首页|Evaluating the use of meteorological predictions in directly pumped irrigational operations using photovoltaic energy
Evaluating the use of meteorological predictions in directly pumped irrigational operations using photovoltaic energy
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NSTL
Elsevier
? 2022 Elsevier B.V.The modernization process in irrigation has generated a higher energy demand. Due to this problem, the ongoing increase in energy tariffs, and the reduction in manufacturing costs of photovoltaic (PV) panels, there has been an increased use of renewable energies, such as PV energy, to power the pumping equipment involved in pressurized irrigation. On direct pumping, the available solar power can be lower than that required by the pumping units. This fact can result in stoppages that can produce unwanted transient effects or even the emptying of the network. To avoid these phenomena and reduce the use of conventional energy, a methodology is proposed in this work, whereby meteorological predictions, corrected with a Kalman filter, are used to calculate the available PV power, irrigation needs, and maintaining soil moisture above desirable levels for the crop by minimizing deep percolation. This methodology is then compared to the traditional scheduling method that uses historical data and replaces the crop′s evapotranspiration that occurs in a given time period. The methodology was applied to a real case study during an irrigation campaign, which was simulated using a weekly operative period. It was found that the use of meteorological predictions allowed PV energy consumption estimates to be improved from 68.7% to 79.3%, while the use of available photovoltaic energy in the case study increased from 11.64% to 13.37%.
Energy availabilityPhotovoltaic irrigationPrecision irrigationPredicting irrigation needsPVOI
Carricondo-Anton J.M.、Manzano Juarez J.、Royuela Tomas A.、Jimenez-Bello M.A.、Sala A.
展开 >
Centro Valenciano de Estudios sobre el Riego (CVER) Universitat Politècnica de València
Instituto de Ingeniería del Agua y del Medio Ambiente (IIAMA) Universitat Politècnica de València
Instituto Universitario de Automática e Informática Industrial (AI2) Universitat Politècnica de València
NSTL
Elsevier
