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.
The rapid increase of photovoltaic installations highlights the potential of agrivoltaic systems. These dual-land use systems mitigate land use conflicts for places with limited open space and moreover, show the potential as an added value in crop- and livestock cultivation. The many different names and interacting possibilities between agriculture and PV make it difficult and confusing for stakeholders to compare and benchmark existing installations as well as propose and set new (EU) legislation schemes. This work proposes a standardized classification (including names) of agrivoltaic systems, which is usable worldwide. The classification is based on the application, system, the farming type, PV structure and flexibility. These elements makes it possible to describe and categorize each existing agrivoltaic installation properly. This work suggests to mention each sub-category (for example: static stilted orchard agrovoltaic system) in future research papers or documents to order to better compare (rangevoltaic <=> agrovoltaic) and benchmark new installed installations. When comparing agrivoltaics, the use of the proposed seven KPIs will help to make meaningful comparisons and grounded decisions in case of possible new installations.
A system combining soil grown crops with photovoltaic panels (PV) installed several meters above the ground is referred to as agrivoltaic systems. In this work a patented agrivoltaic solar tracking system named Agrovoltaico®, was examined in combination with a maize crop in a simulation study. To this purpose a software platform was developed coupling a radiation and shading model to the generic crop growth simulator GECROS. The simulation was conducted using a 40-year climate dataset from a location in North Italy, rainfed maize and different Agrovoltaico configurations (that differ according to panel density and sun-tracking set up). Control simulations for an irrigated maize crop under full light were added to results. Reduction of global radiation under the Agrovoltaico system was more affected by panel density (29.5% and 13.4% respectively for double density and single density), than by panel management (23.2% and 20.0% for suntrack and static panels, respectively). Radiation reduction, under Agrovoltaico, affected mean soil temperature, evapotranspiration and soil water balance, on average providing more favorable conditions for plant growth than in full light. As a consequence, in rainfed conditions, average grain yield was higher and more stable under agrivoltaic than under full light. The advantage of growing maize in the shade of Agrovoltaico increased proportionally to drought stress, which indicates that agrivoltaic systems could increase crop resilience to climate change. The benefit of producing renewable energy with Agrovoltaico was assessed using the Land Equivalent Ratio, comparing the electric energy produced by Agrovoltaico cultivated with biogas maize to that produced by a combination of conventional ground mounted PV systems and biogas maize in monoculture. Land Equivalent Ratio was always above 1, it increased with panel density and it was higher with sun tracking than with static panels. The best Agrivoltaico scenario produced twice as much energy, per unit area, as the combination of ground mounted PV systems and biogas maize in monoculture. For this Agrivoltaico can be considered a valuable system to produce renewable energy on farm without negatively affecting land productivity.
Researchers present here a novel ecosystems approach—agrivoltaics—to bolster the resilience of renewable energy and food production security to a changing climate by creating a hybrid of colocated agriculture and solar PV infrastructure, where crops are grown in the partial shade of the solar infrastructure. They suggest that this energy- and food-generating ecosystem may become an important—but as yet quantitatively uninvestigated—mechanism for maximizing crop yields, efficiently delivering water to plants and generating renewable energy in dryland environments. We demonstrate proof of concept for agrivoltaics as a food–energy–water system approach in drylands by simultaneously monitoring the physical and biological dimensions of the novel ecosystem. We hypothesized that colocating solar and agricultural could yield several significant benefits to multiple ecosystem services, including (1) water: maximizing the efficiency of water used for plant irrigation by decreasing evaporation from soil and transpiration from crop canopies, and (2) food: preventing depression in photosynthesis due to heat and light stress, thus allowing for greater carbon uptake for growth and reproduction. An additional benefit might be (3) energy: transpirational cooling from the understorey crops lowering temperatures on the underside of the panels, which could improve PV efficiency. We focused on three common agricultural species that represent different adaptive niches for dryland environments: chiltepin pepper (Capsicum annuum var. glabriusculum), jalapeño (C. annuum var. annuum) and cherry tomato (Solanum lycopersicum var. cerasiforme). We created an agrivoltaic system by planting these species under a PV array—3.3m off the ground at the lowest end and at a tilt of 32°—to capture the physical and biological impacts of this approach. Throughout the average three-month summer growing season we monitored incoming light levels, air temperature and relative humidity continuously using sensors mounted 2.5m above the soil surface, and soil surface temperature and moisture at 5-cm depth. Both the traditional planting area (control) and agrivoltaic system received equal irrigation rates, and we tested two irrigation scenarios—daily irrigation and irrigation every 2d. The amount of incoming photosynthetically active radiation (PAR) was consistently greater in the traditional, open-sky planting area (control plot) than under the PV panels. This reduction in the amount of incoming energy under the PV panels yielded cooler daytime air temperatures, averaging 1.2+0.3 °C lower in the agrivoltaics system over the traditional setting. Night-time temperatures were 0.5+0.4 °C warmer in the agrivoltaics system over the traditional setting (Fig. 2b). Photosynthetic rates, and therefore growth and reproduction, are also regulated by atmospheric dryness, as represented by vapour pressure deficit (VPD) where lower VPD indicates more moisture in the air. VPD was consistently lower in the agrivoltaics system than in the traditional growing setting, averaging 0.52+0.15 kPa lower across the growing season. Having documented that an agrivoltaic installation can significantly reduce air temperatures, direct sunlight and atmospheric demand for water relative to nearby traditional agricultural settings, we address several questions regarding impacts of the food–energy–water nexus system.
Community solar is an innovative new investment model that can provide Americans with the many benefits of solar energy even if they cannot site a system on their own property because they are renters, have roofs that are shaded or in disrepair, or they are not able to finance a solar installation. These barriers are particularly prevalent in less affluent areas, making community solar a promising way to improve access to renewable energy in low-income neighborhoods. This Handbook is intended to help municipalities clearly define and articulate the project’s objectives and understand the financial, legal, and policy issues they would need to address to initiate community solar investments in their communities and convey the resulting benefits to their constituents. The Handbook identifies three obstacles to success — access to capital, expertise, and risk-allocation — and includes suggestions on how to overcome these obstacles, including the potential use of public funds to reduce the project’s cost and public-private partnerships. This study also includes ideas gleaned from other community solar projects that appear particularly interesting or innovative. In addition, it offers five possible deployment models municipalities could use to support, finance, or build a community solar project in their jurisdictions. There are no simple, one-size-fits-all, models for a successful community solar project. However, a municipality can be a catalyst and hub for development of the necessary expertise, and it has opportunities to help reduce project costs and risks that can open the door for successful projects.
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