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Agriculture sector is backbone of each country. Nowadays the energy efficiency in this sector is at a very low level, which shows the necessity of more investments in this regard. By appearance of smart grid technologies, some new concepts were also appeared in the agriculture sector, such as smart farm, and smart agriculture. This paper provides an energy management system for an agriculture field equipped with renewable energy resources and a river turbine. A decision tree is developed in this paper to schedule and optimize the use of energy resources for reducing the electricity costs. Decision tree method enables the system to obtain optimal scheduling of energy resources in offline mode, without using any external server/machine or internet access. A case study validates the performance of developed decision tree, and the errors and accuracy of all gained results are discussed.
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Agriculture sector is backbone of each country. Nowadays the energy efficiency in this sector is at a very low level, which shows the necessity of more investments in this regard. By appearance of smart grid technologies, some new concepts were also appeared in the agriculture sector, such as smart farm, and smart agriculture. This paper provides an energy management system for an agriculture field equipped with renewable energy resources and a river turbine. A decision tree is developed in this paper to schedule and optimize the use of energy resources for reducing the electricity costs. Decision tree method enables the system to obtain optimal scheduling of energy resources in offline mode, without using any external server/machine or internet access. A case study validates the performance of developed decision tree, and the errors and accuracy of all gained results are discussed.
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