INFLUENCE OF THE SAMPLING FREQUENCY ON VARIOUS MAXIMUM POWER POINT TRACKING COMMANDS
DOI:
https://doi.org/10.59277/RRST-EE.2023.68.1.2Keywords:
Intelligent neural networks, Frequency sample rate, Smoothness of the power signal, Low ripple rate, Photovoltaic maximum power point tracking (MPPT), Photovoltaic (PV) systemAbstract
The present work continues the previous article published in the International Journal of Energy (Elsevier, 2019). Our previous study aimed to develop a new and innovative method based on neural network algorithms to predict an instantaneous command. A new control strategy for photovoltaic systems was presented in [1]. This command is based on the neuronal network (NN) technique. To the best of our knowledge, this technique has never been used in this field for that objective. The authors of this work used it to synthesize control laws for electronic power converters.
It should be noted that the newly designed algorithm based on neural networks is expected to be more robust with a good performance concerning tracking speed and precision. Moreover, the present research work aims at providing a robust neural structure against noisy empirical data, thus allowing the prediction of a new command. Indeed, in the present work, we will examine the parameters affecting four MPPT controls in addition to the new neural network-based algorithm developed in [1].
References
(1) S. Issaadi, W. Issaadi, A. Khireddine, New intelligent control strategy by robust neural network algorithm for real time detection of an optimized maximum power tracking control in photovoltaic systems, International Journal of Energy, 187, 15 November 2019, 115881.
(2) W. Issaadi, A. Khireddine, S. Issaadi. Management of a base station of a mobile network using a photovoltaic system, International Journal of Renewable & Sustainable Energy Reviews (Elsevier), 59, C, pp. 1570–1590 (2016).
(3) W. Issaadi, S. Issaadi, A. Khireddine, Comparative study of the photovoltaic system optimization techniques: Contribution to the improvement and development of a new approach, International Journal of Renewable & Sustainable Energy Reviews (Elsevier). 82, 3, pp. 2112-2127 (February 2018).
(4) T. Esram, P.L. Chapman, Comparison of photovoltaic array maximum power point tracking methods, IEEE Transactions on Energy Conversion, 22, 2, pp. 439–449 (June 2007).
(5) V. Salas, E. Olıas, A. Barrado, A. Lazaro, Review of the maximum power point tracking algorithms for stand-alone photovoltaic systems”, Solar Energy Materials and Solar Cells, 90, 11, pp. 1555–1578 (2006).
(6) D.P. Hohm, M.E. Ropp, Comparative study of maximum power point tracking algorithms using an experimental programmable, maximum power point tracking test bed, IEEE Photovoltaic Specialists Conference, PVSC 2000, pp. 1699-1702 (Sept. 2000).
(7) H.D. Maheshappa et al., An improved maximum power point tracker using a step-up converter with current locked loop, Renewable Energy, 13, 22, pp. 195-201 (1998).
(8) S.J. Chiang et al. “Residential Photovoltaic Energy Storage System”. IEEE Trans. on I. E., 45, 3, pp. 385-394 (June 1998).
(9) W. Issaadi Conventional MPPT and control of a photovoltaic system by neural networks: improvements and perspectives, Proceedings of the international conference on design and production engineering, ‘DPE’2016’. Berlin, Germany (July 25–26, 2016).
(10) W. Issaadi et al., Command of a photovoltaic system by artificial intelligence comparatives studies with conventional controls: Results improvements and perspectives, IEEE-8th International Conference on Modelling Identification and Control (ICMIC), pp. 583-591 (2016).
(11) E. Mujadi, ANN based peak power tracking for PV supplied dc motors, Solar Energy, 69, 4, pp. 343-354 (2000).
(12) R. Akkaya, A.A. Kulaksız, O. Aydogdu, DSP implementation of a PV system with GAMLP-NN based MPPT controller supplying BLDC motor drive, Energy Conversion and Management, 48, 1, pp. 210–218 (2007).
(13) N. Dasgupta, A. Pandey, A.K. Mukerjee, Voltage-sensing-based photovoltaic MPPT with improved tracking and drift avoidance capabilities, Solar Energy Materials and Solar Cells, 92, 12, pp. 1552–1558 (2008).
(14) K-H. Chao, C-J. Li, An intelligent maximum power point tracking method based on extension theory for PV systems, Expert Systems with Applications, 37, 2, pp. 1050–1055 (2010).
(15) A. Oi, Design and simulation of photovoltaic water pumping system, Faculty of California Polytechnic State University (2005).
(16) W. Issaadi, Control of a photovoltaic system by Fuzzy Logic, comparative studies with conventional controls: results, improvements, and perspectives, International Journal of Intelligent Engineering Informatics, 5, 3, pp. 206–224 (2017).
(17) W. Issaadi, An improved MPPT converter using current compensation method for PV-Applications. International Journal of Renewable Energy Research, 6, 3. pp. 894-913 (2016).
