The use of renewable energy in modern greenhouse management is important to achieve efficient and sustainable food supplies for a world with increasing population. This study assessed the performance of a blind-type shading regulator that can automatically rotate semi-transparent photovoltaic (PV) blades installed on the greenhouse roof in response to sunlight variation. The PV blind oriented parallel to the roof partially blocked intense sunlight penetration into the greenhouse, but it transmitted sunlight during cloudy time by turning the blind bearing to be perpendicular to the roof. A stable irradiation environment is therefore producible in the greenhouse under variable sky conditions. Annual operations demonstrated that the blinds’ own generated electrical energy can sustain PV blind operation and produce surplus electrical energy. The PV blind electricity generation and sunlight availability for crops below the PV blind roof were calculated based on a mathematical model developed using theoretical sunlight parameters and the experimentally obtained PV blind system parameters. Assuming cloudless skies and threshold irradiance for blind rotation set at 500 W m−2, 13.0 and 12.3kWh m−2 yr−1 surplus electrical energy can be generated, respectively, by north–south and east–west oriented model greenhouses. Cloudy skies reduce surplus electrical energy production by 50%, but PV blinds can supply greenhouse electrical energy demands partially or completely, depending on the degree of greenhouse electrification. Below the PV blinds, 8–10 MJ m−2 day−1 of insolation is expected to irradiate crops under actual sky conditions. This insolation is sufficient to cultivate major horticultural crops. Regulating the threshold irradiance level for PV blind turning can control the sunlight apportionment ratio for cultivation and electricity generation, thereby enabling sustainable energy–food dual production in a greenhouse.

Wireless sensor networks (WSNs) can be reliable tools in agricultural management. In this work, a low cost, low power consumption, and simple wireless sensing system dedicated for agricultural environments is presented. The system is applicable to small to medium sized fields, located anywhere with cellular network coverage, even in isolated rural areas. The novelty of the developed system lies in the fact that it uses a dummy device as Coordinator which through simple but advanced programming can receive, process, and send data packets from all End-notes to the cloud via a 4G cellular network. Furthermore, it is energy independent, using solar energy harvesting panels, making it feasible to operate in remote, isolated fields. A star topology was followed for the sake of simplification, low energy demands and increased network reliability. The developed system was tested and evaluated in laboratory and real field environment with satisfactory operation in terms of independence, and operational reliability concerning packet losses, communication range (>250m covering fields up to 37ha), energy autonomy, and uninterrupted operation. The network can support up to seven nodes in a 30 min data acquisition cycle. These results confirmed the potential of this system to serve as a viable option for monitoring environmental, soil, and crop parameters.

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 meteorological 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.

This study aims to review existing literature about agrivoltaics and use experimentation to explore if the advantages they provide are great enough to justify their introduction into Australian agriculture. A key parameter for this study is land productivity that is measured using “land equivalent ratio” (LER) which is a combination of crop yield (measured in kilograms) and energy production (measured in watt-hours).

This case study shows that, in a mature vineyard, with a typical panel steering policy conservative on crop yield, growers could save 13% of water compared to an open-field reference. Experimental data pertaining to apple trees, grapevines, tomatoes, and maize were collected in this study.

In this paper, a novel UGV (unmanned ground vehicle) for precision agriculture, named “Agri.q,” is presented. The Agri.q has a multiple degrees of freedom positioning mechanism and it is equipped with a robotic arm and vision sensors, which allow to challenge irregular terrains and to perform precision field operations with perception. In particular, the integration of a 7 DOFs (degrees of freedom) manipulator and a mobile frame results in a reconfigurable workspace, which opens to samples collection and inspection in non-structured environments.

The transition to using clean, affordable, and reliable electrical energy is critical for enhancing human opportunities and capabilities. In the United States, many states and localities are engaging in this transition despite the lack of ambitious federal policy support. This research builds on the theoretical framework of the multilevel perspective (MLP) of sociotechnical transitions as well as the concept of energy justice to investigate potential pathways to 100 percent renewable energy (RE) for electricity provision in the U.S. This research seeks to answer the question: what are the technical, policy, and perceptual pathways, barriers, and opportunities for just transition to 100% renewable electricity in the U.S., at a state and local levels? In this dissertation, an analysis of factors contributing to RE transition in communities across the country is developed. Results from this are used to make further analysis and recommendations to research undertaken specifically in the context of Michigan’s Western Upper Peninsula (WUP). This dissertation demonstrates that research on achieving a just energy transition requires transdisciplinary approaches that integrate social sciences, engineering, and natural sciences and multiple ways of knowing from scientists, practitioners, and diverse community perspectives. This research provides tools for decision makers at all levels of government, local stakeholders, citizens, and the academic world in understanding what matters for success in a just transition to 100% RE in the U.S.

This paper presents solar-powered irrigation systems (SPIS) as a clean energy option for agriculture and rural electrification. Included is an overview of practice for SPISs, including how the sustainability of SPIS greatly depends on how water resources are managed.  

 

This paper proposes a solution for the present energy crisis for Indian farmers. It introduces a system consisting of a solar-powered water pump along with an automatic water flow control using a moisture sensor. This system could be applied to AgriSolar operations that required water pumping for various applications on a farm operation.

This paper presents the design of a solar tracking system via LDR sensor values to harness maximum solar energy that is converted into electrical energy which in turn is used to power the irrigation system. This system can be applied in AgriSolar operations where irrigation systems are included.