Advanced weather forecasting for RES applications: Smart4RES developments tow...Leonardo ENERGY
Recording at: https://youtu.be/45Zpjog95QU
This is the 3rd Smart4RES webinar that will address technological and market challenges in RES prediction and will introduce the Smart4RES strategy to improve weather forecasting models with high resolution.
Through wind and solar applications, Innovative Numerical Weather Prediction and Large-Eddy Simulation approaches will be presented.
Advanced weather forecasting for RES applications: Smart4RES developments tow...Leonardo ENERGY
Recording at: https://youtu.be/45Zpjog95QU
This is the 3rd Smart4RES webinar that will address technological and market challenges in RES prediction and will introduce the Smart4RES strategy to improve weather forecasting models with high resolution.
Through wind and solar applications, Innovative Numerical Weather Prediction and Large-Eddy Simulation approaches will be presented.
EMPLOYING MULTI CORE ARCHITECTURE TO OPTIMIZE ON PERFORMANCE, FOR APPROACH IN...IAEME Publication
Cloud detection is an important task in meteorological application. Cloud information is especially important for now-casting purposes [1] and as an input for different satellite based estimation of atmospheric and surface parameters [2 -4]. The solar energy is the principal source of energy in the solar system. Clouds have high reflectance and absorption property which is used to distinguish them with land, water or sea area. There is critical demand to develop application, which can calculate the presence of cloud by using the available satellite image processing data, so that prediction of radiated solar energy can be optimised and energy budget can be predicted more easily.
In this deck from the Stanford HPC Conference, Peter Dueben from the European Centre for Medium-Range Weather Forecasts (ECMWF) presents: Machine Learning for Weather Forecasts.
"I will present recent studies that use deep learning to learn the equations of motion of the atmosphere, to emulate model components of weather forecast models and to enhance usability of weather forecasts. I will than talk about the main challenges for the application of deep learning in cutting-edge weather forecasts and suggest approaches to improve usability in the future."
Peter is contributing to the development and optimization of weather and climate models for modern supercomputers. He is focusing on a better understanding of model error and model uncertainty, on the use of reduced numerical precision that is optimised for a given level of model error, on global cloud- resolving simulations with ECMWF's forecast model, and the use of machine learning, and in particular deep learning, to improve the workflow and predictions. Peter has graduated in Physics and wrote his PhD thesis at the Max Planck Institute for Meteorology in Germany. He worked as Postdoc with Tim Palmer at the University of Oxford and has taken up a position as University Research Fellow of the Royal Society at the European Centre for Medium-Range Weather Forecasts (ECMWF) in 2017.
Watch the video: https://youtu.be/ks3fkRj8Iqc
Learn more: https://www.ecmwf.int/
and
http://www.hpcadvisorycouncil.com/events/2020/stanford-workshop/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Strahlendorff - EO and insitu for weather, water and climateMikko Strahlendorff
Earth Observation and in-situ data for weather, water and climate are principally clear physical numerical data, but still the diversity is large in data types and with new opportunities from crowd sourcing the challenge to share and disseminate all of it is challenging. And then there is also politics for some data that prevents a simple all is open and freely available. A crucial aspect is to look at the whole production chain to end-users for supporting a better Earth.
Solar resource measurements and sattelite dataSolarReference
To access explanatory notes and download link, head to -
http://solarreference.com/all-you-need-to-know-about-solar-resource-measurement/
This presentation can also be downloaded for SFERA website (SFERA Summer School 2013). Amazing, concise, to the point document. For more quality resources, visit
http://solarreference.com
Optimal combinaison of CFD modeling and statistical learning for short-term w...Jean-Claude Meteodyn
After almost three decades of active research, short-term wind power forecasting is now considered as a mature field. It has been widely and successfully put into operation within the past ten years. Meteodyn with over a decade of experience in wind engineering has contributed to this spread with tens of wind farm equipped with forecast solutions around the world. Our next-generation short-term forecasting solution has been designed to makes the most of both a tailored micro-scale CFD modeling and advanced statistical learning. In the frame of our model design, various options have been considered and evaluated taking into account both model performance and operational constraints. Two main approaches for wind power forecasting are usually considered in the literature (and sometimes opposed): “physical” and “statistical”. It is widely admitted that an optimal combination of both is necessary to build a high performance forecasting system. However, behind "optimal combination" resides a wide variety of design options. We propose here to shed some light on what performances one should expect from several modeling options for combining physics (mesoscale/CFD modeling) and statistics (grey/black box statistical learning, phase/magnitude correction, data filtering). Case studies are taken from real wind farms in various climate and terrain conditions.
As global warming intensifies, learning how to adapt to climate changes and consequent extreme weather events is gaining urgency. More accurate weather models and intelligent warning systems enable the improvement of the resilience of the local areas and production activities. One way of achieving this is through obtaining more accurate short term weather forecasts tailored for specific applications by analyzing large amounts of publicly available data such as localized meteorological measurements obtained from IoT sensors, open-source forecasts and even Earth observation data. In this talk we will show how we apply machine learning algorithms to efficiently improve and transform weather forecasts obtained from meteorological services and implement them in various decision-making use-cases such as precision agriculture, heating and cooling in buildings, urban infrastructure optimization (water distribution, urban lighting, traffic), logistics optimization and many more.
