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Emulation of Energy Scheduling for an Agriculture Irrigation System Considering Field Data

机译:考虑田间数据的农业灌溉系统能量调度仿真

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As the global population is daily soaring, the need for water and energy is also increasing. This makes the role of the agriculture sector more tangible. Water and energy efficiency in this sector is still very low, and the need for smart management and strategic planning are obvious. This paper proposes an autonomous approach to increase the efficiency of energy and water consumption in the agriculture irrigation process. The model contains local renewable energy resources to supply the irrigation electricity demand. In the previous works developed by the authors, the irrigation scheduling had been performed by a decision tree approach. however, in this paper, the model schedules irrigation according to the realtime field data as well as the availability of the local resources to minimize operational costs. The system also includes a laboratory demonstration to test the scheduling process under practical challenges. A case study is also shown to validate the model, and its results show a gap between expected and real results. Nevertheless, the results proved the functionality and applicability of the proposed model.
机译:随着全球人口的日增,对水和能源的需求也在增加。这使农业部门的作用更加明显。该部门的水和能源效率仍然很低,对智能管理和战略规划的需求显而易见。本文提出了一种自主的方法来提高农业灌溉过程中的能源和水消耗效率。该模型包含本地可再生能源,用于满足灌溉用电需求。在作者以前的工作中,灌溉计划是通过决策树方法执行的。然而,在本文中,该模型根据实时现场数据以及本地资源的可用性来安排灌溉时间,以最大程度地降低运营成本。该系统还包括一个实验室演示,以在实际挑战下测试调度过程。还显示了一个案例研究来验证该模型,其结果表明预期结果与实际结果之间存在差距。然而,结果证明了所提出模型的功能性和适用性。

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