Multi-objective optimal scheduling of distribution networks with load aggregator involvement

The widespread distribution and large number of user-side resources pose challenges for direct dispatch by the power grid. To fully leverage the regulation potential of demand-side resources, this paper proposes a multi-objective scheduling model for distribution networks with load aggregator involvement, aiming to minimize economic cost, reduce network losses, and increase renewable energy utilization. Aggregated models of air conditioners and electric vehicles are developed based on their operational characteristics and user demand. Fuzzy chance constraints are introduced to address the uncertainty in demand response participation. The model is solved using the AUGMECON-R method to generate the Pareto front, and the TOPSIS approach with comprehensive weighting is used to identify the optimal scheduling scheme. The simulation results demonstrate that the proposed method cuts economic cost by $159, reduces network losses by 0.201 MW, and increases the proportion of renewable energy supply by 1.5 percentage points. The results indicate that the model improves the operational performance of the distribution network operation by fully utilizing the flexibility of user-side resources. • Aggregation models for ACs and EVs based on their operational characteristics. • Response potential assessment for ACs and EVs according to user energy consumption demands. • A multi-objective model for distribution networks considering the involvement of LA. • An AUGMECON-R method for multi-objective solving to obtain Pareto sets. • TOPSIS method with the comprehensive weight to select the optimal scheduling scheme.