Optimal Active-Reactive Power Dispatch for Distribution Network With Carbon Trading Based on Improved Multi-Objective Equilibrium Optimizer Algorithm

In distribution networks with a high proportion of renewable energy, the optimal active-reactive power dispatch problem (OARPD) is increasingly complex due to the volatility and randomness of wind and solar output, as well as variations in grid load. This paper proposes a new low-carbon scheduling model that incorporates a tiered carbon emission trading (CET) mechanism, minimizes operating costs, and reduces voltage deviations. Additionally, to address constraints on the number of discrete device actions within the scheduling period, a dynamic reactive power optimization strategy based on tiered operating costs is introduced. Then proposed an improved multi-objective equilibrium optimizer (IMOEO) algorithm for solving the OARPD problem with renewable generators. The IMOEO algorithm incorporates a Sobol sequence initialization method, dynamic adjustment factors, and particles that employ various evolutionary strategies based on the crowding distance. These elements are integrated to enhance population diversity and improve global exploration capabilities. Subsequently, the algorithm is applied to an modified IEEE-33 distribution network, followed by a thorough statistical analysis of the results. The findings indicate that IMOEO outperforms other methods in achieving a superior non-dominated Pareto front, effectively addresses the OARPD problem with renewable energy, and delivers high-quality solutions.