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

doi:10.12052/gdutxb.240084

Abstract

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

CLC Number:

TM744

Zhou Yong-wang, Cai Zheng-tong, Xu Can-cheng, Ni Qiang. Probabilistic Multi-energy Flow Calculation and Analysis for Electricity-heating-gas Integrated Energy System Based on Data-driven[J].Journal of Guangdong University of Technology, 2024, 41(05): 1-12.

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URL: https://xbzrb.gdut.edu.cn/EN/10.12052/gdutxb.240084

https://xbzrb.gdut.edu.cn/EN/Y2024/V41/I05/1

References

[1] 孙宏斌, 潘昭光, 郭庆来. 多能流能量管理研究: 挑战与展望[J]. 电力系统自动化, 2016, 40(15): 1-8.
SUN H B, PAN Z G, GUO Q L. Energy management for multi-energy flow: challenges and prospects[J]. Automation of Electric Power Systems, 2016, 40(15): 1-8.
[2] 王舒萍, 张沈习, 程浩忠, 等. 考虑天然气系统初值优化的综合能源系统改进多能流计算方法[J]. 电力自动化设备, 2022, 42(1): 28-36.
WANG S P, ZHANG S X, CHENG H Z, et al. Improved multi-energy flow calculation method for integrated energy system considering initial value optimization of natural gas system[J]. Electric Power Automation Equipment, 2022, 42(1): 28-36.
[3] SHABANPOUR-HAGHIGHI A, SEIFI A R. An integrated steady-state operation assessment of electrical, natural gas, and district heating networks[J]. IEEE Transactions on Power Systems, 2016, 31(5): 3636-3647.
[4] MASSRUR H R, NIKNAM T, AGHAEI J, et al. Fast decomposed energy flow in large-scale integrated electricity-gas-heat energy systems[J]. IEEE Transactions on Sustainable Energy, 2018, 9(4): 1565-1577.
[5] CHEN Y, ZHAO J, MA J. Fast decoupled multi-energy flow calculation for integrated energy system[J]. Journal of Modern Power Systems and Clean Energy, 2020, 8(5): 951-960.
[6] 王英瑞, 曾博, 郭经, 等. 电–热–气综合能源系统多能流计算方法[J]. 电网技术, 2016, 40(10): 2942-2950.
WANG Y R, ZENG B, GUO J, et al. Multi-energy flow calculation method for integrated energy system containing electricity, heat and gas[J]. Power System Technology, 2016, 40(10): 2942-2950.
[7] LI J H, HUANG Y J, ZHU M S. Gradient descent iterative method for energy flow of integrated energy system considering multiple modes of compressors[J]. Energy Conversion and Management, 2020, 207: 112534.
[8] 钟俊杰, 李勇, 曾子龙, 等. 综合能源系统多能流准稳态分析与计算[J]. 电力自动化设备, 2019, 39(8): 22-30.
ZHONG J J, LI Y, ZENG Z L, et al. Quasi-steady-state analysis and calculation of multi-energy flow for integrated energy system[J]. Electric Power Automation Equipment, 2019, 39(8): 22-30.
[9] 闵庆久, 马兆兴, 马英姿. 基于PSO-Newton法的电–气综合能源系统能流计算[J]. 电力工程技术, 2021, 40(1): 33-39.
MIN Q J, MA Z X, MA Y Z. Energy flow calculation of integrated power-gas energy system based on PSO-newton method[J]. Electric Power Engineering Technology, 2021, 40(1): 33-39.
[10] SHABANPOUR-HAGHIGHI A, SEIFI A R. Simultaneous integrated optimal energy flow of electricity, gas, and heat[J]. Energy Conversion and Management, 2015, 101: 579-591.
[11] 陈胜, 卫志农, 孙国强, 等. 电–气混联综合能源系统概率能量流分析[J]. 中国电机工程学报, 2015, 35(24): 6331-6340.
CHEN S, WEI Z N, SUN G Q, et al. Probabilistic energy flow analysis in integrated electricity and natural-gas energy systems[J]. Proceedings of the CSEE, 2015, 35(24): 6331-6340.
