Impact of Data Quality on Real-Time Locational Marginal Price

被引：85

作者：

Jia, Liyan ^{[1
]}

Kim, Jinsub ^{[1
]}

Thomas, Robert J. ^{[1
]}

Tong, Lang ^{[1
]}

机构：

[1] Cornell Univ, Sch Elect & Comp Engn, Ithaca, NY 14853 USA

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 2014年 / 29卷 / 02期

基金：

美国国家科学基金会;

关键词：

Bad data detection; cyber security of smart grid; locational marginal price (LMP); power system state estimation; real-time market; STATE ESTIMATION; TOPOLOGY ERRORS; ATTACKS;

D O I：

10.1109/TPWRS.2013.2286992

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 problem of characterizing impacts of data quality on real-time locational marginal price (LMP) is considered. Because the real-time LMP is computed from the estimated network topology and system state, bad data that cause errors in topology processing and state estimation affect real-time LMP. It is shown that the power system state space is partitioned into price regions of convex polytopes. Under different bad data models, the worst case impacts of bad data on real-time LMP are analyzed. Numerical simulations are used to illustrate worst case performance for IEEE-14 and IEEE-118 networks.

引用

页码：627 / 636

页数：10

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