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3 results on '"Vanessa J. Fundel"'

1. Enhancing the Value of Weather and Climate Services in Society: Identified Gaps and Needs as Outcomes of the First WMO WWRP/SERA Weather and Society Conference

Author

Martin Göber, Isadora Christel, David Hoffmann, Carla J. Mooney, Lina Rodriguez, Nico Becker, Elizabeth E. Ebert, Carina Fearnley, Vanessa J. Fundel, Tobias Geiger, Brian Golding, Jelmer Jeurig, Ilan Kelman, Thomas Kox, France-Audrey Magro, Adriaan Perrels, Julio C. Postigo, Sally H. Potter, Joanne Robbins, Henning Rust, Daniela Schoster, Marion L. Tan, Andrea Taylor, and Hywel Williams

Subjects
Atmospheric Science, Emergency preparedness, Policy, Social Science, 500 Naturwissenschaften und Mathematik::550 Geowissenschaften, Geologie::551 Geologie, Hydrologie, Meteorologie, Communications/decision making, Societal impacts, Risk assessment
Published
2023
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3. Towards improved understanding of the applicability of uncertainty forecasts in the electric power industry

Author

Georges Kariniotakis, Malte Siefert, Corinna Möhrlen, Umit Cali, Jethro Browell, Sebastian Haglund El Gaidi, Bri-Mathias Hodge, Vanessa J. Fundel, Ricardo J. Bessa, Publica, Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento em Lisboa ( INESC-ID ), Instituto Superior Técnico, Universidade Técnica de Lisboa ( IST ) -Instituto de Engenharia de Sistemas e Computadores ( INESC ), WEPROG Aps, Deutscher Wetterdienst [Offenbach] ( DWD ), Fraunhofer Institute for Wind Energy and Energy System Technology, Department of Electronic and Electrical Engineering [University of Strathclyde], University of Strathclyde, Department of Mechanics, Royal Institute of Technology [Stockholm] ( KTH ), NREL, US Department of Energy, The University of North Carolina at Charlotte [Charlotte], Centre Procédés, Énergies Renouvelables, Systèmes Énergétiques ( PERSEE ), MINES ParisTech - École nationale supérieure des mines de Paris-PSL Research University ( PSL ), Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento em Lisboa (INESC-ID), Instituto Superior Técnico, Universidade Técnica de Lisboa (IST)-Instituto de Engenharia de Sistemas e Computadores (INESC), Deutscher Wetterdienst [Offenbach] (DWD), Department of Electronic and Electrical Engineering [Strathclyde], University of Strathclyde [Glasgow], Royal Institute of Technology [Stockholm] (KTH ), University of North Carolina [Charlotte] (UNC), University of North Carolina System (UNC), Centre Procédés, Énergies Renouvelables, Systèmes Énergétiques (PERSEE), MINES ParisTech - École nationale supérieure des mines de Paris, and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)

Subjects
Engineering, Control and Optimization, 010504 meteorology & atmospheric sciences, Standardization, Operations research, 020209 energy, Best practice, TK, forecast, Energy Engineering and Power Technology, Wind power forecasting, ensembles, 02 engineering and technology, User requirements document, 7. Clean energy, 01 natural sciences, lcsh:Technology, [ SPI.NRJ ] Engineering Sciences [physics]/Electric power, 0202 electrical engineering, electronic engineering, information engineering, wind energy, Electrical and Electronic Engineering, uncertainty, Engineering (miscellaneous), 0105 earth and related environmental sciences, [ INFO.INFO-RO ] Computer Science [cs]/Operations Research [cs.RO], Wind power, Renewable Energy, Sustainability and the Environment, business.industry, lcsh:T, [SPI.NRJ]Engineering Sciences [physics]/Electric power, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], decision-making, Risk analysis (engineering), statistics, weather, Electricity, Electric power industry, business, Consensus forecast, quantiles, Energy (miscellaneous)
Abstract

International audience; Around the world wind energy is starting to become a major energy provider in electricity markets, as well as participating in ancillary services markets to help maintain grid stability. The reliability of system operations and smooth integration of wind energy into electricity markets has been strongly supported by years of improvement in weather and wind power forecasting systems. Deterministic forecasts are still predominant in utility practice although truly optimal decisions and risk hedging are only possible with the adoption of uncertainty forecasts. One of the main barriers for the industrial adoption of uncertainty forecasts is the lack of understanding of its information content (e.g., its physical and statistical modeling) and standardization of uncertainty forecast products, which frequently leads to mistrust towards uncertainty forecasts and their applicability in practice. This paper aims at improving this understanding by establishing a common terminology and reviewing the methods to determine, estimate, and communicate the uncertainty in weather and wind power forecasts. This conceptual analysis of the state of the art highlights that: (i) end-users should start to look at the forecast’s properties in order to map different uncertainty representations to specific wind energy-related user requirements; (ii) a multidisciplinary team is required to foster the integration of stochastic methods in the industry sector. A set of recommendations for standardization and improved training of operators are provided along with examples of best practices

Published
2017
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