Pilot 3.2 | High photovoltaic penetration at urban scale

Pilot 3.2 | High photovoltaic penetration at urban scale

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.

/ Objectives

GIS tool for urban areas to simulate variability in space and in time the electric energy load and the yield productions of rooftop PV systems to assess for planning phase:

  • 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.

GIS tools for existing rooftop PV systems in on specific urban area, to monitor and nowcast:

  • the temporal and spatial variability of the injected electric energy for grid operators and aggregators for solar energy trading;
  • the temporal variability of the energy yield of a specific rooftop PV system for the citizen and the PV developers being contracted by the PV system owner.
/ Partners

ARMINES, DLR-DFD, DLR-VE, TSV

/ Key Users

Urban planners, grid operators, industrials, aggregator for energy trading, researchers in Energy and Urban planning and citizens.

/ Key Datasets

(S) satellite-based decametric DEM, (S) airborne- or satellite-based sub-metric DSM, (S) building cadastral 2D plans, (S) Copernicus Sentinel-1 and -2 for timescan analysis of Normalized Difference Vegetation Index (NDVI), Normalized Difference Built Index (NDBI) and Normalized Difference Water Index (NDWI) statistics, (S) Satellite-based global urban footprint imperviousness data (A) atmospheric optical state (aerosol optical depth, aerosol mixtures (black carbon, sea salt, mineral dust, sulphate, etc.), total column water vapour and ozone contents) from Copernicus Atmospheric Monitoring Service (CAMS), (A) surface solar radiation from CAMS, using Meteorological geostationary satellite (Meteosat Second Generation, MSG), (A) cloud structures as post-processing product from CAMS, (AS) in-situ measurements (pyranometric, air-pollution, PV metering, …).

/ ID Card (ARMINES)
Expected outcome of the pilot

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.

/ ID Card (DLR)
Expected outcome of the pilot

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.

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