Artificial Intelligence in Power and Energy Systems

Societies are highly dependent on electricity use to ensure safe, reliable, and comfortable living. The increase of electricity demand is expected to continue in the future and it is considered a crucial requirement for economic development. Concerns about the impact of electricity use in the environment and about the eventual fuel based primary source shortage are presently taken as very serious at scientific, economic and politic levels. These concerns have led to intensive research and to new energy policies envisaging the increased use of renewable energy sources for electricity production and increased energy use efficiency.

In such a dynamic, complex, and competitive environment as the power and energy sector, the use of artificial intelligence is of crucial importance to enable taking full advantage from the opportunities in the field in order to overcome the challenges that are constantly arising.

This track aims at bringing together different experiences in the application of artificial intelligence to power and energy problems. This track targets the contribution of the main international experts in the field, both from academia and industry.

The authors of the two best papers will be invited to publish an extended version of their work in the Energy Informatics journal from Springer.


The topics of interest include, but are not limited to: 

  • Agent-based Smart Grid Simulation
  • Big Data Applications for Energy Systems
  • Coalitions and Aggregations of Smart Grid and Market Players
  • Consumer Profiling
  • Context Aware Systems
  • Data-Mining Approaches in Smart Grids
  • Decision Support Approaches for Smart Grids
  • Demand Response Aggregation
  • Demand Response Integration in the Market
  • Demand Response Remuneration Methods
  • Electricity Market Modelling and Simulation
  • Electricity Market Negotiation Strategies
  • Energy Resource Management in Buildings
  • Information technology applications
  • Innovative Demand Response Models and Programs
  • Innovative Energy Tariffs
  • Integration of Electric Vehicles in the Power System
  • Intelligent Approaches for Microgrid Management
  • Intelligent Home Management Systems
  • Intelligent methods for Demand Management
  • Intelligent Resources Scheduling
  • Intelligent Supervisory Control Systems
  • Knowledge-based approaches for Power and Energy Systems
  • Load Forecast
  • Market Models for Variable Renewable Energy
  • Multi-Agent Applications for Smart Grids
  • Multi-Agent Systems in Power and Energy Systems
  • Other Artificial Intelligence-based Methods for Power and Energy Systems
  • Real-time simulation
  • Reliability, Protection and Network Security Methods
  • Renewable Energy Forecast using Computational Intelligence
  • Semantic communication and data
  • Smart Sensors and Advanced Metering Infrastructure

Organisation Committee

  • Zita Vale, Polytechnic of Porto, Portugal
  • Tiago Pinto, Polytechnic of Porto, Portugal
  • Pedro Faria, Polytechnic of Porto, Portugal
  • Elena Mocanu, University of Twente, The Netherlands
  • Decebal Constantin Mocanu, Technical University of Eindhoven, The Netherlands

Program Committee

  • Omid Abrishambaf, SOLUTE, Spain
  • Hugo Algarvio, Laboratório Nacional de Energia e Geologia, Portugal
  • Gustavo Arroyo-Figueroa, Instituto Nacional de Electricidad y Energias Limpias, Mexico
  • Alfonso Briones, Universidad de Salamanca, Spain
  • Rui Castro, Universidade de Lisboa, Portugal
  • João P. S. Catalão, Universidade do Porto, Portugal
  • Bo Nørregaard Jørgensen, University of Southern Denmark, Denmark
  • Germano Lambert-Torres, PS Solutions, Brazil
  • Fernando Lopes, Laboratório Nacional de Energia e Geologia, Portugal
  • Phuong Nguyen, Eindhoven University of Technology, The Netherlands
  • Dagmar Niebur, Drexel University, United States
  • Isabel Praça, Instituto Superior de Engenharia do Porto, Portugal
  • Sérgio Ramos, Instituto Superior de Engenharia do Porto, Portugal
  • Jose L. Rueda, Delft University of Technology, The Netherlands
  • Pierluigi Siano, Università degli Studi di Salerno, Italy