广东工业大学学报 ›› 2024, Vol. 41 ›› Issue (05): 1-12.doi: 10.12052/gdutxb.240084

• 电气工程 •    下一篇

基于数据驱动的电-热-气综合能源系统概率多能流计算分析

周永旺, 蔡政彤, 许灿城, 倪强   

  1. 广东工业大学 自动化学院, 广东 广州 510006
  • 收稿日期:2024-07-30 出版日期:2024-09-25 发布日期:2024-10-08
  • 通信作者: 倪强(1987-),男,讲师,博士,主要研究方向为综合能源系统优化、电力电子系统故障诊断与健康管理,E-mail:nq666@gdut.edu.cn
  • 作者简介:周永旺(1966-),男,副教授,硕士,主要研究方向为电力系统分析计算与稳定控制、综合能源优化等,E-mail:zhouyongwang@sohu.com
  • 基金资助:
    国家自然科学基金资助项目(62103109)；广东省自然科学基金资助项目(2024A1515011966)

Probabilistic Multi-energy Flow Calculation and Analysis for Electricity-heating-gas Integrated Energy System Based on Data-driven

Zhou Yong-wang, Cai Zheng-tong, Xu Can-cheng, Ni Qiang   

  1. School of Automation, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2024-07-30 Online:2024-09-25 Published:2024-10-08

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摘要： 针对可再生能源与系统负荷波动对综合能源系统多能流分布的不确定性量化问题，提出一种基于数据驱动的综合能源系统概率多能流计算方法。首先，提出了考虑压缩机不同工作模式的综合能源系统多能流计算统一模型，并探讨了压缩机不同工作模式对能流分布的影响；其次，提出基于支持向量回归的概率能流计算方法，先通过多次重复的确定性多能流计算，构建数据样本集，再用支持向量回归挖掘出综合能源系统中已知负荷、网络节点信息与未知节点参数的非线性映射关系；最后，通过算例分析对提出的多能流计算统一模型在不同压缩机工作模式下的有效性进行了验证；通过与传统概率多能流计算方法对比研究，证明提出的数据驱动概率能流计算方法具有更高的计算精度与效率。

关键词: 综合能源系统, 压缩机工作模式, 不确定性量化, 概率多能流, 数据驱动

Abstract: In order to quantify the uncertainty of multi-energy flow distribution in the integrated energy system, a probabilistic multi-energy flow calculation method of integrated energy system based on data-driven is proposed. Firstly, a unified multi-energy flow calculation model suitable for different working modes of compressors in integrated energy system is established, and the impact of different operating modes of compressors on the multi-energy flow distribution is also discussed. Secondly, a probabilistic multi-energy flow calculation method based on support vector regression is developed. The method first constructs a data set by calculating deterministic multi-energy flow repeatedly, and then the support vector regression is used to mine the nonlinear mapping relationship between known loads, network node information and unknown node parameters in the integrated energy system. Finally, through case analysis, it is verified that the proposed unified multi-energy flow model can be applied to different compressor working conditions. By comparing with traditional probabilistic multi-energy flow calculation methods, it is shown that the proposed data-driven probabilistic multi-energy flow calculation method has higher computational accuracy and efficiency.

Key words: integrated energy system, compressor working modes, uncertainty quantification, probabilistic multi-energy flow, data-driven

中图分类号: 

  • TM744
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