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About

About

Ricardo Bessa was born in 1983 in Viseu, received his Licenciado (five-year) degree from the Faculty of Engineering of the University of Porto, Portugal (FEUP) in 2006 in Electrical and Computer Engineering. In 2008, he received the M.Sc. degree in Data Analysis and Decision Support Systems on the Faculty of Economics of the University of Porto (FEP). He obtained his Ph.D. degree in the Doctoral Program in Sustainable Energy Systems (MIT Portugal) at FEUP in 2013. Currently, he is a Senior Researcher and Area Manager at INESC TEC in its Center for Power and Energy Systems. 

His research interests include renewable energy forecasting, electric vehicles, data mining and decision-making under risk. He worked in several international projects such as the European Projects FP6 ANEMOS.plus, FP7 SuSTAINABLE, FP7 EvolvDSO, Horizon 2020 UPGRID, Horizon 2020 InteGrid and an international collaboration with Argonne National Laboratory for the U.S. Department of Energy. At the national level he participated in the development of renewable energy forecasting systems and consultant services about energy storage.

He is co-authors of more than 32 journal papers and 61 conference papers.

Interest
Topics
Details

Details

  • Name

    Ricardo Jorge Bessa
  • Cluster

    Power and Energy
  • Role

    Assistant Centre Coordinator
  • Since

    01st February 2006
012
Publications

2017

Towards Improved Understanding of the Applicability of Uncertainty Forecasts in the Electric Power Industry

Authors
Bessa, RJ; Mohlen, C; Fundel, V; Siefert, M; Browell, J; El Gaidi, SH; Hodge, BM; Cali, U; Kariniotakis, G;

Publication
ENERGIES

Abstract
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.

Supervised
thesis

2017

Optimization and Control of Virtual Power Plants

Author
Jorge Miguel Pérola Filipe

Institution
UP-FEUP

2017

Big Data techniques for Solar Power Forecasting

Author
Rui Miguel da Cunha Nunes

Institution
UP-FEP

2017

Previsão Probabilística dos Desvios dos Agentes Comerciais e Produtores do Mercado de Eletricidade

Author
Cézar Vicente Cerciari

Institution
UP-FCUP

2016

Energy Markets Simulation and Forecasting with Emergent Business Models

Author
Renato da Silva Fernandes

Institution
UP-FEP

2016

Residential Consumer Behavioural Analysis on the Participation in Demand Response Strategies including Distributed Generation and Electric Vehicles

Author
Kamalanathan Ganesan

Institution
UP-FEUP