Multi-objective confidence gap decision based robust optimal dispatch of integrated energy system using entropy expectation maximization GMM

Abstract

To cope with the uncertainty of renewable energy output and achieve robust optimal dispatch of the integrated energy system, the confidence gap decision theory with Gaussian mixed probability distribution is introduced into the dispatch model. The entropy expectation maximization Gaussian mixture model (GMM), which is developed by adding an entropy factor to the expectation maximization algorithm, is proposed to reduce the initial value sensitivity in the GMM hidden variables solution process. Considering the comprehensive optimization objectives of maximizing exergy efficiency and minimizing operating cost, a multi-objective robust optimal dispatch model based on the confidence gap decision is established. And the model is transformed into a deterministic model according to the uncertainty theory for the sake of convenient calculation. Further, an efficient non-dominated sorting mechanism is combined with an improved differential evolution algorithm to efficiently solve the model. Finally, the effectiveness and superiority of the proposed method are verified by example analysis.