Entries by Carl Berntsen

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Evaluation of Solar Photovoltaic Systems to Shade Cows in a Pasture-Based Dairy Herd

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.

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Electrical Consumption on Midwestern Dairy Farms in the United States and Agrivoltaics to Shade Cows in a Pasture-Based Dairy System

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.

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Agrivoltaic Systems Design and Assessment: A Critical Review, and a Descriptive Model towards a Sustainable Landscape Vision (Three-Dimensional Agrivoltaic Patterns)

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.

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Feasibility Study of a Blind-Type Photovoltaic Roof-Shade System Designed for Simultaneous Production of Crops and Electricity in a Greenhouse

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.

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Low-Cost Wireless Sensing System for Precision Agriculture Applications in Orchards

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.

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I-Solar, a Real-Time Photovoltaic Simulation Model for Accurate Estimation of Generated Power

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.

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Improving Productivity of Cropland Through Agrivoltaics

The concept of combining photovoltaics (PV) with agriculture (agrivoltaics or APV) is being explored across the globe and has established field trials in countries including, but not limited to, Germany, Vietnam, Italy, France, Japan and Chile. An agrivoltaic system involves positioning solar panels directly above or near active agricultural land to provide some form of shading to the crops and to generate electricity from the solar array. The usefulness of this concept is seen when considering the abundance of land that becomes available to the PV market if that land can be shared with the agricultural sector. For instance, consider that in 2016 Australia used 372 million hectares of land for agriculture, of which 8.3% was designated cropland. Therefore, even if some proportion of this cropland (say an 8th) are retrofitted with overhanging PV systems, Australia’s effective solar generation area would increase by roughly four million hectares. This would greatly enhance the renewable energy sectors ability to satisfy baseload energy requirements of the national grid. At first glance the concept of shading plants seems counterintuitive to the perception that cropland should be without obstructions. However, agrivoltaics recognises that crops do not require every hour of sunlight to photosynthesise. Consequently, the solar energy resource can effectively be shared with photovoltaic technology to increase the productivity of the land without greatly decreasing the yield of the crop, and in some cases, increasing crop yield. This is achieved by spacing the rows of solar panels in such a way that the shadows caused by the panels still permit crops to photosynthesise sufficiently in addition to reducing heat related stress caused by the environment. As such, 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).

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Development of a Decision Support System to Evaluate Crop Performance Under Dynamic Solar Panels

Achieving optimal yield and quality at harvest depends on the grower’s ability to avoid abiotic stresses (water, light, and temperature). This task has usually been satisfied through the implementation of adequate horticultural practices. In the context of clean energy transition and global climate change, growers nowadays have the possibility to grow their crops under solar panels, which modify the micro-environment of the crops. Being able to anticipate the behavior of plants under these new micro-environmental conditions would help growers adapt their horticultural practices. For electricity producers, in the context of dynamic agrivoltaic systems, anticipating the crop status is useful to choose a solar panels steering policy that maximizes electricity production while ensuring favorable environmental conditions for the crop to grow. To help electricity producers and growers estimate a crop status under panels, we developed a decision support system (DSS) called crop_sim. As of now, it can be used to monitor two types of perennial crops: grapevines and apple trees. crop_sim produces three indicators of the crop status: predawn water potential, canopy temperature and carbon production. Besides providing information on the crop status, the DSS incorporates an expert system which indicates the best time and the amount of irrigation to maintain a desired water status under the new micro-environmental conditions. This paper first focuses on the description of crop_sim and the usefulness of the three indicators. Then, a case study is presented. Our results show 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 are being collected. They will be used to adapt the model to tomato and maize, evaluate it and make it robust enough to bring to market. Further improvements of the crop_sim model may be required to finely reproduce observations in the field. A full validation of the model is expected when all data from the experiments will be available. The DSS will evolve depending on the requirements of the agrivoltaics community and may incorporate additional plant indicators and new expert system rules.

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Design of a UGV Powered by Solar Energy for Precision Agriculture

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. Moreover, Agri.q mounts an orientable landing platform for drones which is made of solar panels, enabling multi-robot strategies and solar power storage, with a view to sustainable energy. In fact, the device will assume a central role in a more complex automated system for agriculture, that includes the use of UAV (unmanned aerial vehicle) and UGV for coordinated field monitoring and servicing. The platform is covered with photovoltaic panels useful to recharge a 12 V battery that gives power to the system. A positioning device permits to orient the platform so to keep it horizontal above the ground or to optimize the sunlight collection process. A seven DOFs manipulator is mounted on the rover and can be placed in different positions on the UGV depending on the task that it has to perform. The solution adopted to mount the robotic arm on the rover is discussed and indexes to evaluate the performances of the mounting system in terms of augmentation of the robotic workspace are presented. The mechatronic system architecture is also reported and finally the first prototype is shown in different meaningful configurations. Future studies will consider the integration of vision sensors on the prototype and will analyze Agri.q02 capabilities in a real vineyard scenario. Moreover, the software package for the autonomous guide and manipulation tasks will be developed.

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A Transdisciplinary Analysis of Just Transition Pathways to 100% Renewable Electricity

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.