based on artificial neural networks for photovoltaic energy systems," Ain Shams Engineering Journal , vol. 6, no. 3, pp. 873-881, 2015.

Y-T.Chen, Y.-C. Jhang and R.-H. Liang, "Fuzzy-logic based-scaling variable step-size MPPT methodfor PV systems," Solar Energy, vol. 126, pp. 53-63, 2016.

B. Bendiba, F. Krimb, H. Belmilia, M. F. Almia and S.Bouloumaa, "Advanced Fuzzy MPPT Controller for a stand-alone PV system," Energy Procedia, vol. 50, p. 383 – 392, 2014.

I.-S. Kim, "Robust maximum power point tracker using sliding mode controller for the three-phase grid-connected photovoltaic system," Solar Energy, vol. 81, no. 3, pp. 405-414, 2007.

M. Moradi, S. R. Tousi, M. Nemati, N. Basir and N. Shalavi, "A robust hybrid method for maximum power point tracking in photovoltaic systems," Solar Energy, vol. 94, pp. 266-276, 2013.

O. Y.-L. K. C.-Y. C. Chian-Song, "Terminal sliding mode control for maximum power point tracking of photovoltaic power generation systems," Solar Energy , vol. 86, pp. 2986-2995, 2012.

R. EL Idrissi, A. Abbou and M. Salimi, "Artificial Neural-Network-Based Maximum Power Point Tracking for Photovoltaic Pumping System Using Backstepping Controller," in 2018 IEEE 59th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON), Riga, Latvia, 2018.

A. Luque and e. Steven Hegedus, Handbook of photovoltaic science and engineering, John Wiley & Sons, 2011.

J. A. Gow and C. D. Manning, "Development of a photovoltaic array model for use in power-electronics simulation studies," IEE Proceedings-Electric Power Applications , vol. 146, no. 2, pp. 193-200, 1999.

Y. T. Tan, D. S. Kirschen and N. Jenkins, "A model of PV generation suitable for stability analysis," IEEE Transactions on energy conversion, vol. 19, no. 4, pp. 748-755, 2004.

K. Hussein, I. Muta, T. Hoshino and M. Osakada, "Maximum photovoltaic power tracking: an algorithm for rapidly changing atmospheric conditions," IEE Proceedings-Generation, Transmission and Distribution , vol. 142, no. 1, pp. 59-64, 1995.

A. J. Forsyth and S. V. Mollov, "Modelling and control of DC-DC converters," Power engineering journal , vol. 12, no. 5, pp. 229-236, 1998.

K. Dahech, M. Allouche, T. Damak and F. Tadeo, "Backstepping sliding mode control for maximum power point tracking of a photovoltaic system," Electric Power Systems Research, vol. 143, pp. 182-188, 2017.

Kalogirou and S. A, "Artificial neural networks in renewable energy systems applications: a review," Renewable and sustainable energy reviews, vol. 5, no. 4, pp. 373-401, 2001.

Kulaksiz, A. Afşin and R. Akkaya, "Training data optimization for ANNs using genetic algorithms to enhance MPPT efficiency of a stand-alone PV system," Turkish Journal of Electrical Engineering & Computer Sciences , vol. 20, no. 2, pp. 241-254, 2012.




DOI: http://doi.org/10.11591/ijeecs.v20.i3.pp%25p
Total views : 57 times

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

shopify stats IJEECS visitor statistics