Objectives of the service
The growing demands for food and energy security with decreasing availability of arable land for farming caused by global population growth as well as demand of land for energy production presents a major challenge for our societies and its ambitions to transition towards low carbon and green economy. Agri-PV is a promising system since it combines the two independent systems of energy and agriculture that are co-located and interconnected in one place. Due to this co-location and integration, there are lot of challenges faced by Agri-PV stakeholders and it is important to understand them for the sustainability of Agri-PV plants.
The goal of DAPV services is to offer a unique and one of its kind integrated solutions for different segments of Agri-PV customers based on innovative self-learning AI-powered technologies in forecasting of weather/climate, energy generation , crop yield, O&M, plant design and economics of Agri-PV systems using satellite earth observation data and actual ground data.
The main objectives of DAPV services in this feasibility study is to have engagement with the APV customers/users for understand their requirements, perform a technical feasibility of the DAPV services including a proof-of-concept of DAPV services at the APV pilot customers sites and finally to consolidate the experiences in terms of technical and commercial viability study and provide a road map for the service market roll-out.
Users and their needs
This study is targeted first to understand the challenges faced in three important customer segments in Agri-PV:
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Energy companies
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Agri-PV developers and EPC companies
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Large farmland owners as well as farmers
all mostly located in the EU countries like Germany, France and Italy.
Following is the summary of important desires and requirements from most of these customers:
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Integrated monitoring and forecasting system for Agri-PV with location specific weather forecasting and capabilities of accurately forecasting energy, crop yield, predictive O&M and revenues (economics) for the operations of APV system.
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Design optimizations of APV system at planning stage using inputs from satellite earth observation and AI.
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Services should comply according to the regulations, either crop yield first or both crop and energy production optimizations, which should be taken into consideration at the planning stage of designing the APV systems.
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Requirement of pre-design estimations/predictions of the size, design, and performance in terms of energy production, crop growth and losses in O&M in the APV. There are currently no systems available for APV as a whole and DAPV services are of great interest.
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APV site characteristics like soil quality, water resources, etc., before and after APV construction using satellite earth observation data
Service/ system concept
The DAPV service concept was envisaged to provide location specific short-to-long-term intelligent energy, crop-growth, O&M forecasting (days, months, years ahead) decision support system, including plant design services, tailored for the Agri-Photovoltaics (APV) sector’s planning, development, economics, and operations. Thanks to a combination of space-based earth observation (EO) data as well as PV and agriculture in-situ data, our disruptive deep-learning AI technology system will be able to deliver accurate forecasts based on APV location weather to farmland owners, APV plant designer, planners, energy companies, agriculture & food companies, or societies etc.
Space Added Value
The DAPV services will massively use satellite earth observation as the main source of information for atmosphere, energy resources, crop growth, APV plant design and O&M, modelling and forecasting. We will use atmosphere (surface and pressure level), selected ocean surface data, and land data based on COPERNICUS (CAMS, C3S, CMEMS, CLMS, SENTINEL) services as well as EUMETSAT, ECMWF and NASA datasets at different spatial and temporal resolution.
Modelling, forecasting, and resulting decision making in renewable energy and agricultural applications is still commonly based on in-situ ground data and the spatial resolution, data quality and availability are very inhomogeneous between different regions and economic owners of energy or agricultural farms and is expected for APV systems as it is a combination of them. A generalized approach and concept to an AI-based modelling, forecasting and decision making is not possible under these conditions. Satellite Earth Observation data, in contrast, show a consistent set of observed parameters, spatial and temporal resolution, and data quality for every region of the world. This allows us to develop new business models and AI-based technical innovations which are flexible, adaptable, more reliable, and accurate, yet transparent and trustworthy. In renewable energy forecasting we have shown that use of SatEO data leads to an increase of economic value of up to 50% compared to other solutions.
Current Status
In the first stage of the study the stakeholder analysis was performed, and important APV customer segments were identified. Then the user requirements were identified through surveys, one-to-one meetings, and consultations with three targeted customer segments of energy companies, APV project developers and EPC companies and large-scale farmland owners & farmers. Important value proposition based DAPV services were identified based on user requirements.
In the second stage, the service and system architecture were designed for the DAPV solutions identifying the various functional modules and interactions between them for achieving the required services and smooth function of the system. A proof-of-concept of this integrated system and the modules were studied at two different pilot users (one each from energy and EPC customer segments) in Europe at their Agri-PV sites. During the proof-of-concept various assumptions for the services were tested for their user desired solutions, technical as well as commercial viability and was successfully completed, validating the technical feasibility of DAPV services. Further a business case was developed around these services for its commercial viability.
In the final stage of the study, roadmap and next steps towards a demonstration project using these services for commercial roll-out of the services to all the customer segments in APV are being pursued.
