The combined use of solar photovoltaics and agriculture may provide farmers with an alternative source of income and reduce heat stress in dairy cows. The objective of this study was to determine the effects on grazing cattle under shade from a solar photovoltaic system. The study was conducted at the University of Minnesota West Central Research and Outreach Center in Morris, Minnesota on a grazing dairy. Twenty-four crossbred cows were randomly assigned to 2 treatment groups (shade or no shade) from June to September in 2019. The replicated (n = 4) treatment groups of 6 cows each were provided shade from a 30-kW photovoltaic system. Two groups of cows had access to shade in paddocks, and 2 groups of cows had no shade in paddocks. All cows were located in the same pasture during summer. Behavior observations and milk production were evaluated for cows during 4 periods of summer. Boluses and an eartag sensor monitored internal body temperature, activity, and rumination on all cows, respectively. Independent variables were the fixed effects of breed, treatment group, coat color, period, and parity, and random effects were replicate group, date, and cow. No differences in fly prevalence, milk production, fat and protein production, or drinking bouts were observed between the treatment groups. Shade cows had more ear flicks (11.4 ear flicks/30 s) than no-shade cows (8.6 ear flicks/30 s) and had dirtier bellies and lower legs (2.2 and 3.2, respectively) than no-shade cows (1.9 and 2.9, respectively). During afternoon hours, shade cows had lower respiration rates (66.4 breaths/min) than no-shade cows (78.3 breaths/min). From 1200 to 1800 h and 1800 to 0000 h, shade cows had lower body temperature (39.0 and 39.2°C, respectively) than no-shade cows (39.3 and 39.4°C, respectively). Furthermore, between milking times (0800 and 1600 h), the shade cows had lower body temperature (38.9°C) than no-shade cows (39.1°C). Agrivoltaics incorporated into pasture dairy systems may reduce the intensity of heats stress in dairy cows and increase well-being of cows and the efficiency of land use.
The objectives of the thesis were to investigate electrical energy use on dairy farms located in west central Minnesota and to evaluate the effects of shade use by cattle from solar photovoltaic systems. As the push for sustainable food production from consumers continues to grow, food industries and processors are looking for ways they can be more marketable to consumers. Not only do food industries investigate sustainable practices within their own systems, they also push their suppliers to explore ways to lower their farms’ carbon footprints. Measurements of baseline fossil fuel consumption within dairy production systems are scarce. Therefore, there is a need to discern where and how fossil fuel-derived energy is being used within dairy production systems. Baseline energy use data collection is the first step in addressing the demand for a reduced carbon footprint within dairy production systems. Energy use on five Midwest dairy farms was evaluated from July 2018 to December 2019. Through in-depth monitoring of electricity-consuming processes, it was found that electricity use can differ quite drastically in different types of milking systems and farms. Electricity on an annual basis per cow ranged from 400 kWh/cow in a low-input and grazing farm to 1,145 kWh/cow in an automated milking farm. To reduce electrical energy consumption as well as reduce the effects of heat stress in pastured dairy cows, producers may investigate using an agrivoltaic system. Biological effects of internal body temperature, milk production, and respiration rates and behavioral effects of activity, rumination, fly avoidance behaviors, and standing and lying time of the solar shade were evaluated. Treatment groups were shade or no shade of cattle on pasture. The results of this agrivoltaic system suggested that grazing cattle that have access to shade had lower respiration rates and lower body temperatures compared to cattle that do not have access to shade. Electricity used in dairy farms was examined to help producers find areas in their farms that have the potential for reduced energy consumption. Furthermore, the use of an agrivoltaic system on a pasture-based dairy was studied for its shading effects on the health and behavior of dairy cows.
As an answer to the increasing demand for photovoltaics as a key element in the energy transition strategy of many countries—which entails land use issues, as well as concerns regarding landscape transformation, biodiversity, ecosystems and human well-being—new approaches and market segments have emerged that consider integrated perspectives. Among these, agrivoltaics is emerging as very promising for allowing benefits in the food–energy (and water) nexus. Demonstrative projects are developing worldwide, and experience with varied design solutions suitable for the scale up to commercial scale is being gathered based primarily on efficiency considerations; nevertheless, it is unquestionable that with the increase in the size, from the demonstration to the commercial scale, attention has to be paid to ecological impacts associated to specific design choices, and namely to those related to landscape transformation issues. This study reviews and analyzes the technological and spatial design options that have become available to date implementing a rigorous, comprehensive analysis based on the most updated knowledge in the field, and proposes a thorough methodology based on design and performance parameters that enable us to define the main attributes of the system from a trans-disciplinary perspective. The energy and engineering design optimization, the development of new technologies and the correct selection of plant species adapted to the PV system are the areas where the current research is actively focusing in APV systems. Along with the continuous research progress, the success of several international experiences through pilot projects which implement new design solutions and use different PV technologies has triggered APV, and it has been met with great acceptance from the industry and interest from governments. It is in fact a significant potential contribution to meet climate challenges touching on food, energy, agriculture and rural policies. Moreover, it is understood—i.e., by energy developers—as a possible driver for the implementation of large-scale PV installations and building integrated agriculture, which without the APV function, would not be successful in the authorization process due to land use concerns. A sharp increase is expected in terms of number of installations and capacity in the near future. Along this trend, new concerns regarding landscape and urban transformation issues are emerging as the implementation of APV might be mainly focused on the efficiency of the PV system (more profitable than agriculture), with insufficient attention on the correct synergy between energy and food production. The study of ecosystem service trade-offs in the spatial planning and design for energy transition, to identify potential synergies and minimize trade-offs between renewable energy and other ecosystem services, has been already acknowledged as a key issue for avoiding conflicts between global and local perspectives. The development of new innovative systems (PV system technology) and components (photovoltaic devices technology) can enhance the energy performance of selected design options for APV greenhouse typology.
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.
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