Pump-as-turbines for hydropower energy recovery from on-demand irrigation networks: Flow fluctuation characterisation, energy potential extrapolation, and real-scale implementation.

Abstract

More water efficient irrigation techniques have been studied and developed during the last decades, and are becoming of significant importance in arid and semi-arid regions, as these are leading to more energy intensive irrigation infrastructures. This thesis presents hydropower energy recovery as a potential measure to improve the energy efficiency in on-demand irrigation networks. Findings in four main elements of work are developed, presented and discussed, related to: i) flow fluctuations prediction, ii) feasibility assessment, iii) energy potential extrapolation and iv) real-scale implementation. On the first element, a new methodology to predict the in-pipe flow variations in on-demand networks along an irrigation season was developed. As fluctuations in the flow rate provokes considerable effects on turbine efficiency for hydropower energy recovery, this characterisation is largely important to quantify in detail the hydropower potential. Furthermore, the theoretical performance of pump-as-turbines was considered based on the theoretical best efficiency point, selecting the device returning the minimum payback period. Pumps-as-turbines are conventional pumps working in reverse mode as turbines. Using them for energy recovery has been shown to be cost-effective at sites with small power output capacity rather than conventional turbines. Their cost-effectiveness lies in the fact that pumps are mass produced and many models exist of differing sizes. This results in considerably cheaper machinery covering a wide range of flow and head combinations. However, anticipating their performance is a well-known challenge. Secondly, the methodology feasibility was evaluated comparing the results predicted in nine points of an on-demand irrigation network with actual data recorded for the 2015 irrigation season. Several statistical parameters and efficiency criteria were used to compare the results coming from simulations and from the application of actual flow observations in a real network, in high resolution, and over a 1-year period. The validation of this methodology will allow its application in different irrigation networks to quantify the existing potential and study how PATs could improve their energy efficiency. The overall result of the methodology comparing actual records and predicted data was satisfactory. In the case of the flow, it presented a good fit between the predicted and the actual values, with a MAE and RMSE of 0.0026 and 0.0068 on the occurrence probability. Values for R2 and efficiency criteria of 0.804 and 0.576 respectively, were obtained. Therefore, the results showed a feasible average accuracy for flow prediction, which allowed a more accurate estimation of the hydropower potential. Once the method was developed and validated, a large-scale energy recovery assessment was carried out, which could provide an approximation of the potential benefits associated with hydropower in on-demand irrigation networks. Linear regression models and artificial neural networks were used to estimate the energy recovery potential in an irrigated surface of about 164,000 ha. Three proxy variables were used, including: irrigated surface, theoretical crop irrigation requirements and slope. Using the results provided by artificial neural networks, the economic, environmental and energetic impacts were quantified in the area analysed. A reduction in energy consumption in the agriculture sector of this magnitude could have significant impacts on food production and climate change. This was the largest scale assessment of hydropower potential conducted in irrigation networks to date with the next nearest being an assessment of 4,000 ha. Finally, an experimental hydropower plant using a pump-as-turbine was designed and constructed in an actual on-demand irrigation network to supply energy to a local farm in Southern Spain. A 4 kW pump-as-turbine was installed in a by-pass, recovering around 20 m of head and turbining 30 l s-1, connected to a bank of batteries that worked as backup for periods where no electricity generation was possible. The pilot plant was design using the methodologies developed in the earlier parts of the thesis. The plant supplied the energy demanded at the farm during the entire irrigation season, eliminating a diesel generator previously used to fulfil the energy demand. Significant benefits were achieved, exceeding 2,000 of economic savings and more than 8 t eCO2. Lastly, an analysis of two pump-as-turbine regulation schemes (hydraulic and electric), and the global efficiency of the plant were carried out. The results obtained in this research could lead to a more efficient plant designs and a better understanding of PAT performance working under actual conditions in irrigation networks. Thereby improving the plant power and global efficiency, and sustainability of energy sources applied to the agriculture sector.