Simulation of Standalone Hybrid Solar-Battery Fed Water Pumping System
PDF
PDF

How to Cite

Sumithara, A., and S. Chitra. 2022. “Simulation of Standalone Hybrid Solar-Battery Fed Water Pumping System”. Journal of Electronics and Informatics 4 (1): 32-41. https://doi.org/10.36548/jei.2022.1.004.

Keywords

— Photovoltaic
— Battery
— bidirectional DC-DC converter
— Artificial Neural Network
Published: 29-04-2022

Abstract

A hybrid battery-based solar (Photovoltaic) water pumping system for agriculture applications has been presented in this research. The battery hybrid power generation is utilized as an energy source to accomplish full-scale continuous water delivery, regardless of climatic conditions. The solar photovoltaic (PV) battery system is used as the primary source, with the battery acting as a backup. With that, when the photovoltaic cluster is insufficient to handle water pumping due to weather conditions or around night time, the battery supplies power. Moreover, it is charged by the solar cluster when the water conveyance isn't needed. As a result, no external inventory is used to charge the batteries. A bidirectional charging control allows to change the battery's activity mode by using a buck-boost converter. Artificial neural network is proposed as the controller for switching the pulse of the bidirectional converter. MATLAB/SIMULINK software is used for analysing performance of the proposed system.

References

  1. S. S. Chandel, M. Nagaraju Naik, and R. Chandel, “Review of solar photovoltaic water pumping system technology for irrigation and community drinking water supplies,” Renewable and Sustainable Energy Reviews, vol. 49, pp. 1084–1099, Sep. 2015.
  2. S. S. Patil and R. M. Zende, “Solar powered water pumping system,” in 2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS), Chennai, India, 2017, pp. 186–190.
  3. 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 J. Photovoltaics, vol. 3, no. 3, pp. 1070–1078, Jul. 2013.
  4. Atarsia Loubna, Toufouti Riad, “Standalone photovoltaic array fed induction motor driven water pumping system ,” in International Journal of Electrical and Computer Engineering (IJECE) Vol. 10, No. 5 2020.
  5. H. R., H. Daneshpajooh, A. Safaee, P. Jain, and A. Bakhshai,“Bidirectional DC - DC converters for energy storage systems,” inEnergy Storage in the Emerging Era of Smart Grids, R. Carbone, Ed. InTech, 2011.
  6. B. Y. Li, C. Xu, C. Li, and Z. Guan, “Working principle analysis and control algorithm for bidirectional DC/DC converter,” p. 9, 2017.
  7. M. A. Elgendy, B. Zahawi, and D. J. Atkinson, “Evaluation of perturband observe MPPT algorithm implementation techniques,” in 6th IET International Conference on Power Electronics, Machines and Drives (PEMD 2012), Bristol, UK, 2012, pp. P110–P110.
  8. J. Macaulay and Z. Zhou, “A fuzzy logical-based variable step size P&O MPPT algorithm for photovoltaic system,” Energies, vol. 11, no. 6, p. 1340, May 2018.
  9. Rajan Kumar , Bhim Singh, “Solar PV-Battery based Hybrid Water Pumping System using BLDC Motor Drive ,” in 1st IEEE International Conference on Power Electronics. Intelligent Control and Energy Systems (ICPEICES-2016) p. 9, 2016.
  10. Ramasamy, Suganthi, and Maruthupandi Perumal. "CNN based deep learning technique for improved H7 TLI with grid connected photovoltaic systems." International Journal of Energy Research 45.14 (2021): 19851-19868.