1. School of Electrical Engineering, Southeast University, Nanjing 210096, China;2. Electric Power Research Institute of State Grid Tianjin Electric Power Company, Tianjin 300384, China

To meet the emerging trend of low carbonization in electric power industry, a regional carbon emission management model is presented based on multi-objective probabilistic optimal power flow under the background of renewable energy integration. An improved imperialist competitive algorithm coupled with fuzzy satisfying decision is also proposed to obtain the ‘optimal solution' from the multi-objective problem. Contrasting to the goal of minimizing generation cost and total carbon emission in the traditional model, this method could prevent some regions from being over-polluted by reducing carbon emission imbalance among them. To handle the uncertainty caused by renewable power injections, the stochastic response surface method is employed considering correlation in probabilistic load flow to circumvent the voltage violation and line overload. Finally, case studies of Matpower 30-node test system and the actual regional power network in Jiangsu are performed. The results show that the proposed model and algorithm could effectively manage carbon emissions of both entire system and local regions, as well as give guidance in choosing optimal sites for renewable power stations.