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2026 Competition on Evolutionary Computation in the Energy Domain: Fairness-aware Pricing in Energy Communities

Deadline: 2026-06-01
Webpage: https://www.gecad.isep.ipp.pt/ERM-competitions/2026-1/

Description

This competition challenges participants to develop and benchmark evolutionary algorithms for optimizing fairness-oriented energy pricing strategies in Local Energy Communities (LECs). Unlike traditional optimization tasks that prioritize cost reduction, this problem emphasizes equitable cost distribution, user satisfaction, and fairness.

Participants must design metaheuristic algorithms that optimize local energy prices, using a provided MATLAB framework and fairness metrics such as Jain’s Fairness Index, standard deviation of energy bills, and Quality of Experience (QoE). The energy transactions are pre-optimized through a Mixed-Integer Linear Programming (MILP) model, allowing algorithms to focus exclusively on price optimization.

Abstract Submission

The competition allows 2-page contributions to the GECCO Companion to present short descriptions of the competition entry, focusing on algorithmic design, strengths and limitations. The 2-page abstract paper will require at least one author to register at the conference as a presenter. It is important to mention that these 2-page abstracts ARE NOT APC Eligible (no publication fee has to be paid by the authors) under the current ACM Open publishing guidelines. The following dates are relevant for these submissions:

  • Submission opening: April 1, 2026
  • Submission deadline: April 21, 2026
  • Notification: April 28, 2026
  • Camera-ready: May 5, 2026
  • Author's mandatory registration: May 11, 2026

Organizers

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Fernando Lezama

Fernando Lezama received the Ph.D. in ICT from the ITESM, Mexico, in 2014. Since 2017, he is a researcher at GECAD, Polytechnic of Porto, where he contributes in the application of computational intelligence (CI) in the energy domain. Dr. Lezama is part of the National System of Researchers of Mexico since 2016, Chair of the IEEE CIS TF 3 on CI in the Energy Domain, and has been involved in the organization of special sessions, workshops, and competitions (at IEEE WCCI, IEEE CEC and ACM GECCO), to promote the use of CI to solve complex problems in the energy domain.


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José Almeida

José Almeida has a degree in Electrical and Computer Engineering (2019) from Polytechnic Institute of Porto, Porto. He is currently working towards the M.Sc. degree in electrical engineering from the Polytechnic Institute of Porto (ISEP/IPP), Porto, Portugal. He is a Researcher with GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, ISEP/IPP. His research interests include optimization in power and energy systems; electric vehicles; smart grids; distributed energy resource management; and electricity markets.


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Joao Soares

João Soares has a B.Sc. in computer science (2008) and a master (2011) in Electrical Engineering by Polytechnic of Porto. He attained his Ph.D. degree in Electrical and Computer Engineering at UTAD university (2017). He is a researcher at ISEP/GECAD and his research interests include optimization in power and energy systems, including heuristic, hybrid and classical optimization.


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Filipe Sousa

Filipe Sousa is currently pursuing a Master's Degree in Industrial Management at Instituto Superior de Engenharia do Porto (ISEP) and holds a Master's Degree in Multimedia from Faculdade de Engenharia da Universidade do Porto (FEUP). He is currently a Researcher at GECAD-Polytechnic of Porto. Additionally, he has been involved in organizing workshops, webinars, special sessions, and has disseminated multiple projects (e.g., H2020).


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Zita Vale

Zita Vale received the Ph.D. degree in electrical and computer engineering from the University of Porto, Porto, Portugal, in 1993. She is currently a Professor with the Polytechnic Institute of Porto, Porto. Her research interests focus on artificial intelligence applications, smart grids, electricity markets, demand response, electric vehicles, and renewable energy sources.