Research Article
Sizing of a Standalone Photovoltaic Water Pumping System of a Well in Ngoundiane Site
@INPROCEEDINGS{10.1007/978-3-030-80618-7_8, author={Amy Sadio and Senghane Mbodji and Biram Dieng and Arona Ndiaye and Ibrahima Fall and Papa Lat Tabara Sow}, title={Sizing of a Standalone Photovoltaic Water Pumping System of a Well in Ngoundiane Site}, proceedings={Advances of Science and Technology. 8th EAI International Conference, ICAST 2020, Bahir Dar, Ethiopia, October 2-4, 2020, Proceedings, Part II}, proceedings_a={ICAST PART 2}, year={2021}, month={7}, keywords={Photovoltaic water pumping system Numerical method Average loss of power supply probability}, doi={10.1007/978-3-030-80618-7_8} }- Amy Sadio
Senghane Mbodji
Biram Dieng
Arona Ndiaye
Ibrahima Fall
Papa Lat Tabara Sow
Year: 2021
Sizing of a Standalone Photovoltaic Water Pumping System of a Well in Ngoundiane Site
ICAST PART 2
Springer
DOI: 10.1007/978-3-030-80618-7_8
Abstract
In this paper, the sizing and design of a standalone photovoltaic water pumping system in Ngoundiane, a village located in Senegal is investigated. An intuitive sizing method is firstly applied to get approximate information on the sizes of the various components. In this method, the capacity of various components is separately computed and any relationship between them are considered. To improve the results, a new sizing approach based on numerical methods is developed using the Average Loss of Power Supply Probability (ALPSP) criterion. Empirical simple models are used to model the components of PV system. From the energy generated by PV array, the different states of charge of the battery storage are estimated. A simple algorithm has been elaborated to determine the different PV and battery combinations for various ALPSP levels. The proposed model has been applied to the meteorological average data in Ngoundiane site and conducted using MATLAB software. The results showed that the numerical method proposed allows a 50% reduction of the storage capacity when compared to the intuitive method. However, we noticed that the values of ALPSP are particularly high with a smaller value of 0.3, probably due to the underestimation of input parameters and the nature of meteorological data used in the model. In order to show the importance of the developed approach, a comparison with literature has been performed.
