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

江涛; 徐聪; 贾少辉; 王深; 张亚健

doi:10.11959/j.issn.1000-0801.2024162

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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

研究与开发 | 更新时间：2024-09-23

- 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
- 电信科学 2024年40卷第8期页码：108-120
- 作者机构：
  
  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
- 作者简介：
  
  [ "江涛（1984- ），男，中远海运（天津）有限公司经济师，主要研究方向为可再生能源及数字技术管理。" ]
  [ "徐聪（1982- ），男，中远海运（天津）有限公司工程师，主要研究方向为信息技术。" ]
  [ "贾少辉（1993- ），男，中远海运（天津）有限公司工程师，主要研究方向为数据分析和应用。" ]
  [ "王深（1987- ），男，中远海运（天津）有限公司高级工程师，主要研究方向为人工智能。" ]
  [ "张亚健（1991- ），男，博士，上海大学机电工程与自动化学院副教授，主要研究方向为电力系统优化运行、电力系统网络化控制。" ]
- 基金信息：
  
  国家自然科学基金青年项目(62103254);中国远洋海运集团“十四五”第一批科研项目(2023-1-Z010-02)
- DOI：10.11959/j.issn.1000-0801.2024162
  中图分类号： TM73
- 收稿日期：2024-04-18，
  
  修回日期：2024-05-08，
  
  纸质出版日期：2024-08-20
- 稿件说明：
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江涛,徐聪,贾少辉等.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[J].电信科学,2024,40(08):108-120.

JIANG Tao,XU Cong,JIA Shaohui,et al.Low-carbon optimization planning method for integrated energy system based on DG uncertainty affine model[J].Telecommunications Science,2024,40(08):108-120.
江涛,徐聪,贾少辉等.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[J].电信科学,2024,40(08):108-120. DOI： 10.11959/j.issn.1000-0801.2024162.

JIANG Tao,XU Cong,JIA Shaohui,et al.Low-carbon optimization planning method for integrated energy system based on DG uncertainty affine model[J].Telecommunications Science,2024,40(08):108-120. DOI： 10.11959/j.issn.1000-0801.2024162.

摘要

针对风电、光伏等新能源分布式发电系统（distributed generator，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IEEE 33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。

Abstract

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%.

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references

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