Introduction

This webinar aims to designate the potential role of solar energy resource and forecasting in solar farms' efficient planning and operation.

Agenda

• Webinar content/EO4GEO project


• Bringing together Earth Observation resources in Europe: the e-shape project


• Energy meteorology: Terms and Definitions


• Earth Observation systems for Solar Energy


• Solar energy nowcasting and short-term forecasting


• Use of satellite data to assess and forecast solar energy potential in cities: from solar cadaster to PV variability at urban scale

Learning outcomes

• Learn the concepts of Energy Meteorology and discuss what it offers to the solar sector


• Recognize the main atmospheric and solar-related parameters that contribute to the efficient use of PV and CSP systems


• Learn the basic principles of solar forecasting


• Discuss about Earth Observations (EO) for solar nowcasting and forecasting


• Identify the use of solar energy tools for urban-scale applications


• Learn about PV nowcasting and short-term forecasting in urban scale

The Space/Geospatial Sector Skills Alliance

Towards an innovative strategy for skills development and capacity building in the space geo-information sector supporting Copernicus User Uptake

The EO4GEO project

• Duration: 4 years from January the 1st, 2018
• Budget: 3,87 million €
• Partnership: 25 Partners + 30+ Associated Partners (from 16 EU Countries) from Academia, Companies and networks
• Coordinators: GISIG (General), KU Leuven (Scientific & Technological), PLUS (Education & Training), Climate-KIC (Exploitation)

The VISION

To foster the growth of the European Earth Observation / Geographic Information (EO/GI) sector ensuring a workforce with the right skills, in the right place, at the right time.

The MISSION

To ensure the strategic cooperation among stakeholders on skills development in the EO/GI sector.

EO4GEO IS MUCH MORE

• A series of pre-defined curiculla in support of Copernicus


• A portfolio of training modules directly usable in the context of Copernicus and other relevant prograns


• A series of training actions (webinars, academic courses, etc.) in the three sub-sectors - integrated applications, smart cities and climate change


• A mobility program to promote internships and on-the-job training


• A Long-term Action plan to sustain the proposed solutions

www.eo4geo.eu

@EO4GEOtalks

Let's start from the basics...

What is Energy Meteorology?

Energy Meteorology is in the interface of renewable energy and atmospheric physics

Atmospheric physics is needed for the assessment and forecasting of the power output from solar and wind energy systems as well as for the planning, monitoring, and efficient operation of these systems.

What energy meteorology offers to the solar sector?

• Higher penetration in the energy mix and efficient grid integration
• Efficient use of large-scale applications

Most Important

International and consensus collaboration

Earth Observation systems for Solar Energy

Different space and time scales for solar resource assessment

Direct, Diffuse and Global Irradiance

Beam normal irradiance (BNI): measured using an instrument that tracks the sun and shades out the diffuse, it only records the direct component. Diffuse horizontal irradiance (DHI): measured using an instrument that has a shade to block out the direct radiation. Global horizontal irradiance (GHI): measured with an instrument mounted horizontally

GHI = BNI + DNI×cos(θ) http://www.nrel.gov/midc/srrl_bms

Concentrating solar power and photovoltaics

The ground-truth

The principle of radiative transfer and the satellite-derived solution

The principle of radiative transfer and the satellite-derived solution

CAMS Radiation service (CRS)

The challenge

How we can use such a service? How we can apply Earth Observation data to meet the demands for typical solar energy applications? What are the benefits and drawbacks of such an approach?

The e-shape project

e-shape - EuroGEO Showcases Applications Powered by Europe

• European contribution to GEO establishing EuroGEO
• 15M€, 69 partners, 7 showcases, 37 pilots
• 4 years grant (2019-2023)
• ARMINES (France) coordinator – e-shape.eu

• Promoting users’ uptake of European Earth Observation (EO) resources
• Building on Copernicus and GEOSS through the development of co-design pilots
• Built on a user-centric approach to deliver economic, social and policy value to European citizens.