[12] CHEN S, WEI Z N, SUN G Q, et al. Multi-linear probabilistic energy flow analysis of integrated electrical and natural-gas systems[J]. IEEE Transactions on Power Systems, 2017, 32(3): 1970-1979.
[13] 张儒峰, 姜涛, 李国庆, 等. 基于最大熵原理的电–气综合能源系统概率能量流分析[J]. 中国电机工程学报, 2019, 39(15): 4430-4441.
ZHANG R F, JIANG T, LI G Q, et al. Maximum entropy based probabilistic energy flow calculation for integrated electricity and natural gas systems[J]. Proceedings of the CSEE, 2019, 39(15): 4430-4441.
[14] 杨家豪. 区域综合能源系统冷–热–电–气概率多能流计算[J]. 电网技术, 2019, 43(1): 74-83.
YANG J H. Probabilistic multi-energy flow calculation for regional integrated energy system containing cooling, heating, electricity and gas[J]. Power System Technology, 2019, 43(1): 74-83.
[15] YUAN J, WENG Y. Support matrix regression for learning power flow in distribution grid with unobservability[J]. IEEE Transactions on Power Systems, 2021, 37(2): 1151-1161.
[16] XU Y, HU Z, MILI L, et al. Probabilistic power flow based on a gaussian process emulator[J]. IEEE Transactions on Power Systems, 2020, 35(4): 3278-3281.
[17] LIU X. Combined analysis of electricity and heat networks[D]. Cardiff: Cardiff University, 2013.
[18] LI Q, AN S, GEDRA T W. Solving natural gas loadflow problems using electric load flow techniques [C]//Proceedings of the North American Power Symposium. Rolla: NAPS, 2003: 1-7.
[19] 卫志农, 仲磊磊, 薛溟枫, 等. 基于数据驱动的电-热互联综合能源系统线性化潮流计算[J]. 电力自动化设备, 2019, 39(8): 31-37.
WEI Z N, ZHONG L L, XUE M F, et al. Linearization flow calculation for integrated electricity-heat energy system based on data-driven[J]. Electric Power Automation Equipment, 2019, 39(8): 31-37.
[20] TIAN H, ZHAO H, LIU C, et al. A dual-driven linear modeling approach for multiple energy flow calculation in electricity-heat system[J]. Applied Energy, 2022, 314: 118872.
[21] 陈乾, 张沈习, 程浩忠, 等. 基于径向基函数随机响应面法的综合能源系统概率能流计算[J]. 中国电机工程学报, 2022, 42(22): 8075-8089.
CHEN Q, ZHANG S X, CHENG H Z, et al. Probabilistic energy flow calculation for integrated energy systems based on radial basis function-stochastic response surface method[J]. Proceedings of the CSEE, 2022, 42(22): 8075-8089.
[22] 江茂泽, 徐羽镗, 王寿喜, 等. 输配气管网的模拟与分析[M]. 北京: 石油工业出版社, 1995: 205-219.
[23] ZENG Q, FANG J K, LI J H, et al. Steady-state analysis of the integrated natural gas and electric power system with bi-directional energy conversion[J]. Applied Energy, 2016, 184: 1483-1492.
[24] LI Y Z, WU Q H. Downside risk constrained probabilistic optimal power flow with wind power integrated[J]. IEEE Transactions on Power Systems, 2015, 31(2): 1649-1650.
[25] 魏步晗, 鲍刚, 李振华. 基于支持向量回归预测模型考虑天气因素和分时电价因素的短期电力负荷预测[J]. 电网与清洁能源, 2023, 39(11): 9-19.
WEI B H, BAO G, LI Z H. Short-term electricity load forecasting based on support vector regression forecasting model considering weather factors and time-of-use tariff factors[J]. Power System and Clean Energy, 2023, 39(11): 9-19.
[26] 朱宇迪. 基于数据驱动的潮流非线性回归建模及其灵敏度解析[D]. 吉林: 东北电力大学, 2024.
[27] LI Y, LI W, YAN W, et al. Probabilistic optimal power flow considering correlations of wind speeds following different distributions[J]. IEEE Transactions on Power Systems, 2014, 29(4): 1847-1854.

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