基于DG不确定仿射模型的综合能源系统低碳优化规划方法  

Low-carbon optimization planning method for integrated energy system based on DG uncertainty affine model

作　　者：江涛 徐聪 贾少辉 王深 张亚健 JIANG Tao;XU Cong;JIA Shaohui;WANG Shen;ZHANG Yajian(COSCO Shipping(Tianjin)Co.,Ltd.,Tianjin 300010,China;Tianjin Keepsens Information Technology Co.,Ltd.,Tianjin 300010,China;School of Mechatronic Engineering and Automation,Shanghai University,Shanghai 200444,China)

机构地区：[1]中远海运(天津)有限公司,天津300010 [2]天津鲲鹏信息技术有限公司,天津300010 [3]上海大学机电工程与自动化学院,上海200444

出　　处：《电信科学》2024年第8期108-120,共13页Telecommunications Science

基　　金：国家自然科学基金青年项目(No.62103254);中国远洋海运集团“十四五”第一批科研项目(No.2023-1-Z010-02)。

摘　　要：针对风电、光伏等新能源分布式发电系统(distributedgenerator,DG)受环境因素变化导致出力不确定、现有碳交易模型交易价格固定导致减碳成本增多的问题,提出基于DG不确定仿射模型的综合能源系统低碳优化规划方法。首先,根据环境条件建立基于矩阵形式仿射算法的DG出力模型,降低DG出力不确定性对综合能源系统优化规划的影响。其次,将碳排放量作为惩罚措施引入综合能源系统优化规划中,改进传统碳交易模型,降低综合能源系统碳排放量。然后,基于差分进化粒子群优化算法,对建立的综合能源系统低碳规划模型求解,避免算法在寻优过程陷入局部最优。最后,在IEEE33节点系统上的仿真结果表明,所提规划方法比传统随机优化和区间优化规划方法分别降低了8.68%和2.93%的总投资成本,比传统固定碳交易价格模型降低了6.28%的碳排放量。Aiming at the problem that the output of distributed generators(DG)of new energy sources such as wind power and photovoltaic is uncertain due to changes in environmental factors,and the transaction price of the existing carbon trading model is fixed,resulting in increased carbon reduction costs,an integrated energy system optimization planning method that takes into account dynamic carbon emission constraints and DG uncertainty was proposed.Firstly,a DG output model based on matrix affine algorithm was established according to environmental conditions to reduce the impact of DG output uncertainty on the optimization planning of the integrated energy system.Secondly,carbon emissions was introduced as a punitive measure into the optimization planning of the integrated energy system to improve the traditional carbon trading model and reduce the carbon emissions of the integrated energy system.Then,based on the differential evolution-particle swarm optimization algorithm,the established low-carbon planning model of the integrated energy system was solved to avoid the algorithm from falling into local optimality during the optimization process.Finally,the simulation results on an IEEE 33 node system show that the proposed planning method reduces the total investment cost by 8.68%and 2.93%respectively compared with the traditional stochastic optimization and interval optimization planning methods.Compared with the traditional fixed carbon trading price model,carbon emissions are reduced by 6.28%.

关 键 词：阶梯式碳交易 综合能源系统 仿射模型 差分进化粒子群算法 区间优化 

分 类 号：TM73[电气工程—电力系统及自动化]