H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Engineering and Technology D-index 55 Citations 10,447 191 World Ranking 1006 National Ranking 31

Research.com Recognitions

Awards & Achievements

2015 - IEEE Fellow For contributions to modeling and forecasting of electricity markets

Overview

What is he best known for?

The fields of study he is best known for:

  • Mathematical optimization
  • Finance
  • Microeconomics

His main research concerns Mathematical optimization, Linear programming, Electricity market, Integer programming and Optimization problem. His research integrates issues of Total cost, Distributed generation, Activity-based costing and Game theory in his study of Mathematical optimization. Javier Contreras interconnects Electric power system and Energy storage in the investigation of issues within Linear programming.

His Electricity market research is multidisciplinary, relying on both Electricity generation, Microeconomics and Environmental economics. His Microeconomics research is multidisciplinary, incorporating elements of Wind power, Electricity price forecasting, Economic forecasting and Electricity. The Electricity study combines topics in areas such as Financial economics and Econometrics.

His most cited work include:

  • ARIMA models to predict next-day electricity prices (787 citations)
  • Forecasting next-day electricity prices by time series models (741 citations)
  • A GARCH forecasting model to predict day-ahead electricity prices (555 citations)

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

Javier Contreras spends much of his time researching Mathematical optimization, Electricity market, Electricity, Renewable energy and Linear programming. His biological study spans a wide range of topics, including Distributed generation, Electric power system and Transmission. He has included themes like Production, Microeconomics, Profit, Econometrics and Electricity generation in his Electricity market study.

His Electricity price forecasting study, which is part of a larger body of work in Electricity, is frequently linked to Autoregressive integrated moving average, bridging the gap between disciplines. His Renewable energy research is multidisciplinary, incorporating elements of Wind power, Stochastic programming, Photovoltaic system, Energy storage and Environmental economics. His research in Linear programming intersects with topics in Network topology and Transformer.

He most often published in these fields:

  • Mathematical optimization (44.49%)
  • Electricity market (22.43%)
  • Electricity (20.53%)

What were the highlights of his more recent work (between 2018-2021)?

  • Mathematical optimization (44.49%)
  • Renewable energy (19.77%)
  • Linear programming (17.49%)

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

Javier Contreras mainly focuses on Mathematical optimization, Renewable energy, Linear programming, Electricity and Distributed generation. As part of his studies on Mathematical optimization, Javier Contreras often connects relevant subjects like Investment. His Renewable energy research focuses on Photovoltaic system and how it relates to Dispatchable generation, Hybrid power, Compressed air energy storage and Bidding.

His Linear programming research incorporates themes from Electric vehicle, Solver, Wind power and Voltage regulator. In the subject of general Electricity, his work in Electricity market is often linked to Mainland China, thereby combining diverse domains of study. His Electricity market study combines topics from a wide range of disciplines, such as Order and Econometrics.

Between 2018 and 2021, his most popular works were:

  • Daily pattern prediction based classification modeling approach for day-ahead electricity price forecasting (56 citations)
  • A novel energy scheduling framework for reliable and economic operation of islanded and grid-connected microgrids (27 citations)
  • Uncertainty-Based Models for Optimal Management of Energy Hubs Considering Demand Response (16 citations)

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

  • Finance
  • Microeconomics
  • Mathematical optimization

Mathematical optimization, Electric power system, Electricity market, Distribution networks and Electric vehicle are his primary areas of study. His research integrates issues of Distributed generation, Renewable energy, Linearization and Energy management in his study of Mathematical optimization. Javier Contreras combines subjects such as Electricity generation, Environmental economics and Energy consumption with his study of Electric power system.

In general Electricity market, his work in Electricity price forecasting is often linked to Weighted voting linking many areas of study. His Distribution networks study combines topics in areas such as Bidding, Scheduling, Equilibrium problem and Nash equilibrium. His Electric vehicle research is multidisciplinary, relying on both Linear programming, Level of service, Solver and Reduction.

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

ARIMA models to predict next-day electricity prices

Javier Contreras;Rosario Espinola;F. J. Nogales;Antonio J. Conejo.
IEEE Transactions on Power Systems (2002)

1451 Citations

Forecasting next-day electricity prices by time series models

F. J. Nogales;J. Contreras;A. J. Conejo;R. Espinola.
IEEE Transactions on Power Systems (2002)

1161 Citations

A GARCH forecasting model to predict day-ahead electricity prices

R.C. Garcia;J. Contreras;M. van Akkeren;J.B.C. Garcia.
IEEE Transactions on Power Systems (2005)

835 Citations

Forecasting electricity prices for a day-ahead pool-based electric energy market

Antonio J. Conejo;Javier Contreras;Rosa Espínola;Miguel A. Plazas.
International Journal of Forecasting (2005)

637 Citations

Optimization of control strategies for stand-alone renewable energy systems with hydrogen storage

Rodolfo Dufo-López;José L. Bernal-Agustín;Javier Contreras.
Renewable Energy (2007)

426 Citations

Self-scheduling of a hydro producer in a pool-based electricity market

Antonio J. Conejo;Jose M. Arroyo;J. Contreras;Francisco A. Villamor.
IEEE Transactions on Power Systems (2002)

425 Citations

Numerical solutions to Nash-Cournot equilibria in coupled constraint electricity markets

J. Contreras;M. Klusch;J.B. Krawczyk.
IEEE Transactions on Power Systems (2004)

305 Citations

Transmission Expansion Planning in Electricity Markets

S. de la Torre;A.J. Conejo;J. Contreras.
IEEE Transactions on Power Systems (2008)

283 Citations

A Three-Level Static MILP Model for Generation and Transmission Expansion Planning

David Pozo;Enzo Sauma;Javier Contreras.
IEEE Transactions on Power Systems (2013)

249 Citations

A kernel-oriented algorithm for transmission expansion planning

J. Contreras;F.F. Wu.
IEEE Transactions on Power Systems (2000)

243 Citations

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