Probabilistic Multi-Energy Flow Calculation of Electricity-Gas Integrated Energy Systems With Hydrogen Injection

被引:24
|
作者
Zhang, Shenxi [1 ]
Wang, Shuping [1 ]
Zhang, Zhenyuan [2 ]
Lyu, Jiawei [1 ]
Cheng, Haozhong [1 ]
Huang, Mingyu [3 ]
Zhang, Qingping [3 ]
机构
[1] Shanghai Jiao Tong Univ, Minist Educ, Key Lab Control Power Transmiss & Convers, Elect Engn Dept, Shanghai 200240, Peoples R China
[2] Univ Elect Sci & Technol China, Chengdu 610054, Peoples R China
[3] State Grid Ningxia Elect Power Co Ltd, Elect Power Res Inst, Yinchuan 750002, Ningxia, Peoples R China
关键词
Hydrogen; Steady-state; Pipelines; Mathematical model; Jacobian matrices; Gravity; Probabilistic logic; Cumulant method; electricity-gas integrated energy systems; hydrogen injection; Jacobian matrix; Nataf transformation; probabilistic multienergy flow; POWER-FLOW; LOAD FLOW; NATAF TRANSFORMATION; NATURAL-GAS; MANAGEMENT; CUMULANT; NETWORK;
D O I
10.1109/TIA.2021.3094487
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Probabilistic multienergy flow (PMEF) analysis is the fundamental of planning and operation of integrated energy systems (IES) considering uncertainties. The injection of hydrogen will make the PMEF calculation more complex and can deeply affect the distribution of energy flows. This article studies an efficient PMEF calculation method which can obtain the probabilistic information of electricity-gas IES with hydrogen injection. First, the steady-state model of electricity-gas IES with hydrogen injection is established, in which the gas network with hydrogen injection is formulated in compact matrix form. Second, the Jacobian matrix for the steady-state model of electricity-gas IES with hydrogen injection is derived. Third, the cumulant method and Nataf transformation are applied to calculate the PMEF considering the correlations. Finally, case studies are carried out on a coupled IES, which consists of modified IEEE 33-bus electricity system and 11-node gas system. The results demonstrate that the proposed PMEF method can reduce computational time greatly while keeping high computational accuracy when compared with the Monte-Carlo simulation method.
引用
收藏
页码:2740 / 2750
页数:11
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