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

doi:10.12052/gdutxb.240084

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

更新时间：2026-05-27

- Probabilistic Multi-energy Flow Calculation and Analysis for Electricity-heating-gas Integrated Energy System Based on Data-driven
- Vol. 41, Issue 5, Pages: 1-12(2024)
- 作者机构：
  
  广东工业大学自动化学院,广东,广州,510006
- 作者简介：
- 基金信息：
- DOI：10.12052/gdutxb.240084
  CLC： TM744
- Published：2024
- 稿件说明：
移动端阅览
周永旺, 蔡政彤, 许灿城, 倪强. 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[J]. 广东工业大学学报, 2024, 41(5): 1-12.

Zhou Yong-wang, Cai Zheng-tong, Xu Can-cheng, et al. Probabilistic Multi-energy Flow Calculation and Analysis for Electricity-heating-gas Integrated Energy System Based on Data-driven[J]. 2024, 41(5): 1-12.
周永旺, 蔡政彤, 许灿城, 倪强. 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[J]. 广东工业大学学报, 2024, 41(5): 1-12. DOI： 10.12052/gdutxb.240084.

Zhou Yong-wang, Cai Zheng-tong, Xu Can-cheng, et al. Probabilistic Multi-energy Flow Calculation and Analysis for Electricity-heating-gas Integrated Energy System Based on Data-driven[J]. 2024, 41(5): 1-12. DOI： 10.12052/gdutxb.240084.

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。

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.

关键词

Keywords

references

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