A flexible, genuine software for the simulation and sizing of photovoltaic pumping systems

Abstract

There are few resources as precious to life as water. However, even today, many people around the world still lack decent access to it. One of the reasons for this is the remoteness of these populations from modern water collection and distribution technologies, often coupled with an unfavourable socio-economic situation. Photovoltaic pumping technology makes it possible to respond both to this problem and to the criteria of sustainable development. This technology makes it possible to pump water without emitting greenhouse gases even when located at a remote distance from an electrical grid. However, the associated initial investment and the intermittency of the system can be major obstacles to the development of this technology. Several researchers have already worked on these systems, proposing numerous forecasting models that allow better prediction of the volume of water pumped based on input data. However, links between the academic research are lacking, and it remains difficult to know which models and strategies are best suited to improving forecasts and reducing costs. The work carried out here implements a software approach in order to synthesize existing research and facilitate photovoltaic pumping system sizing for domestic consumption. It mainly consists of an aggregation of models found in the literature within a free, flexible and well-documented software solution. This software is coded in the Python programming language and provides the user with useful tools for the modeling and sizing of such pumping systems. Using this software, several comparative studies are carried out to evaluate the quality of pump models, the influence of weather files and the viability of direct coupling. The results obtained highlight the pump models to be used preferentially, as well as the variability in pumped water output coming from the use of typical weather files such as TMY, CWEC and IWEC standards. It is also shown that systems with a pump directly coupled to the photovoltaic array, without the intermediary of MPPT converter, are the most cost-efficient option if the pump input characteristics match well with the photovoltaic modules. Otherwise the option of coupling via MPPT results in more cost-efficient systems on average. The proposed software leaves room for further development. The continuation of this work consists primarily in validating the predictive power of the software through experimental results, after which new models could be implemented to improve the support of pumping systems for agriculture, for example.

Date	8 Jul 2020
Original language	American English
Awarding Institution	École de technologie supérieure
Supervisor	Daniel Rousse (Supervisor) & Sergio Gualteros Martinez (Co-supervisor)