Journal
ENVIRONMENTAL IMPACT ASSESSMENT REVIEW
Volume 86, Issue -, Pages -Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.eiar.2020.106496
Keywords
Smart farming; Agriculture; Consumption of energy; Technological innovation; Renewable energy supply; Environment
Categories
Funding
- Key R&D projects of science and Technology Department of Jilin Province [20200402003NC]
- Doctoral Research Initiation Funding Project of Jilin Engineering Normal University [BSSK201805]
- Research results of Jilin Social Science Fund Project [2020B045]
- Program for Innovative Research Team of Jilin Engineering Normal University
- Science and Technology Department of Jilin Province soft science project [20190601022FG]
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This paper proposes the idea of merging smart farms with renewable energy and demonstrates the framework to connect a smart farm energy system and analyze its feasibility and advantages. Using Reactive Energy Utilization Technology to predict the optimal wind power scenario in the smart farm, it achieves better renewable energy consumption, accuracy, and efficiency.
Over the decades, both agriculture and energy grids have encountered significant challenges, such as the lack of power supply to agricultural farms and the difficulties of renewable energy use in the electricity sector. To overcome and address these issues, this paper presents an idea of merging smart farm and renewable energy, using surplus renewable energy for the agriculture sector using the smart farm for renewable energy supplies. First, demonstrate the framework to connect a smart farm energy system and analyze its feasibility and advantages. In this paper, Reactive Energy Utilization Technology (REUT) has been used as an efficient energy consumption system for the smart farm. It is used to predict the optimum wind power scenario in the smart farm by monitoring continuous control variables, with the lowest voltage reached in each scenario, and minimized actual total power losses. A combined system consisting of smart farming production, as well as renewable energy consumption, has been evaluated in experimental results. Experimental results and discussion shows that the proposed method has better renewable energy consumption, accuracy(96.7%), and efficiency(95.6%) for smart farming.
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