PARSEC sectors: Energy, EO
Application fields: Alternative Energy, Energy & Natural Resources
Keywords: energy planning, EO data, forest, image processing, machine learning, renewable energy market, Self-consumption, solar irradiance, urban planning
In 14 and a half seconds, the sun provides as much energy to Earth as its population uses in a day. Capturing all this energy is feasible and depends only on decision making.
Nowadays, there is an increase of the share of renewable energy sources in the total energy production and consumption mix (currently 22%, with the goal to reach 30% globally within the next decade), in conjunction with the overall influence of the climatic conditions from the irrational use of the produced energy. Indicatively, over the past 5 years an estimated 15 gigatonnes equivalent of CO2 emissions was avoided with the use of renewables, a number that is expected to increase to almost 70 gigatonnes for the next 30 years.
The renewable energy market requires an efficient and optimal energy planning and management. The modern technical solutions for the grid operators support monitoring, forecasting, and managing the energy production with the use of space technologies, which are in particular useful in decision-making for the energy producers that exploit photovoltaic or concentrated solar power plants as well as for the electricity transmission and distribution system operators. To this direction, in the framework of the EuroGEO e-shape project a novel service was officially released in summer 2020 in support to the distributed solar plant energy production management, electricity handling entities and smart grid operations in Europe and North Africa. Called NextSENSE, this pilot is a 5-year scientific and technical achievement of the collaboration of the National Observatory of Athens (NOA) in Greece with the World Radiation Center (PMOD/WRC) in Switzerland and exploits the synergy of Earth observation (EO) data and radiative transfer modeling with image processing and optical flow technologies, machine learning and high performance computing architectures.
The use of EO data and energy management systems like in nextSENSE is based on the new European Energy Target Model which has as a main scope the energy market liberalization and the creation of a single competitive electricity market. The main characteristic of this model has to do with the continuous intraday energy trading, so the operational exploitation of the space technology and the nextSENSE service is able to provide accurate solar energy short-term forecasts, crucial in the energy market, where on-the-spot energy prices are defined by supply and demand equilibriums. As a result, if the energy suppliers can have such accurate estimations for the distributed solar energy production from solar systems, this information provides them with a comprehensive advantage with clear economic benefits for their intraday and day-to-day market operations.
NextSENSE aims to actively support the smart solar energy planning and real-time management. Climatological data in terms of solar atlases form the energy planning solutions which are able to provide critical information for existing and new solar farm installations and investments. Real-time and forecasting data of solar irradiance shape the energy management tools by controlling the solar based electricity production, its transmission and distribution, and hence, the renewable energy market. Using near-real-time cloud microphysics data derived from EO data sources, we introduce a novel short-term forecasting system (3 h ahead) that is capable of calculating solar energy in large-scale (1.5 million-pixel area covering Europe and North Africa) and in high spatial (5 km over nadir) and temporal resolution (15 min intervals). For the operational implementation of such a big data computing architecture (20 million simulations in less than a minute), we exploit a synergy of high-performance computing and deterministic image processing technologies (dense optical flow estimation). The user through the nextSENSE’s fully dynamically interface is able to navigate, zoom and click at any pixel of the 1.5 million matrix retrieving solar energy potential information for 3 hours ahead and 3 hours back at 15-min intervals.
NextSENSE is able to provide access to accurate solar energy information mainly for urban planning, energy management and grid stability, while it can actively support the energy producers at any solar system scale as well as the transmission and distribution system operators, with open access solutions for decision making, promoting and supporting the sustainable development as well as affordable and modern energy for all. It is a totally open access platform for continuous monitoring and short-term forecasting of solar energy in large-scale and which runs operationally, online and in real-time. NextSENSE was evaluated against ground-based measurements of solar irradiation as well as with real solar plant production data in Europe, North Africa and Southern Asia. Indicatively, over the past 5 years more than 30 publications in scientific journal and conferences studied the accuracy of this service in terms of energy planning (new solar farms installation) and management (energy market operations).
NextSENSE is just the beginning and next years will enable the solar industry to better plan clean energies, which in turn will boost the relative contribution to national portfolios. Rooftop solar photovoltaic systems can make also a significant contribution to Europe’s energy transition. Realizing this potential raises challenges at policy and electricity system planning and management level. To this direction, a series of dedicated EO-based solutions are under development in order to be applied at city scale and to quantify the effect of additional parameters to solar energy production, like the photovoltaic panels efficiency in the urban environment, the shadow effects, the buildings energy adequacy and the electricity balance for smooth smart grid operations.
Some examples:
The city of Athens in Greece which is a city of 4 million citizens and covers an area of 500 km2 from which an estimated 120 km2 is the potentially available rooftop area for PV installations and which can produce almost 7 TWh in an annual basis. This energy is able to fulfill more than the 50% of the city’s energy consumption. The potential benefits could be at least 30.5 billion euros for the next decade (2020-2030) as a discounted cost by the extensive installation and exploitation of rooftop PV installations for a 100% rooftop coverage scenario, and an almost 226 megatonnes of CO2 equivalent of emissions will be avoided.
The nextSENSE system of nowcasting, forecasting and solar atlas services of NOA provides the opportunity for efficient planning and management of solar energy at any scale and location. In Egypt, the official solar atlas was created for the needs of the ministry of electricity and renewable energy. In this study, 29 specific locations were selected for the construction of new solar farm projects, one of which is the site of Benban, where a 1.8 GW solar farm will be completed by the end of 2020 providing massively green energy to the region and actively contributing in the energy mix in Egypt. The Magdi Yacoub Heart Foundation in Aswan has also used the nextSENSE service for assessing the proper energy production monitoring solutions for the under construction photovoltaic park, covering the energy needs of the hospital and the residential area. The contribution of these services to the society in Egypt was awarded and highlighted by the Minister of Electricity and Renewable Energy, the Minister of Immigration and Egyptian Expatriate Affairs and the Minister of State for Military Production.
This article was prepared thanks to a contribution of Dr Panagiotis Kosmopoulos, NOA and and Dr Stelios Kazadzis, PMOD/WRC in the context of the EuroGEO e-shape project
References
EuroGEO e-shape project: https://e-shape.eu/
The service can be found in the following link: http://solea.gr/solar-energy-management/.
Contacts: Dr Panagiotis Kosmopoulos (NOA; pkosmo@noa.gr) and Dr Stelios Kazadzis (PMOD/WRC; stelios.kazadzis@pmodwrc.ch).
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