(18) N. Pongratananukul, Analysis and simulation tools for solar array power systems, University of Central Florida (2005).
(19) T.E. Persen, FPGA-based design of a maximum-power-point-tracking system for space applications, University of Florida (2004).
(20) R. Kianinezhad, B. Nahid, F. Betin, G.A. Capolino, A new field oriented control of dual three phase induction machines, IEEE International Conference on Industrial Technology, Hammamet, Tunisia (December 2004).
(21) Ch. Hua, J. Lin, Ch. Shen, Implementation of a DSP-controlled PV system with peak power tracking, IEEE Trans. Ind. Electron., 45, 1, pp. 99–107 (1998).
(22) S. Qin et al., Comparative analysis of incremental conductance and perturb-and observation methods to implement MPPT in photovoltaic system, Wuhan institute of technology, China (2011).
(23) Ch. Hua, J. Lin, Ch. Shen, Implementation of a DSP-controlled PV system with peak power tracking, IEEE Trans. Ind. Electron., 45, pp. 99–107 (1998).
(24) Z. Salameh, D. Taylor, Step-up maximum power point tracker for photovoltaic arrays, Solar Energy, 44, pp. 57–61 (1990).
(25) T.P. Nguyen, Solar Panel Maximum Power Point Tracker, Undergraduate Thesis, The University of Queensland Department of Computer Science & Electrical Engineering (19 October 2001).
(26) N. Femia, G. Petrone, G. Spagnuolo, M. Vitelli, Optimization of perturb and observe maximum power point tracking method, IEEE Transactions on Power Electronics, 20, 4, pp. 16-19 (Mar. 2004).
(27) K. Noppadol, W. Theerayod, S. Phaophak, FPGA implementation of MPPT using variable step-size P&O algorithm for PV applications, Communication and Information Technologies, ISCIT’06, IEEE International Symposium, pp. 212–215 (Sept. 2006).
(28) W. Xiao, A Modified Adaptative Hill Climbing Maximum Power Point Tracking (MPPT) Control Method For Photovoltaic Power Systems, The University of British Columbia (2003).
(29) A. Oi, Design and Simulation of Photovoltaic Water Pumping System, Faculty of California Polytechnic State University (2005).
(30) E. Koutroulis, K. Kalaitzakis, N.C. Voulgaris, Development of a microcontroller-based, photovoltaic maximum power point tracking control system, IEEE Transactions on Power Electronics, 16, 1, pp. 46–54 (2001).
(31) A.B.G. Bahgat et al., Maximum Power point tracking controller for PV systems using neural networks, Renewable Energy, 30, 8, pp. 1257–1268 (2005).
(32) H. Knopf, Analysis, Simulation, and Evaluation of Maximum Power Point Tracking (MPPT) Methods for a Solar Powered Vehicle. Master of Science in Electrical and Computer Engineering, Portland State University (1999).
(33) K.H. Hussein, I. Muta, T. Hoshino, M. Osakada, Maximum photovoltaic power tracking: an algorithm for rapidly changing atmospheric conditions, IEE Proc. Generation Transmission Distrib., 142, 1, pp. 59–64 (1995).
(34) K. Ripsaw, T. Saito, I. Takano, Y. Sawada, Maximum power point tracking control of photovoltaic generation system under non-uniform insolation by means of monitoring cells, Conf. Record of the Twenty-Eighth IEEE Photovoltaic Specialists Conf., pp. 1707-1710 (2000).
(35) G.J. Yu, Y.S. Jung, J.Y. Choi, J.H. Song, G.S. Kim, A novel two-mode MPPT control algorithm based on comparative study of existing algorithms, Conf. Record of the Twenty-Ninth IEEE Photovoltaic Specialists Conf., pp. 1531–1534 (2002).
(36) J.H. Lee, H. B. Bo, H. Cho, Advanced incremental conductance MPPT algorithm with a variable step size, Power Electronics and Motion Control Conference, EPE-PEMC 12th International, pp. 603–607 (Aug. 2006).
(37) T.Y. Kim, H.G. Ahn, S.K. Park, Y.K. Le, A novel maximum power point tracking control for photovoltaic power system under rapidly changing solar radiation, IEEE International Symposium, 2, pp. 1011–1014 (Jun. 2001).
(38) F. Saftoiu, A.M. Morega, Cooling system for photovoltaic panels, Rev. Roum. Sci. Techn. – Électrotechn. Et Énerg., 67, 3, pp. 343–348 (2022).
(39) M. Burlacu, V. Navrapescu, A-I. Chirila, I-D. Deaconu, Optimal reactive power management for microgrids based on photovoltaic inverters using sine-cosine algorithm, Rev. Roum. Sci. Techn. – Électrotechn. Et Énerg., 67, 2, pp. 117–122 (2022).
