计及碳排放轨迹的综合能源系统动态优化调度方法OA

With the increasing of global pressure to reduce carbon emissions day by day,it has become critically urgent to mini-mize carbon emissions in the operation of integrated energy systems.In response to this challenge,this paper proposes a dynamic optimal scheduling method for integrated energy systems that considers the carbon emission trajectory.Firstly,a carbon emission trajectory model for integrated energy systems is developed,and a new scheduling framework is introduced.Multiple objective op-timization problem,including carbon emission minimization,energy supply-demand balance,and system operation costs,are comprehensively addressed.The scheduling strategy is adaptively adjusted using a deep reinforcement learning algorithm.Sec-ond,to meet the specific requirements of low-carbon energy systems,a robust and flexible state space and action space are con-structed.Additionally,a composite reward function based on carbon emissions and energy efficiency optimization is designed to ensure that the system achieves optimal scheduling in a dynamically changing environment.Finally,the effectiveness of the pro-posed dynamic optimal scheduling method is validated through simulation experiments under various scenarios.A comparative analysis with other optimal scheduling methods demonstrate the significant advantages of this approach in enhancing energy utili-zation efficiency and reducing carbon emissions.