Objectives

• O1: Develop operational EO services with and for users active in key societal sectors


• O2: Demonstrate the benefits of the EO pilots through the coordinated downstream exploitation of EO data and the utilization of existing EO resources


• O3: Promote the uptake of pilots at national and international scale, across vertical markets (private and public) and amongst key user communities


• O4: Enable the long-term sustainability of the numerous pilots, their penetration in public and private markets and support their upscaling


• O5: Increase uptake by raising awareness on the solutions developed through tailored and well-targeted communication, dissemination and outreach activities

e-shape - EuroGEO Showcases Applications Powered by Europe

Solar radiation/energy nowcasting and short-term forecasting

PMOD-WRC

Solar radiation forecasting basics

Surface solar radiation is variable spatiotemporaly Sun position (solar elevation) Atmospheric composition (aerosols, gases, water vapor) Clouds (coverage, on/off sun) Surface solar radiation used for solar-based energy production Different components (GHI & DNI) Solar variability affects: National and regional electric grid stability Solar contribution in the energy mix / (real time demand) Planning and management of PV and CSP Trading, distribution, storage, optimization

Solar radiation forecasting basics

Forecasting approaches Deterministic (one value at its time) Probabilistic (ensemble with probability)

Solar radiation forecasting basics

Forecasting approaches Deterministic (one value at its time) Probabilistic (ensemble with probability)

Solar radiation/energy forecasting and now-casting

EO and solar nowcasting/The Sense System

EO and solar Nowcasting/Clouds

EO and solar Nowcasting

Aerosols

Aerosols

Aerosols

Sense validation

nextSense Solar Forecasting

E-Shape: nextSENSE: introduction of Cloud motion vector forecasting

Cloud Motion Vectors

nextSense Solar Forecasting validation

nextSense Solar Forecasting validation

nextSense - demonstration

EO and solar forecasting - Global

Example nextSense approach for India

INSAT 3D satellite full domain

INSAT 3D satellite use for India

Users and co-design aspect

Greek TSO → Direct use of nextSENSE as an EMS Egyptian ministry of Electricity and Renewable Energy Authority → Energy management & Aswan renewable energy based hospital National Grid Authority → Solar forecasting Commercial REN EPC contractors in Europe, Africa, Middle East and Southern Asia → 2021

Remarks

Solar power forecasting is essential for cost-effective energy system integration of solar energy. Applications: specific requirements with respect to forecast horizon and spatiotemporal resolution.

Forecasting solar irradiance should be evaluated in the context of strategies for the system integration of solar power, which aim to provide the necessary power to cover demand at any time.

Reliable short-term irradiance forecasts can be derived from EO based data using cloud motion-based methodologies.

Forecast evaluations are important. Hybrid approaches on used methodologies could be beneficial

Choice of a forecast method depends on:

• User needs
• Measurement data and model availability
• Spatiotemporal aspects
• Evaluation – uncertainty of method
• Technical aspects

Use of satellite data to assess and forecast solar energy potential in cities: from solar cadaster to PV variability at urban scale

Solar Cadaster: high resolution (metric) urban solar mapping

Photovoltaic (PV) systems (rooftop, parking shades, etc.) in urban areas are very interesting

• Low cost since the price of PV modules are constantly and dramatically decreasing
• No emission of pollutants nor GHGs during their exploitation
• Production of electricity where this electricity is consumed
• Added value to unused urban roofs/parking shades (e.g. commercial centre)
• Positive impact on Urban Heat Island

Solar Cadasters enable to:

• Analyse the solar potential of roofs/shades over a city w.r.t. the local electricity consumption
• Help public or private decision-makers and investors

Solar Cadaster from In Sun We Trust

In Sun We Trust is providing free, accurate and easy-to-use tool for the general public to assess solar potential of rooftop PV systems with the support of: The French national mapping agency (IGN) MINES ParisTech Transvalor Innovation - SoDa

nantes-metropole.insunwetrust.solar

From Solar Cadaster to urban-scale solar variability

Static yearly irradiation on tilted plans (1-m res.)

