2021 COMPETITION ON EVOLUTIONARY COMPUTATION IN THE ENERGY DOMAIN: SMART GRID APPLICATIONS

Following the success of the previous editions (CEC, GECCO, WCCI), we are launching a more challenging competition at major conferences in the field of computational intelligence. This GECCO 2021 competition proposes two tracks in the energy domain:

Track 1) Bi-level optimization of bidding strategies in local energy markets (LEM). This track is constructed under the same framework of the past competitions (therefore, former competitors can adapt their algorithms to this new track), representing a complex bi-level problem in which competitive agents in the upper-level try to maximize their profits, modifying and depending on the price determined in the lower-level problem (i.e., the clearing price in the LEM), thus resulting in a strong interdependence of their decisions.

Track 2) Flexibility management of home appliances to support DSO requests. A model for aggregators flexibility provision in distribution networks that takes advantage of load flexibility resources allowing the re-schedule of shifting/real-time home-appliances to provision a request from a distribution system operator (DSO) is proposed. The problem can be modeled as a Mixed-Integer Non-Linear Programming (MINLP) in which the aggregator strives to match a flexibility request from the DSO/BRP, paying remuneration to the households participating in the DR program according to their preferences and the modification of their baseline profile.

Note: Both tracks are developed to run under the same framework of past competitions.

Instructions: 

Rules

– Participants will propose and implement metaheuristic algorithms (e.g., evolutionary algorithms, swarm intelligence, estimation of distribution algorithm, etc.) to solve complex problems in the energy domain by offering two distinct tracks.

– The organizers provide a framework, implemented in MATALAB© 2014b 64 bits (Download here), in which participants can easily test their algorithms (we also provide a differential evolution algorithm implementation as an example). The guidelines  (Download here) include the necessary information to understand the problems, how the solutions are represented, and how the fitness function is evaluated. Those elements are common for all participants.

– Since the proposed algorithms might have distinct sizes of population and run for a variable number of iterations, a maximum number of “10,000 function evaluations” is allowed for track 1 and “100,000” function evaluations are allowed for track 2. The convergence properties of the algorithms are not a criterion to be qualified in this competition.

– Only random seed initial solutions are allowed in this competition. Heuristics and special tweaks for initial solutions are not accepted.

– 20 independent trials should be performed in the framework by each participant.

How to submit an entry

–The winner will be the participant with the minimum ranking index in each independent track, which is calculated as the average value over the 20 trials of the expected fitness value plus. We will make an independent rank for each track (i.e., we will have a winner for each track).

– Each participant is kindly requested to put the text files corresponding to final results (see guideline document), as well as the implementation files (codes), obtained by using a specific optimizer, into a .zip named CEC2021_trackX_AlgorithmName_ParticipantName.zip (e.g. CECI2021_track2_DE_Lezama.zip).