D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 54 Citations 11,332 221 World Ranking 1082 National Ranking 18

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Artificial intelligence
  • Machine learning

Pierre Pinson mostly deals with Econometrics, Probabilistic logic, Probabilistic forecasting, Wind power forecasting and Electric power system. His research integrates issues of Regression analysis, Electricity price forecasting and Microeconomics in his study of Econometrics. His Probabilistic logic study combines topics in areas such as Uncertainty quantification, Economic forecasting, Parametric statistics and Solar power forecasting.

His Probabilistic forecasting research is multidisciplinary, incorporating elements of Prediction interval, Ensemble forecasting, Mathematical optimization and Consensus forecast. His studies in Wind power forecasting integrate themes in fields like Offshore wind power, Demand forecasting, HIRLAM, Weather forecasting and Forecast verification. His research integrates issues of Reliability engineering, Industrial organization, Electricity market and Trading strategy in his study of Electric power system.

His most cited work include:

  • Trading Wind Generation From Short-Term Probabilistic Forecasts of Wind Power (431 citations)
  • Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond (421 citations)
  • Probabilistic Forecasting of Wind Power Generation Using Extreme Learning Machine (387 citations)

What are the main themes of his work throughout his whole career to date?

His main research concerns Mathematical optimization, Electric power system, Meteorology, Econometrics and Probabilistic logic. His study in the fields of Stochastic programming, Linear programming and Optimization problem under the domain of Mathematical optimization overlaps with other disciplines such as Natural gas. The Electric power system study combines topics in areas such as Procurement, Environmental economics, Electricity market and Operations research.

His Meteorology study incorporates themes from Offshore wind power, Climatology and Wind power forecasting. Pierre Pinson studies Econometrics, focusing on Nonparametric statistics in particular. His biological study focuses on Probabilistic forecasting.

He most often published in these fields:

  • Mathematical optimization (20.21%)
  • Electric power system (19.95%)
  • Meteorology (16.06%)

What were the highlights of his more recent work (between 2019-2021)?

  • Mathematical optimization (20.21%)
  • Electric power system (19.95%)
  • Flexibility (8.03%)

In recent papers he was focusing on the following fields of study:

His primary scientific interests are in Mathematical optimization, Electric power system, Flexibility, Order and Electricity market. His Optimization problem study in the realm of Mathematical optimization interacts with subjects such as Natural gas, Scalability and Distribution system. The study incorporates disciplines such as Industrial engineering, Procurement, Stochastic programming, Weather forecasting and Operations research in addition to Electric power system.

Pierre Pinson studied Weather forecasting and Smoothing that intersect with Meteorology and Offshore wind power. His Flexibility research is multidisciplinary, incorporating perspectives in Base load power plant, Demand response, Economic dispatch and Reinforcement learning. His work carried out in the field of Electricity market brings together such families of science as Information asymmetry, Asset and Perfect competition.

Between 2019 and 2021, his most popular works were:

  • The future of forecasting for renewable energy (23 citations)
  • Do unit commitment constraints affect generation expansion planning? A scalable stochastic model (19 citations)
  • Energy forecasting: A review and outlook (16 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Artificial intelligence
  • Machine learning

His scientific interests lie mostly in Mathematical optimization, Electric power system, Flexibility, Revenue and Context. His work on Optimization problem as part of general Mathematical optimization research is frequently linked to High probability, bridging the gap between disciplines. His Electric power system research includes themes of Stochastic programming, Business model and Meteorology, Numerical weather prediction.

His research in Flexibility intersects with topics in Variable renewable energy, Pipeline transport and Relaxation. His biological study spans a wide range of topics, including Microeconomics, Monetization and Distributed database. In the field of Microeconomics, his study on Marginal cost overlaps with subjects such as Negotiation.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Trading Wind Generation From Short-Term Probabilistic Forecasts of Wind Power

P. Pinson;C. Chevallier;G.N. Kariniotakis.
IEEE Transactions on Power Systems (2007)

635 Citations

Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond

Tao Hong;Pierre Pinson;Shu Fan;Hamidreza Zareipour.
International Journal of Forecasting (2016)

546 Citations

Integrating Renewables in Electricity Markets: Operational Problems

Juan Miguel Morales González;Antonio J. Conejo;Henrik Madsen;Pierre Pinson.
(2013)

516 Citations

Probabilistic Forecasting of Wind Power Generation Using Extreme Learning Machine

Can Wan;Zhao Xu;Pierre Pinson;Zhao Yang Dong.
IEEE Transactions on Power Systems (2014)

509 Citations

From probabilistic forecasts to statistical scenarios of short-term wind power production

Pierre Pinson;Henrik Madsen;Henrik Aa. Nielsen;George Papaefthymiou.
Wind Energy (2009)

497 Citations

Global Energy Forecasting Competition 2012

Tao Hong;Pierre Pinson;Shu Fan.
International Journal of Forecasting (2014)

420 Citations

Benefits and challenges of electrical demand response: A critical review

Niamh O׳Connell;Pierre Pinson;Henrik Madsen;Mark O׳Malley.
Renewable & Sustainable Energy Reviews (2014)

381 Citations

Standardizing the Performance Evaluation of Short-Term Wind Power Prediction Models:

Henrik Madsen;Pierre Pinson;Georges Kariniotakis;Henrik Aa. Nielsen.
Wind Engineering (2005)

375 Citations

On the market impact of wind energy forecasts

Tryggvi Jónsson;Pierre Pinson;Henrik Madsen.
Energy Economics (2010)

337 Citations

Non‐parametric probabilistic forecasts of wind power: required properties and evaluation

Pierre Pinson;Henrik Aa. Nielsen;Jan K. Møller;Henrik Madsen.
Wind Energy (2007)

317 Citations

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