Urban energy system modelling of distribution grids to plan, monitor and nowcast the spatiotemporal variability of the electric consumption

Sponsor	Project	Solution provider	User
			stakeholders in the public health domain, private companies and research institutions

• Energy & mineral resources / renewable energy
• Urban development / smart cities
• Environment climate & health / meteo and climate
• Financial & digital services / insurance and real estate
• Infrastructure & transport / construction

Target users include:

1. Urban planners
2. grid operators
3. industrials
4. aggregator for energy trading
5. researchers in Energy and Urban planning
6. citizens

Rooftop PV systems in urban areas are very interesting because they do not emit air pollutants nor GHGs during their exploitation, they produce electricity where this electricity is consumed, and they add value to unused urban roofs and parking shades and may reduce urban heat island effect. But, due to complex shading effects in urban context (vegetation, surrounding buildings, superstructures of roofs, etc.) and local atmospheric and meteorological effects, their massive penetration in urban areas will induce a significant variability in space and in time in the energy injected in the electric grid. As far as the electric demand side is concerned, a detailed modelling of energy requirements from residential, commercial, and industrial buildings with varying demand profiles for electricity is also required. Therefore, there is a need, in urban area, for Geographical Information System (GIS)-like tool for grid operators, urban planning decision makers, industries, aggregators for solar energy trading, citizen (PV self-consumption) and researchers. This GIS-tool is meant to provide an urban energy system modelling of distribution grids to plan, monitor and nowcast (i.e. and short term forecast) the spatiotemporal variability of the electric consumption on one hand and of the production of fleet of PV rooftop systems on the other hand.

Existing GIS-tools for the Nantes (F) and Oldenburg (D) areas will be enhanced by new satellite-based datasets. The cost/benefit of using satellite-based data will be assessed in several specific use cases.

The service has been demonstrated and assess by 40 professional in the solar rardiation domain during the 9^thedition of the solar training co-organized by Soda Transvalor and MINES ParisTech ARMINES.

 A live recording video of this session is available here:

• Historical analysis of PV variability (case #1)
  • Usage: PV self consumption (sizing individual systems, In Sun We Trust)
• Historical analysis of PV variability (case #2)
  • Usage : Simulated PV injection in different source points of the electric grid for different scenarios of PV penetration (for DSO, e.g. ENEDIS)
• PV nowcasting and short-term forecasting (case #3)
  • Usage: Energy trading with portfolio of PV rooftop systems

More than 80% of the global population lives in areas at risk of at least one major Vector-Borne Disease (VBD), with more than 700.000 deaths at a global scale (WHO, 2020). Mosquitoes are the protagonists of these vectors, transmitting pathogens to living beings with the most important being the Mosquito-Borne Diseases (MBDs) in Europe, namely West Nile Fever linked to Culex mosquitoes, Malaria linked to Anopheles mosquitoes and Chikungunya, Dengue and Zika linked to Aedes mosquitoes.

EYWA builds on a modular system architecture of 7 TIERS that allows federated access to global data repositories, exploits European infrastructure as Copernicus, Copernicus Core Services, and DIAS (CreoDIAS), uses advanced DataCube technology for the processing of big EO data in conjunction with in-situ trap and other environmental/epidemiological data, and invokes validated ML/DL entomological and deterministic (dynamic) epidemiological models. The challenges in the proposed action is to further develop and adapt the models to treat effectively non-European datasets, which in principle suffer from scarcity, data sharing incompatibility and standardization issues, the latter making the main challenge towards the implementation of EYWA globally.

The EYWA system provides a number of benefits:

• Generates a combined database of entomological & epidemiological data.
• Creates standards around the entomological & epidemiological data.
• Provides mosquito population predictions on multiple spatiotemporal resolutions.
• Provides West Nile Virus risk forecast in multiple spatiotemporal resolutions.

Raises the awareness around the issues and risks of Mosquito-borne diseases.

Learn more about the service: http://epidemics.space.noa.gr:8081/

Learn more about e-shape: www.e-shape.eu

A question? Contact the Helpdesk: https://helpdesk.e-shape.eu