Cross Entropy Covariance Matrix Adaptation Evolution Strategy for Solving the Bi-Level Bidding Optimization Problem in Local Energy Markets

The increased penetration of renewables in power distribution networks has motivated significant interest local energy systems. One the main goals markets is to promote participation small consumers transactions. Such transactions can be modeled as a bi-level optimization problem which players (e.g., consumers, prosumers, or producers) at upper level try maximize their profits, whereas market mechanism lower maximizes transacted. However, strategic bidding complex NP-hard problem, due its inherently nonlinear and discontinued characteristics. Thus, this article proposes application hybridized Cross Entropy Covariance Matrix Adaptation Evolution Strategy (CE-CMAES) tackle such problem. proposed CE-CMAES uses cross entropy for global exploration search space covariance matrix adaptation evolution strategy exploitation. prevents premature convergence while efficiently exploring space, thanks adaptive step-size mechanism. performance algorithm tested through simulation practical system with renewable penetration. comparative analysis shows that achieves superior results concerning overall cost, mean fitness, Ranking Index (i.e., metric used competition evaluation) compared state-of-the-art algorithms. Wilcoxon Signed-Rank Statistical test also applied, demonstrating are statistically different from other