MAXIMIZING EFFICIENCY OF A PHOTOVOLTAIC WATER PUMPING SYSTEM USING THE MPPT-BASED FUZZY LOGIC CONTROLLER
Keywords:
PV energy utilization efficiency, maximum power point tracking, fuzzy logic controller, photovoltaic water pumping systemAbstract
In order to facilitate the most suitable approach for maximizing the overall efficiency of a standalone photovoltaic water pumping system (PVWPS), providing a more accurate and efficient model is necessary prior to installation. In this paper, after implementing the PVWPS model, the fuzzy logic controller (FLC) based on the maximum power point tracking (MPPT) technique is proposed to detect the maximum PV power output by regulating the switching duty ratio of the interface converter to match the PV generator and motor pump as the load. The FLC design is derived from the genetic optimization, and thus the complexity is significantly reduced by 24%. In the test, the PVWPS with MPPT controllers was carried out under weather variations at a constant head pumping (20 m) and a daily average water supply of 20,000 L/day. As a result, the proposed MPPT-FLC offers PV energy utilization efficiency of up to 91% by means of maximizing the motor speed, and consequently increasing the water discharge per watt of the installed PV array. Furthermore, the global efficiency of the PVWPS can increase up to 3.4%, which is 6%, 10%, and 15% more efficient than the existing controllers: the conventional FLC, the neural network-based controller, and the perturb and observe method, respectively.
References
Abdolzadeh, M. and Ameri, M. (2009). Improving the effectiveness of a photovoltaic water pumping system by spraying water over the front of photovoltaic cells. Renew. Energ., 34(1):91-96.
Alghuwainem, S.M. (1994). Matching of a DC motor to a photovoltaic generator using a step-up converter with a current-locked loop. IEEE T. Energy Conver., 9(1):192-198.
Bouselham, L., Hajji, M., Hajji, B., and Bouali, H. (2017). A MPPT-based ANN controller applied to PV pumping system. Proceedings of the International Renewable and Sustainable Energy Conference (IRSEC); Nov. 14-17, 2016; Marrakech, Morocco, p. 1-7.
Chaouali, H., Othamani, H., Mezghani, D., and Ur-Laper, A.M. (2017). Improving the control strategy of a standalone PV pumping system by fuzzy logic technique. Int. J. Adv. Comp. Sci. Appl., 8(3):165-175.
Daud, A-K. and Mahmoud M.M. (2005). Solar powered induction motor-driven water pump operating on a desert well, simulation and field tests. Renew. Energ., 30:701-714.
De Blass, M.A., Torre, J.L., Prieto, E., and Garcia, A. (2002). Selecting a suitable model for characterizing photovoltaic devices. Renew. Energ., 25(3):371-380.
Florescu, A. and Oprea, S. (2012). PV charger system using a synchronous buck converter. Proceedings of the SNET’2012 Conference; Dec. 14, 2012; Bucharest, Romania, p. 328-333.
Habiballahi, M., Ameri, M., and Mansouri, S.H. (2015). Efficiency improvement of photovoltaic water pumping system by means of water flow beneath photovoltaic cells surface. J. Sol. Energ. Eng., 137(4):1-8.
Harrag, A., Titraoui, A., Bahri, H., and Messalti, S.S. (2017). Photovoltaic pumping system - Comparative study analysis between direct and indirect coupling mode. AIP Conf. Proc., 1,814(1):1-11.
Izzuddin, T.A., Johar, M.A., Rahsid, M.Z.A., and Jali., M.H. (2018). Smart irrigation using fuzzy logic method. APRN J. Eng. Appl. Sci., 13(2):517-522.
Kumar, B., Chauhan, Y.K., and Shrivastava, V. (2014). Performance analysis of a water pumping system supplied by a photovoltaic generator with different maximum power point tracking techniques. Songklanakarin J. Sci. Technol., 36(1):107-113.
Langridge, W., Lawrance, W., and Wichert, B. (1996). Development of a photovoltaic pumping system using a brushless DC motor and helical rotor pump. Sol. Energy, 56(2):151-160.
Odeh, I., Yohanis, Y.G., and Norton, B. (2006). Influence of pumping head, insolation and PV array size on PV water pumping system performance. Sol. Energy, 80(1):51-64.
Rao, M.J.M., Sahu, M.K., and Subudhi, P.K. (2018). PV based water pumping system for agricultural sector. Mater. Today-Proc., 5(1):1,008-1,016.
Talbi, B., Krim, F., Rekioua, T., Mekhilef, S., and Laib, A. (2018). A high-performance control scheme for photovoltaic pumping system under sudden irradiance and load changes. Sol. Energy, 159:353-368.
Wongsathan, R. and Seedadan, I. (2017). Artificial intelligence and ANFIS reduced rule for equivalent parameter estimation of PV module on various weather conditions utilize for MPPT. Int. J. Renew. Energ., 12(1):38-55.