Upcoming Datasets: Global wind map, Jake Badger ( Risoe DTU)IRENA Global Atlas
Upcoming Datasets: Global wind map. A presentation by Jake Badger ( Risoe DTU) during the Global Atlas side event which held at the World Future Energy Summit in 2014
Solar Resource Assessment - How to get bankable meteo dataSolarReference
Available for download at http://solarreference.com/solar-resource-assessment-how-to-get-bankable-meteo-data/
This presentation from DLR (German Aerospace Center) explains.
1. Solar radiation data characteristics
2. How radiation data is gathered from ground measurements and derived from satellite data
3. Comparison of the two, and some important factors to be weighed in when deciding what to use
This presentation can also be downloaded at NREL
Sharpen existing tools or get a new toolbox? Contemporary cluster initiatives...Orkestra
UIIN Conference, Madrid, 27-29 May 2024
James Wilson, Orkestra and Deusto Business School
Emily Wise, Lund University
Madeline Smith, The Glasgow School of Art
0x01 - Newton's Third Law: Static vs. Dynamic AbusersOWASP Beja
f you offer a service on the web, odds are that someone will abuse it. Be it an API, a SaaS, a PaaS, or even a static website, someone somewhere will try to figure out a way to use it to their own needs. In this talk we'll compare measures that are effective against static attackers and how to battle a dynamic attacker who adapts to your counter-measures.
About the Speaker
===============
Diogo Sousa, Engineering Manager @ Canonical
An opinionated individual with an interest in cryptography and its intersection with secure software development.
Have you ever wondered how search works while visiting an e-commerce site, internal website, or searching through other types of online resources? Look no further than this informative session on the ways that taxonomies help end-users navigate the internet! Hear from taxonomists and other information professionals who have first-hand experience creating and working with taxonomies that aid in navigation, search, and discovery across a range of disciplines.
Acorn Recovery: Restore IT infra within minutesIP ServerOne
Introducing Acorn Recovery as a Service, a simple, fast, and secure managed disaster recovery (DRaaS) by IP ServerOne. A DR solution that helps restore your IT infra within minutes.
This presentation, created by Syed Faiz ul Hassan, explores the profound influence of media on public perception and behavior. It delves into the evolution of media from oral traditions to modern digital and social media platforms. Key topics include the role of media in information propagation, socialization, crisis awareness, globalization, and education. The presentation also examines media influence through agenda setting, propaganda, and manipulative techniques used by advertisers and marketers. Furthermore, it highlights the impact of surveillance enabled by media technologies on personal behavior and preferences. Through this comprehensive overview, the presentation aims to shed light on how media shapes collective consciousness and public opinion.
This presentation by Morris Kleiner (University of Minnesota), was made during the discussion “Competition and Regulation in Professions and Occupations” held at the Working Party No. 2 on Competition and Regulation on 10 June 2024. More papers and presentations on the topic can be found out at oe.cd/crps.
This presentation was uploaded with the author’s consent.
Competition and Regulation in Professional Services – KLEINER – June 2024 OEC...
11 schroedter homscheidt_satellite_and_camera
1. Deutsches Fernerkundungsdatenzentrum
Satellite- and (camera-derived) irradiance data for
applications in low voltage grids with large PV shares
Marion Schroedter-Homscheidt, Gerhard Gesell, Lars Klüser, Miriam Kosmale, Sandra
Jung, Niels Killius
Deutsches Zentrum für Luft- und Raumfahrt (DLR)
Earth Observation Center (EOC)
Holger Ruf, Gerd Heilscher
Hochschule Ulm
Contributions fromV.H. Peuch and
A. Benedetti (ECMWF),
L.Wald and M. Lefèvre (Armines),
E.Wey (Transvalor)
2. Deutsches Fernerkundungsdatenzentrum
Introduction
• Satellite-based solar resource information – New Copernicus/MACC service
• What‘s that? What is new?
• What else do we with the intermediate Copernicus service results?
• Cloud/snow statistics
• Dust aerosol statistics
• Nowcasting clouds for large solar power plants -> low voltage grids?
• Feed-in power and transformer load flow in a low voltage grid
• Cloud cameras – can we use NWP instead of a ceilometer for
cloud height assessment?
3. Deutsches Fernerkundungsdatenzentrum
Introduction
• Satellite-based solar resource information – New Copernicus/MACC service
• What‘s that? What is new?
• What else do we with the intermediate Copernicus service results?
• Cloud/snow statistics
• Dust aerosol statistics
• Nowcasting clouds for large solar power plants
• Feed-in power and transformer load flow in a low voltage grid
• Cloud cameras – can we use NWP instead of a ceilometer for
cloud height assessment?
