Optimal reservoir sizing in on-demand irrigation networks: Application to a collective drip irrigation network in Spain

Izquiel, A.; Ballesteros, Rocío; Tarjuelo, J.M.; Moreno, M.

doi:10.1016/j.biosystemseng.2016.04.003

Cited by 5 publications

(3 citation statements)

References 17 publications

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“…The energy consumption in irrigation agriculture has exponentially increased in recent years due to the modernisation of irrigation systems, from surface irrigation to pressurised irrigation [12,13]. It is necessary to find more efficient alternatives [14], mainly in areas with high energy demand, such as irrigable areas with underground water resources, where the extraction cost can reach up to 70% of the total energy cost of irrigation [15]. One of the possible alternatives to decrease the water extraction and application costs is the integration of photovoltaic energy [3,[16][17][18].…”

Section: Introductionmentioning

confidence: 99%

I-Solar, a Real-Time Photovoltaic Simulation Model for Accurate Estimation of Generated Power

2021

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Global energy consumption and costs have increased exponentially in recent years, accelerating the search for viable, profitable, and sustainable alternatives. Renewable energy is currently one of the most suitable alternatives. The high variability of meteorological conditions (irradiance, ambient temperature, and wind speed) requires the development of complex and accurate management models for the optimal performance of photovoltaic systems. The simplification of photovoltaic models can be useful in the sizing of photovoltaic systems, but not for their management in real time. To solve this problem, we developed the I-Solar model, which considers all the elements that comprise the photovoltaic system, the meteorologic conditions, and the energy demand. We have validated it on a solar pumping system, but it can be applied to any other system. The I-Solar model was compared with a simplified model and a machine learning model calibrated in a high-power and complex photovoltaic pumping system located in Albacete, Spain. The results show that the I-Solar model estimates the generated power with a relative error of 7.5%, while the relative error of machine learning models was 5.8%. However, models based on machine learning are specific to the system evaluated, while the I-Solar model can be applied to any system.

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Section: Introductionmentioning

confidence: 99%

I-Solar, a Real-Time Photovoltaic Simulation Model for Accurate Estimation of Generated Power

2021

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“…After the effectiveness comparisons and influence analysis of R ms , T i , T c , T e , R s , and S l were completed, the ANFIS evaluations for flow properties and SIE compared with the measured ones are illustrated and discussed in Figure 9a-9f, as two solid lines in these figures identify the error range of ±10% for different SIE indexes [55,56] . For example, the ANFIS evaluation of Figures 10a-10h illustrate the distributive comparisons between the actual-measured and ANFIS-evaluated SIE indexes on a given irrigated area when different irrigation network being applied, as IFR II , AWIE III , TL IV , and IDS V are enumerated sequentially as representative examples, a high consistence between them can be learned, thus the computational precision of ANFIS evaluation can be ensured and a remarkable promotion in moisture infiltration equilibrium can be achieved.…”

Section: Results and Analysismentioning

confidence: 99%

Influence analysis of sprinkler irrigation effectiveness using ANFIS

Liang

Liu

Wen

et al. 2019

International Journal of Agricultural and Biological Engineering

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In order to improve sprinkler irrigation quality and promote actual irrigation efficiency, the influence analysis of sprinkler irrigation effectiveness (SIE) using ANFIS (Adaptive Neural Fuzzy Inference System) was implemented to balance moisture infiltration and water redistribution in soil field. Firstly, using a detailed description of governing equations proposed for sprinkler irrigation flow, the theoretical foundation and mathematical model of irrigation effectiveness can be established; Secondly, based on a complete preparation of experimental irrigation conditions, a series of calibration indexes quantifying SIE for sprinkler irrigation quality and infiltration efficiency were proposed; Then thirdly, a novel ANFIS system was designed and introduced to evaluate these key effectiveness indexes in actual working operations, so that a series of detailed influence analysis and comprehensive infiltration assessment focusing on sprinkler irrigation effectiveness could be achieved afterwards, which result to the realization of better infiltration equilibrium and higher water redistribution efficiency in actual irrigation test. Therefore, the qualification of sprinkler irrigation effectiveness was achieved, and in addition, the moisture infiltration improvement and soil moisture uniformity were facilitated also in return.

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“…Great effort has been made in the generation of photovoltaic simulation models [9,[16][17][18][19][20], including energy generation forecasts [21]. Furthermore, there are many models for the hydraulic modeling of irrigation systems [5,[22][23][24][25][26], large-scale water distribution networks [5,24,[27][28][29] and pumping systems [6,[30][31][32]. Several models that integrate water delivery systems with photovoltaic modeling have also been developed [9,[33][34][35][36][37], as well as control algorithms for the integrated management of photovoltaic and hydraulic models [38].…”

Section: Introductionmentioning

confidence: 99%

EVASOR, an Integrated Model to Manage Complex Irrigation Systems Energized by Photovoltaic Generators

et al. 2020

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The carbon footprint and energy cost of irrigation are increasing due to the modernization of irrigation systems, which also necessitates highly efficient use of water resources. Alternatives to conventional energy sources to power irrigation systems are renewable sources, primarily photovoltaic energy. Photovoltaic energy has the main disadvantage of producing a highly variable amount of energy, which affects the irrigation uniformity. Modeling irrigation systems in an integrated manner generates useful information about system performance for technicians that helps in the decision-making process. The EVASOR (EVAluation of SOlar iRrigation systems) model integrates different modules to simulate the whole solar irrigation system using a holistic approach: (1) I-Solar, which simulates the instantaneous power generated by the photovoltaic system, (2) AS-Solar, which simulates the variable speed pumping system, (3) Solar-Net, which simulates the hydraulic performance of the water distribution network, and (4) PRESUD-Irregular, which determines the discharge and pressure of all the emitters of the subunits together with irrigation quality parameters (coefficient of uniformity (CU), emission uniformity (EU), and coefficient of variation of the emitter discharge in the subunit (CVq) for any pressure at the subunit inlet. The integrated model EVASOR determines the irrigation quality parameters of complex irrigation systems with information on irradiance, air temperature, wind speed, and water table level for any combination of open subunits. To validate the model, results are presented regarding a case study located in southeast Spain.

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Optimal reservoir sizing in on-demand irrigation networks: Application to a collective drip irrigation network in Spain

Cited by 5 publications

References 17 publications

I-Solar, a Real-Time Photovoltaic Simulation Model for Accurate Estimation of Generated Power

I-Solar, a Real-Time Photovoltaic Simulation Model for Accurate Estimation of Generated Power

Influence analysis of sprinkler irrigation effectiveness using ANFIS

EVASOR, an Integrated Model to Manage Complex Irrigation Systems Energized by Photovoltaic Generators

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