2nd Workshop on Evolutionary Algorithms for Smart Grids (SmartEA)
at ​GECCO 2019 in Prague, July 13th-17th 2019

Call for submissions as PDF

Description and Topics

Sustainability is of significant importance due to increasing demands and limited resources worldwide. In particular, in the field of energy production and consumption, methods are required that allow to phase generation and load efficiently. The vast extension of renewable and distributed energy sources and the growing information infrastructure enable a fine screening of producers and consumers but require the development of tools for the analysis and understanding of large datasets about the energy grid. Key technologies in future ecological, economical and reliable energy systems are energy prediction of renewable resources, prediction of consumption as well as efficient planning and control strategies for network stability.

To enable financially and ecologically viable projects, optimization methods have taken over a key role for planning, optimizing and forecasting sustainable systems. Typically, these approaches make use of domain knowledge in order to achieve the required goal. Even in the case that explicit domain knowledge is not available, specialized methods can also handle large raw numerical sensory data directly, process them, generate reliable and just-in-time responses, and have high fault tolerance.

Scope and Topics

Following the success of the previous edition at GECCO2017 “Workshop on Evolutionary Algorithms for Smart Grids (SmartEA)” (http://ci4energy.uni-paderborn.de/smartEA/), the main goal of this workshop is to promote the research on evolutionary algorithms in smart grids. We are seeking innovative research articles including, but not limited to the following areas:

Submitted work should put an emphasis on modeling of solution spaces, on finding optimal representations and operators for evolutionary algorithms, and on employing and developing advanced evolutionary heuristics, e.g., for step size control, constraint handling, dynamic solution spaces, and multiple conflictive objectives.

Important Dates

These dates are strict, no extensions will be granted

Submission Guidelines

All papers should be in ACM (Association for Computing Machinery) format. Please see GECCO 2019 for details.

Workshop papers must be submitted using the GECCO submission site. After login, the authors need to select the “Workshop Paper” submission form. In the form, the authors must select the workshop they are submitting to. To see a sample of the “Workshop Paper” submission form go to GECCO’s submission site and chose “Sample Submission Forms”.

Submitted papers must not exceed 8 pages (excluding references) and are required to be in compliance with the GECCO 2019 Papers Submission Instructions. It is recommended to use the same templates as the papers submitted to the main tracks. It is not required to remove the author information if the workshop the paper is submitted to does not have a double-blind review process (please, check the workshop description or the workshop organizers on this).

All accepted papers will be presented at the corresponding workshop and appear in the GECCO Conference Companion Proceedings. By submitting a paper, the author(s) agree that, if their paper is accepted, they will:

Submit a final, revised, camera-ready version to the publisher on or before the camera-ready deadline Register at least one author before April 24, 2019 to attend the conference Attend the conference (at least one author) Present the accepted paper at the conference



Fernando Lezama, GECAD-Polytechnic of Porto, Portugal

Fernando Lezama received an M.Sc. degree (with Honors) in Electronic Engineering (2011), and a Ph.D. in ITCs (2014) both from the Monterrey Institute of Technology and Higher Education (ITESM), Mexico. Currently, he is a researcher at GECAD, Polytechnic of Porto, Portugal, where he works in the development of intelligent systems for optimization in smart grids. His research interests include computational intelligence, evolutionary computation, and optimization of smart grids and optical networks.

More information can be found at: here


Joao Soares, GECAD-Polytechnic of Porto, Portugal

João Soares has a BSc in computer science and a master in Electrical Engineering in Portugal, namely Polytechnic of Porto. He attained his PhD degree in Electrical and Computer Engineering at UTAD university. He his a researcher at GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development. His research interests include optimization in power and energy systems, including heuristic, hybrid and classical optimization.

More information can be found at: here


Paul Kaufmann, Mainz University, Germany

Paul Kaufmann is an Assistant Professor at the Mainz University, Germany. His main research interests are evolutionary algorithms, signal classification, and their application to adaptive and reconfigurable hardware systems. After receiving a Ph.D. in Evolvable Hardware (2013) from the University of Paderborn, he stayed at the Fraunhofer Institute for Wind Energy and Energy System Technology and the Energy Management and Power System Operation Group at the University of Kassel from 2012 to 2013. He is organizing the annual EvoENERGY Workshop at EvoStar, heading the IEEE CIS Educational Material subcommittee, has co-founded and is heading the IEEE Task Force on Computational Intelligence in the Energy Domain, and is member of the IEEE Task Force on Evolvable Hardware.

More information can be found at: here


Zita Vale, Polytechnic of Porto, Portugal

Zita Vale is full professor at the Polytechnic Institute of Porto and the director of the Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD). She received her diploma in Electrical Engineering in 1986 and her PhD in 1993, both from University of Porto. Zita Vale works in the area of Power and Energy Systems, with special interest in the application of Artificial Intelligence techniques. She has been involved in more than 50 funded projects related to the development and use of Knowledge-Based systems, Multi-Agent systems, Genetic Algorithms, Neural networks, Particle Swarm Intelligence, Constraint Logic Programming and Data Mining. She published over 800 works, including more than 100 papers in international scientific journals, and more than 500 papers in international scientific conferences.

More information can be found here