Optimal Economic Dispatching of Active Distribution Network Based on Carbon Emission Trading and Sequential Output Reconstruction of Renewable Energy

With the gradual implementation of the “dual carbon” strategy, the introduction of carbon emission trading mechanism has become a central approach to realizing low carbon emission reduction. Moreover, the large-scale grid integration of intermittent energy sources results in a random operation state of the active distribution network. The simulation based on deterministic scenarios encounters difficulty in adapting to the complex power system operation mode. Starting with the description and analysis of uncertainty in renewable energy output, a stochastic differential equation model is employed to reconstruct its sequential output model. Based on the carbon emission trading mechanism, a three-stage ladder carbon emission trading cost model is then constructed, and the optimal economic dispatching model of active distribution network is proposed to minimize the operating cost. To address the challenging issue of probability constraint in scheduling model, the method of separated length transformation and convolution sequence operation is proposed to transform the chance constraint programming into easily solvable mixed integer linear programming. Finally, the proposed model is verified using active distribution system of T area, and the results demonstrate its feasibility and effectiveness.