5. Deutsches Fernerkundungsdatenzentrum
Physical retrieval method Heliosat-4
Scattering through
clouds and
aerosols
diffuse
irradiance
direct and diffuse
irradiance
Global irradiance
Absorption from
clouds,
aerosols, and
water vapour
diffuse
irradiance
Direct
normal
irradiance
Fast radiative transfer model = Heliosat-4
6. Deutsches Fernerkundungsdatenzentrum
McClear clear sky irradiance (GHI, DIF, DIR, DNI)
time series in 1 min steps and in global coverage
• 2004-2015 1-2 days delay online
• 7 years operations secured,
> 20 years planned
• Just register and
download from
http://www.soda-pro.com/ web-
services/radiation/
mcclear
• Interactive and OGC script
access possible
7. Deutsches Fernerkundungsdatenzentrum
MACC-RAD: Heliosat-4 irradiance
(GHI, DIF, DIR, DNI) time series in 15 min steps in
Europe/Africa/Middle East
• 2004-2015 1-2 days delay online
• 7 years operations secured,
> 20 years planned
• Just register and
download from
http://www.soda-pro.com /web-
services/radiation/
macc-rad
• Interactive and OGC script
access possible
8. Deutsches Fernerkundungsdatenzentrum
Registration needed to justify existence of service
Free for any use – commercial as well as R&D
Only restriction: Do not sell the data itself without modifications
Data policy
Here you can find Data Policy and
User‘s Guide
9. Deutsches Fernerkundungsdatenzentrum
Olympic goals in solar resources:
Aim to be more accurate, better resolved, more parameters…
But is that all?
Today’s situation: ‘I’m asking 5 data providers and will get 6 different answers …
and now there is also MACC/Copernicus’
Sure, better, more accurate, more parameters is needed…
But also:
transparency – which input data is used?
Publish instead of company confidential status
Detailed validation – publish instead of treated as company confidential
Continuous validation and quality control with experienced staff – no
project like approach with new PostDoc students every few years
Faster, higher, wider,…. Is that all?
Or: Why a new Copernicus service?
12. Deutsches Fernerkundungsdatenzentrum
Cloud and snow statistics
green = clear
blue = overcast/broken clouds
yellow = cirrus, thin ice
red = scattered clouds
La Réunion
Carpentras, France
13. Deutsches Fernerkundungsdatenzentrum
Dust aerosol statistics – extinction, dust events from MATCH
GHI, IEED_5 GHI, IEED_10
number of exceedance days per year
IEED = Irradiance Extinction Exceedance Day
Thresholds 5, 10, 30% for GHI
10,30,50,70% for direct irradiances
Based on a 30 years climatology of daily
dust aerosol optical depth
14. Deutsches Fernerkundungsdatenzentrum
Duration of dust events – as seen in MATCH
maximum number of consecutive IEED days
GHI, IEED for 10% extinction
mean number of consecutive IEED days
GHI, IEED for 10% extinction
16. Deutsches Fernerkundungsdatenzentrum
Feed-in power and transformer load – Ulm example
Grid simulation
Solar irradiance
at the surface
monitoring
forecast
Optimized solar energy integration
into the existing grid – grid status (historical data)
and nowcasting (expected to be used)
NWP
-17
-6
-45
-3/1
-11
-8
-5
-5
-69
-25
-26
-18-24
-11
-2
-4
-58
-3
-67
17. Deutsches Fernerkundungsdatenzentrum
Pyranometers
more accurate at the point
few locations only
maintenance needed
Satellite
spatially averaged
15 or 5 minutes
Long history available
Satellite or ground observations ?
18. Deutsches Fernerkundungsdatenzentrum
Test site Ulm Einsingen
• 12 PV-Systems with smart meters (red marked)
• 15 minute resolution
• 6.7.2013 – 13.12.2014
• Comparison of individual systems and sum
22. Deutsches Fernerkundungsdatenzentrum
Sky cameras and cloud height – can we save money for a ground based ceilometer
network and use the numerical weather prediction instead ?
Besides the question if sky cameras with their 10 minute forecast horizon and
restricted field of view are of interest at all for low voltage systems… , but PV and CSP
power plants might be interested…
A bit on cameras…
26. Deutsches Fernerkundungsdatenzentrum
Can I use numerical weather prediction‘s cloud condensation
levels as from ECMWF?
multilayer
situation
All cases scattered
Rmsd 5.5 km 5.5 km
Bias 1.09 km 1.17 km
Pearson
corr.
0.50 0.43
only scattered
all
27. Deutsches Fernerkundungsdatenzentrum
The new MACC/Copernicus irradiance service has been presented
Usage of cloud properties from space for extended site characteristics
Usage of aerosol properties from long-term modeling for site characteristics
Cloud properties used in nowcasting for large scale solar power plants
MACC irradiances for feed-in power calculation and transformer loads
in low voltage grids
Quantification of ECMWF cloud base height vs ceilometer in Spain
Wrap-Up
28. Deutsches Fernerkundungsdatenzentrum
This work has recently received funding from the European
Union’s Seventh Programme for research, technological
development and demonstration under grant agreement No
608623 and 608930.
Thanks to …
… Stadtwerke Ulm for providing smart meter and transformer data
… the MACC team for providing data
… ECMWF for providing forecast data
… EUMETSAT for providing MSG satellite observations