Near on-the-fly computation of intra-day irradiation on tilted plans (1-m res.)

Renewable Energy Showcase - Pilot #2: High PV penetration in urban area

• Objective: develop GIS-tools dedicated to high photovoltaic penetration at urban scale, providing EO based information about urban energy system modeling, electric energy demand profiles and accurate electric production of fleet of PV rooftop systems


• Expected user community: Urban planners, grid operators, aggregator for energy trading, researchers in Energy and Urban planning and citizens (self-consumption)>


• Two parts of the pilot:
• Part 1: PV variability at urban scale (pilot in Nantes)
• Part 2: EO-data for PV integration in the urban energy system (pilot in Oldenburg)


• Supporting infrastructure: DIAS WEkEO, Urban TEP


• Partners:
  

EO data

A decametric digital terrain model (DTM) to describe the orographic shadow effects (e.g. SRTM, ASTER) A high-accuracy 10 cm digital surface model (DSM) to provide 3D description of buildings, vegetation and superstructures (IGN, using aerial images correlation). A high-accuracy map of buildings to provide location and contours of corresponding roofs (IGN - BDTOPO©)

The EO data for clear-sky irradiance modeling

Clouds are not the only source of solar variability. The irradiance for clear-sky (cloud-free) condition from McClear (CAMS), integrating aerosols, water vapor depending on the Sun topocentric position

The EO data for clear-sky irradiance modeling

Example with in-situ measurements under clear-sky in Shanghai

Clear-Sky GHI with Climatology Monthly Linke Turbidity (ESRA Model)

Clear-Sky GHI from McClear (Aerosol + WV from CAMS)

The EO data for all-sky irradiance estimation

Satellite-based all-sky solar data HelioClim-3/CAMS Rad (3 km, 15 min, 2004-, 15+ years) Heliosat-2 / Heliosat-4 methods Applied on images from SEVIRI spaceborne by Meteosat Second Generation Heliosat-2 / Heliosat-4 methods

At least one year of in-situ pyranometric measurements for local calibration

Data and Information Access Services (DIAS)

• DIAS WEkEO
• Providing cloud processing requested on-the-fly through asynchronous OGC Web Processing Services (WPS)


• Hosting a Jupyter Hub with Jupyter Notebooks exemplifying in Python different use-cases with:
• GIS-like interface
• WPS asynchronous requests
• Output data exploitation and representation

Overview of the pilot organized around a “core” service

Available pilot on Jupyter Notebook

Available pilot on Jupyter Notebook

Available pilot on Jupyter Notebook

Available pilot on Jupyter Notebook

Available pilot on Jupyter Notebook

Available pilot on Jupyter Notebook

Available pilot on Jupyter Notebook

Available pilot on Jupyter Notebook

Available pilot on Jupyter Notebook

Available pilot on Jupyter Notebook

Hands-on session recording - Youtube:

To get an account to test the pilot:

lionel.menard@mines-paristech.fr

Local urban planning & PV

Study of a PV parking shades (100 kWp) impacted by a “new” building Before the “new building”: 1200 kWh/kWp Impact of the new building: -18.3% 980 kWh/kWp Annual loss: ~2000€/year

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)

Example:urban area of of 1.5 km x 1.5 km 20 % PV penetration: 35 related source points of ENEDIS (DSO) 14 ha of PV roof-top systems (~ 20+ MWp) Nameplate PV power injected in the source points

Temporal evolution of instantaneous PV power potentially injected within a day

PV nowcasting & short-term forecasting (case #3)

Usage: Energy trading with portfolio of PV rooftop systems(e.g. Urban Solar Energy ?)

Use of Cloud Motion Vector (CMV) from two consecutive satellite images:

• CAMS aerosol / water vapor forecasting (CAMS McClear)
• 3D shadowing effects from DSM

Potential use of some PV yield monitoring (in-situ) in the real time loop of forecasting correction

PV nowcasting & short-term forecasting (case #3)