The researchers in this study aimed to simulate crop yields for paddy rice, barley, and soybeans grown under photovoltaic panels with an eye on reaching suitable agricultural productivity for the energy and food nexus coexistence. They also applied a geospatial crop simulation modeling system to stimulate the regional variations in crop yield according to solar radiation reduction scenarios.
In this paper, an integrated methodology is developed to determine optimum areas for Photovoltaic (PV) installations that minimize the relevant visual disturbance and satisfy spatial constraints associated with land use, as well as environmental and techno-economic siting factors. The visual disturbance due to PV installations is quantified by introducing and calculating the “Social Disturbance” (SDIS) indicator, whereas optimum locations are determined for predefined values of two siting preferences (maximum allowable PV locations—grid station distance and minimum allowable total coverage area of PV installations). Thematic maps of appropriate selected exclusion criteria are produced, followed by a cumulative weighted viewshed analysis, where the SDIS indicator is calculated. Optimum solutions are then determined by developing and employing a Genetic Algorithms (GAs) optimization process. The methodology is applied for the municipality of La Palma Del Condado in Spain for 100 different combinations of the two siting preferences. The optimization results are also employed to create a flexible and easy-to-use web-GIS application, facilitating policy-makers to choose the set of solutions that better fulfils their preferences. The GAs algorithm offers the ability to determine distinguishable, but compact, regions of optimum locations in the region, whereas the results indicate the strong dependence of the optimum areas upon the two siting preferences.
Agrivoltaic systems have an increasing interest. Realizing this upcoming technology raises still many challenges at design, policy and economic level. This study addresses a geospatial methodology to quantify the important design and policy questions across Europe. An elevated agrivoltaic system on arable land is evaluated: three crop light requirements (shade-loving, shade-tolerant and shade-intolerant) are simulated at a spatial resolution of 25 km across the European Union (EU). As a result, this study gives insight into the needed optimal ground coverage ratio (GCR) of the agrivoltaic system for a specific place. Additionally, estimations of the energy production, levelized cost of energy (LCOE) and land equivalent ratio (LER) are performed in comparison with a separated system. The results of the study show that the location-dependent solar insolation and crop shade tolerance have a major influence on the financial competitiveness and usefulness of these systems, where a proper European policy system and implementation strategy is required. Finally, a technical study shows an increase in PV power of 1290 GWp (almost × 10 of the current EU’s PV capacity) if potato cultivation alone (1% of the total arable agricultural area) is converted into agrivoltaic systems.
In this paper, the researchers applied the InVEST modeling framework to investigate the potential response of four ecosystem services (carbon storage, pollinator supply, sediment retention, and water retention) to native grassland habitat restoration at 30 solar facilities across the Midwest United States.
Solar electricity from solar parks in rural areas are cost effective and can be deployed fast therefore play an important role in the energy transition. The optimal design of a solar park is largely affected by income scheme, electricity transport capacity, and land lease costs. Important design parameters for utility-scale solar parks that may affect landscape, biodiversity, and soil quality are ground coverage ratio, size, and tilt of the PV tables. Particularly, low tilt PV at high coverage reduces the amount of sunlight on the ground strongly and leads to deterioration of the soil quality over the typical 25-year lifetime. In contrast, vertical PV or an agri-PV designed fairly high above the ground leads to more and homogeneous ground irradiance; these designs are favored for pastures and croplands. In general, the amount and distribution of ground irradiance and precipitation will strongly affect which crops can grow below and between the PV tables and whether this supports the associated food chain. As agrivoltaics is the direct competition between photosynthesis and photovoltaics. Understanding when, where and how much light reaches the ground is key to relate the agri-PV solar park design to the expected agricultural and electricity yields. We have shown that by increasing the minimum height of the system, decreasing the size of the PV tables and decreasing the coverage ratio, the ground irradiance increases, in particular around the gaps between the tables. The most direct way of increasing the lowest irradiance in a solar park design is to use semi-transparent PV panels, such as the commercially available bifacial glass-glass modules. In conclusion: we have shown that we can achieve similar ground irradiance levels in an east- and west-facing design with 77% ground coverage ratio as is achieved by a south-facing design at 53% coverage.
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.
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