Energy-saving design and control strategy towards modern sustainable greenhouse: A review

Zhang, Menghang; Yan, Tingxiang; Wang, Wei; Jia, Xuexiu; Wang, Jin; Klemeš, Jiří Jaromír

doi:10.1016/j.rser.2022.112602

Cited by 54 publications

(15 citation statements)

References 167 publications

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“…In the recent decade, many ways of combining crop growing with PV power production in the same greenhouse structure have been documented in the literature (e.g. Zhang et al 2022;Magadley et al 2022). Agrivoltaic systems can help meet the growing need for food and energy while also reducing water usage.…”

Section: Greenhouse Agrivoltaics In Protected Cultivationmentioning

confidence: 99%

A review study on the design and control of optimised greenhouse environments

Chimankare,

Das,

Kaur

et al. 2023

J. Trop. Ecol.

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Greenhouses are inflated structures with transparent covering that are used to grow crops under controlled climatic conditions. Crops are protected from extreme climate-related events by being enclosed. Furthermore, the greenhouse design ratio impacts the temperature and humidity distribution profile uniformity as well as the greenhouse. As a result, by effectively designing the greenhouse structure, building materials, dimensions, and shapes, the cost of cooling management strategies can be reduced. Structures with changed arch shapes showed to be more effective at reducing greenhouse cooling demands in hot areas. To demonstrate the tropical region’s inherent capabilities for generating a proper atmosphere for plant development, the optimal temperature, humidity, light, and PH for greenhouse production of crops were supplied. Greenhouse cooling systems are dominated by local environmental characteristics that have an immediate impact on their indoor climatic conditions. Photovoltaic systems in greenhouses have proven technological capacity in real-world settings in this area. This could increase the energy efficiency of some agrivoltaic greenhouse design options.

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Section: Greenhouse Agrivoltaics In Protected Cultivationmentioning

confidence: 99%

A review study on the design and control of optimised greenhouse environments

Chimankare,

Das,

Kaur

et al. 2023

J. Trop. Ecol.

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“…conditions in greenhouses vary with the external environment and plant growth. Therefore, a proper monitoring system is a prerequisite for achieving the optimal climatic conditions needed for greenhouse crops [2]. Internet of Things technology can utilize sensors to monitor and control the growing environment of crops.…”

Section: Introductionmentioning

confidence: 99%

Piezoelectric breeze energy harvester with mechanical intelligence mechanism for smart agricultural monitoring systems

Zheng,

Han,

Yang

et al. 2024

Smart Mater. Struct.

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In this paper, a piezoelectric breeze energy harvester with a mechanical intelligence mechanism for smart agricultural monitoring systems (G-PBEH) is proposed. Different from the conventional magnetically coupled piezoelectric cantilever beam harvesters where the end magnet is mostly fixed, the G-PBEH has movable magnets in a fixed cylindrical channel. Which could achieve a mechanical intelligence mechanism with the tuned magnets on the shell, contributing to increasing voltage frequency and widening wind bandwidth. The effects of cylindrical channel length (L) and tuned magnet diameter (D) on performance were investigated. The experimental findings reveal that when L is 10 mm and D is 8 mm, the prototype starts at 2 m/s, and the highest voltage and power are 17.9 V and 944.07 μW (150 kΩ) at 8 m/s. Compared to L is 5 mm (magnet fixed), the voltage waveform has a 28.6% increase in the quantity of peaks. Besides, the voltage is larger than 3 V occupying 91.6% of the experimental wind bandwidth. The application experiment demonstrates that the G-PBEH can be used as a reliable power supplier, which can facilitate the progress of smart monitoring systems for simplified greenhouses in remote areas.

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“…Solar greenhouses are designed to insulate heat and increase production 1 , 2 . In recent years, the area of greenhouses in China has continued to expand 3 , 4 . As of 2020, greenhouses covered 340 hectares, 90% of which are solar greenhouses located in northern China 5 .…”

Section: Introductionmentioning

confidence: 99%

Temperature prediction of solar greenhouse based on NARX regression neural network

Gao

et al. 2023

Sci Rep

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Temperature has an important influence on plant growth and development. In protected agriculture production, accurate prediction of temperature environment is of great significance. However, due to the time series, nonlinear and multi coupling characteristics of temperature, it is difficult to achieve accurate prediction. We proposed a method for building a solar greenhouse temperature prediction model based on a timeseries analysis, that considers the time series characteristics and dynamic temperature changes in the greenhouse system. The method would predict the temperature of greenhouse, and provide reference for the temperature change law in protected agriculture. A parameter analysis was performed on the nonlinear autoregressive exogenous (NARX) neural network, and a solar greenhouse temperature time series prediction model was established using the NARX regression neural network. The results showed that the proposed model depicted a maximum absolute error of 0.67 °C, and model correlation coefficient of 0.9996. Compared with the wavelet and BP neural networks, the NARX regression neural network accurately predicted and significantly outperformed in the solar greenhouse temperature prediction model. Moreover, the prediction model can accurately predict temperature trends within the solar greenhouse and is pivotal to obtaining precise control of solar greenhouse temperature.

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Energy-saving design and control strategy towards modern sustainable greenhouse: A review

Cited by 54 publications

References 167 publications

A review study on the design and control of optimised greenhouse environments

A review study on the design and control of optimised greenhouse environments

Piezoelectric breeze energy harvester with mechanical intelligence mechanism for smart agricultural monitoring systems

Temperature prediction of solar greenhouse based on NARX regression neural network

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