Pollution emission reduction and factor influence effect analysis for energy system under complex conditions

Scientific energy system planning is beneficial to relieve the contradiction between energy supply and demand at present stage. However, the energy system consists of multiple complex subsystems, which contains a variety of uncertainties, and there are complex interactions among subsystems. With considering energy, economy and environment, this paper constructs an energy system planning model, based on uncertain optimization methods including interval programming, two-stage stochastic programming and chance constrained programming. In addition, this paper carries out sensitivity analysis of the model optimization results based on factorial analysis method, selecting main factors affecting pollution emission and revealing its influence and potential interaction. The model can effectively deal with pollutant emissions under complex conditions, optimize the allocation of system resources, and promote the adjustment of energy structure. The results show that on the basis of meeting the system operation and energy demands, it can effectively reduce the system cost, promote the pollution and emission reduction, and achieve the win-win of energy development and environmental protection.