Following the success of the previous editions at major events IEEE PES; CEC; WCCI, and GECCO, we are launching the summer finals of the competition at major conferences in the field of computational intelligence. This year, the GECCO 2025 competition proposes one track in the energy domain that follows the winter challenge launched at the IEEE SSCI 2025 conference:
Testbed - Risk-based optimization of aggregators’ day-ahead energy resource management (ERM) considering the uncertainty of high penetration of distributed energy resources (DER). This testbed represents a centralized day-ahead ERM in a smart grid with a 13-bus distribution network using a 15-scenario case study with 3 scenarios considering extreme events (high impact and low probability). A conditional value-at-risk (CVaR) mechanism is used to measure the risk associated with extreme events for a confidence level (α) of 95%. We also added some restrictions to the initialization of solutions and allowed repairs, and tweak heuristics.
Note: The track is developed to run under the same framework as past competitions.

Competition goals:
The GECCO 2025 competition on “2025 Competition on Evolutionary Computation in the Energy Domain: Summer Finals of the Risk-based Energy Scheduling” has the purpose of bringing together and testing the more advanced Computational Intelligence (CI) techniques applied to energy domain problems, namely a centralized risk-based energy resource management considering extreme event occurrence. The competition provides a coherent framework where participants and practitioners of CI can test their algorithms to solve a real-world optimization problem in the energy domain. The participants have the opportunity to evaluate if their algorithms can rank well in the proposed problem since we understand the validity of the “no-free lunch theorem”, making this contest a unique opportunity worth exploring the applicability of the developed approaches in a real-world problem beyond the typical benchmark and standardized CI problems.