Optimal Low-Carbon Economic Dispatch Strategy for Active Distribution Networks with Participation of Multi-Flexible Loads

Abstract

Optimization dispatch with flexible load participation in new power systems significantly enhances renewable energy accommodation, though the potential of flexible loads remains underexploited. To improve renewable utilization efficiency, promote wind/PV consumption and reduce carbon emissions, this paper establishes a low-carbon economic optimization dispatch model for active distribution networks incorporating flexible loads and tiered carbon trading. First, a hybrid SSA (Sparrow Search Algorithm)–CNN-LSTM model is adopted for accurate renewable generation forecasting. Meanwhile, multi-type flexible loads are categorized into shiftable, transferable and reducible loads based on response characteristics, with tiered carbon trading mechanism introduced to achieve low-carbon operation through price incentives that guide load-side participation while avoiding privacy leakage from direct control. Considering the non-convex nonlinear characteristics of the dispatch model, an improved Beluga Whale Optimization (BWO) algorithm is developed. To address the diminished solution diversity and precision in conventional BWO evolution, Tent chaotic mapping is introduced to resolve initial parameter sensitivity. Finally, modified IEEE-33 bus system simulations demonstrate the method’s validity and feasibility.