A set of interoperable online services that provide EO based business oriented information about PV self consumption, management and planning of grid source point for DSO (Distribution System Operator) and energy nowcasting / forecasting for energy trading and spot market.

A version of the WPS and the Jupyter Notebook for the self-comsuption scenario is deployed on WeKeo DIAS.

It has been publicly tested during the specific session at the 2021 annual Solar Training.

Live demo of the pilot recorded during the Solar Training is available on Youtube:

https://www.youtube.com/watch?v=Sj9eMoLFi0g

Feedback have be collected during the Solar Training and several presentations have been made including reporting lesson learned as per the CAMS online user workshop in Norway 24-25 March 2021:

https://atmosphere.copernicus.eu/cams-online-user-workshop-norway

Updated version for Q3 2022 will add the DSO and forecast use cases.

Two types of outputs will be provided:

1. Time series  in NetCDF format of historical and short term (intra-hourly) forecast PV yields simulation at urban scale
2. Expert analysis embedded in the Jupyter Notebook environment of:

a. Energy self consumption level

b. PV variability injected in the grid

c. Nowcast / Forecast

The powerfull infrastructure  from the WeKeo DIAS as an on-demand shevlved-unsshelved service

A 24/7 lighter infrastructure from MINES ParisTech SDI for testing

Jupyter frontend (Registration required) using a OGC WPS as the backbend process. The frontend to be potentially extended to a pure GIS (QGIS) interface:

https://notebook.oie-lab.net/hub/login

• For 2a (Energy self consumption): Better rooftop PV system sizing and economical feasibility studies.
• For 2b (PV variability injected in the grid): DSO (Distribution System Operator) management and planning of PV electricity injected in the grid at source points.
• For 2c (Nowcast/Forecast): Energy trading with portfolio of PV rooftop systems

• GEO-VENER community benefits regarding the release of business oriented application
• CAMS Radiation Service and high resolution DSM (Digital Surface Model) valorization
• DIAS performance to sustain business activity (Near real time EO data processing)

All Python code are deployed, hosted and synchronized on GitHub supporting the Jupyter Notebook frontend:

https://git.sophia.mines-paristech.fr/e-shape/e-shape-S3P2-notebook/

As the core EO data process is deployed as an OGC WPS standard, it could be invoked in an agnostic manner:

http://s3p2.oie-lab.net/service/wps?Service=WPS&version=1.0.0&request=DescribeProcess&identifier=s3p2

An ISO 19139 Metadata record has been created on the webservice-energy catalogue:

http://geocatalog.webservice-energy.org/geonetwork/srv/fre/catalog.search#/metadata/d9f3542d-2626-4294-b61e-c356faf0741f

This catalogue is weekly harvested by the GEO DAB (Discovery and Access Broker) and consequently the information are available on the GEO Web Portal:

https://bit.ly/34MSYdc

SDG 7 | AFFORDABLE AND CLEAN ENERGY

• The temporal and spatial variability of the injected electric energy in the grid for grid operators and urban planning decision makers;
• The specific behavior of residential, commercial, and industrial buildings with their different electric load patterns;
• The optimal integration and placement of electricity stationery storage applications and the charging and battery exchange stations;
• The adequacy of a specific rooftop PV system with respect to the energy consumption profile of citizens trying to optimize their PV self-consumption with the help of PV system developers.

SDG 11 | SUSTAINABLE CITIES AND COMMUNITIES

Supporting the energy transition enables cities to adapt to climate change conditions and to improve their sustainability level.

SDG 13 | CLIMATE ACTION
The pilot supports larger shares of solar energy which is seen as a key to support the energy transition process as part of climate change mitigation.

An existing GIS-like tool for grid operators, urban planning decision makers, industries, aggregators for solar energy trading, citizen (PV self-consumption) and researchers will make use of EO-based data instead of OpenStreetMap data only.

First data delivery from EO specialists at DLR-DFD to DLR-VE (in Feb 2020, completed).

First data integrated in FlexiGIS at DLR-VE, ready for first assessment by energy system analysis specialists (September 2020, completed).

Currently, DLR internal access by energy system analysis experts as first group of users.

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.

The GIS-tool is meant for experts working in electricity grid operator companies or working for potential analysis or business development in R&D departments at energy utilities and suitable research institutes.

Use case studies will be published to illustrate the potential use of EO data in the expert’s daily job life.

Expert access, this is no typical web application as it will make use of company confidential information on critical infrastructures in operational use.

In the planning phase the information will help to assess:

• the temporal and spatial variability of the injected electric energy in the grid for grid operators and urban planning decision makers;
• the specific behavior of residential, commercial, and industrial buildings with their different electric load patterns;
• the optimal integration and placement of electricity stationery storage applications and the charging and battery exchange stations;
• the adequacy of a specific rooftop PV system with respect to the energy consumption profile of citizens trying to optimize their PV self-consumption with the help of PV system developers.

Cross-sectoral EO-information is a potential to increase user uptake as energy transition is coupled to transportation transition by sector coupling more and more. Therefore, we observe and discuss further EO data usage and uptake with experts from the transportation sector.

Feedback on differences and potentials benefits of EO-based data will be given. 

Awareness in user group 'Energy System Analysis' will be created. This user group is not used to make use of EO-based data so far.

https://github.com/FlexiGIS/FlexiGIS

In case of round benefits of EO-data, the open source FlexiGIS in Github may integrate EO-data and then it would be meaningful to register this application.

SDG 7 | AFFORDABLE AND CLEAN ENERGY

• The temporal and spatial variability of the injected electric energy in the grid for grid operators and urban planning decision makers;
• The specific behavior of residential, commercial, and industrial buildings with their different electric load patterns;
• The optimal integration and placement of electricity stationery storage applications and the charging and battery exchange stations;
• The adequacy of a specific rooftop PV system with respect to the energy consumption profile of citizens trying to optimize their PV self-consumption with the help of PV system developers.

SDG 11 | SUSTAINABLE CITIES AND COMMUNITIES

Supporting the energy transition enables cities to adapt to climate change conditions and to improve their sustainability level.

SDG 13 | CLIMATE ACTION
The pilot supports larger shares of solar energy which is seen as a key to support the energy transition process as part of climate change mitigation.