Multi-Linear Probabilistic Energy Flow Analysis of Integrated Electrical and Natural-Gas Systems

被引：157

作者：

Chen, Sheng ^{[1
]}

Wei, Zhinong ^{[1
]}

Sun, Guoqiang ^{[1
]}

Cheung, Kwok W. ^{[2
]}

Sun, Yonghui ^{[1
]}

机构：

[1] Hohai Univ, Coll Energy & Elect Engn, Nanjing 210098, Jiangsu, Peoples R China

[2] GE Grid Solut, Redmond, WA 98052 USA

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 2017年 / 32卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Integrated electrical and gas systems; Monte Carlo simulation (MCS); multi-linear method; power to gas (P2G); probabilistic energy flow analysis; MONTE-CARLO-SIMULATION; POWER-FLOW; LOAD FLOW; WIND; UNCERTAINTY; NETWORK; MODEL;

D O I：

10.1109/TPWRS.2016.2597162

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The deep interdependence between electrical and gas systems entails a potential threat to the security (or reliability) of both systems. It is imperative to investigate the impacts of massive uncertainties on the overall secure and economical operation of both systems. In this paper, a probabilistic energy flow framework of integrated electrical and gas systems is initially proposed considering correlated varying energy demands and wind power. Three aspects of couplings between electrical and gas systems are considered: gas-fired generators, electric-driven compressors, and energy hubs integrated with power to gas (P2G) units. Furthermore, a multilinear method is specially designed to produce a deterministic energy flow solution for each sample generated by Monte Carlo simulation (MCS). Finally, test results have verified that the proposed multilinear MCS method prevails over the nonlinear MCS. In addition, P2G effectively benefits the operation of both electrical and gas networks.

引用

页码：1970 / 1979

页数：10

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