東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Dynamic state estimation assisted po...

Cui, Yinan.

Linked to FindBook

Google Book

Amazon

博客來

Dynamic state estimation assisted power system monitoring and protection.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Dynamic state estimation assisted power system monitoring and protection./
Author:	Cui, Yinan.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
Description:	122 p.
Notes:	Source: Dissertation Abstracts International, Volume: 78-10(E), Section: B.
Contained By:	Dissertation Abstracts International78-10B(E).
Subject:	Electrical engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10243952
ISBN:	9781369787641

Dynamic state estimation assisted power system monitoring and protection.
Cui, Yinan.

Dynamic state estimation assisted power system monitoring and protection. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 122 p.

Source: Dissertation Abstracts International, Volume: 78-10(E), Section: B.

Thesis (Ph.D.)--North Dakota State University, 2017.

The advent of phasor measurement units (PMUs) has unlocked several novel methods to monitor, control, and protect bulk electric power systems. This thesis introduces the concept of "Dynamic State Estimation" (DSE), aided by PMUs, for wide-area monitoring and protection of power systems. Unlike traditional State Estimation where algebraic variables are estimated from system measurements, DSE refers to a process to estimate the dynamic states associated with synchronous generators. This thesis first establishes the viability of using particle filtering as a technique to perform DSE in power systems. The utility of DSE for protection and wide-area monitoring are then shown as potential novel applications. The work is presented as a collection of several journal and conference papers. In the first paper, we present a particle filtering approach to dynamically estimate the states of a synchronous generator in a multi-machine setting considering the excitation and prime mover control systems. The second paper proposes an improved out-of-step detection method for generators by means of angular difference. The generator's rotor angle is estimated with a particle filter-based dynamic state estimator and the angular separation is then calculated by combining the raw local phasor measurements with this estimate. The third paper introduces a particle filter-based dual estimation method for tracking the dynamic states of a synchronous generator. It considers the situation where the field voltage measurements are not readily available. The particle filter is modified to treat the field voltage as an unknown input which is sequentially estimated along with the other dynamic states. The fourth paper proposes a novel framework for event detection based on energy functions. The key idea is that any event in the system will leave a signature in WAMS data-sets. It is shown that signatures for four broad classes of disturbance events are buried in the components that constitute the energy function for the system. This establishes a direct correspondence (or mapping) between an event and certain component(s) of the energy function. The last paper considers the dynamic latency effect when the measurements and estimated dynamics are transmitted from remote ends to a centralized location through the networks.

ISBN: 9781369787641Subjects--Topical Terms:

649834
Electrical engineering.

Dynamic state estimation assisted power system monitoring and protection.
LDR:03278nmm a2200301 4500 001 2154156
005 20180330130621.5
008 190424s2017 ||||||||||||||||| ||eng d
020 $a 9781369787641
035 $a (MiAaPQ)AAI10243952
035 $a (MiAaPQ)ndsu:11587
035 $a AAI10243952
040 $a MiAaPQ $c MiAaPQ
100 1 $a Cui, Yinan. $3 3217765
245 1 0 $a Dynamic state estimation assisted power system monitoring and protection.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2017
300 $a 122 p.
500 $a Source: Dissertation Abstracts International, Volume: 78-10(E), Section: B.
500 $a Adviser: Rajesh G. Kavasseri.
502 $a Thesis (Ph.D.)--North Dakota State University, 2017.
520 $a The advent of phasor measurement units (PMUs) has unlocked several novel methods to monitor, control, and protect bulk electric power systems. This thesis introduces the concept of "Dynamic State Estimation" (DSE), aided by PMUs, for wide-area monitoring and protection of power systems. Unlike traditional State Estimation where algebraic variables are estimated from system measurements, DSE refers to a process to estimate the dynamic states associated with synchronous generators. This thesis first establishes the viability of using particle filtering as a technique to perform DSE in power systems. The utility of DSE for protection and wide-area monitoring are then shown as potential novel applications. The work is presented as a collection of several journal and conference papers. In the first paper, we present a particle filtering approach to dynamically estimate the states of a synchronous generator in a multi-machine setting considering the excitation and prime mover control systems. The second paper proposes an improved out-of-step detection method for generators by means of angular difference. The generator's rotor angle is estimated with a particle filter-based dynamic state estimator and the angular separation is then calculated by combining the raw local phasor measurements with this estimate. The third paper introduces a particle filter-based dual estimation method for tracking the dynamic states of a synchronous generator. It considers the situation where the field voltage measurements are not readily available. The particle filter is modified to treat the field voltage as an unknown input which is sequentially estimated along with the other dynamic states. The fourth paper proposes a novel framework for event detection based on energy functions. The key idea is that any event in the system will leave a signature in WAMS data-sets. It is shown that signatures for four broad classes of disturbance events are buried in the components that constitute the energy function for the system. This establishes a direct correspondence (or mapping) between an event and certain component(s) of the energy function. The last paper considers the dynamic latency effect when the measurements and estimated dynamics are transmitted from remote ends to a centralized location through the networks.
590 $a School code: 0157.
650 4 $a Electrical engineering. $3 649834
650 4 $a Energy. $3 876794
690 $a 0544
690 $a 0791
710 2 $a North Dakota State University. $b Electrical and Computer Engineering. $3 2095311
773 0 $t Dissertation Abstracts International $g 78-10B(E).
790 $a 0157
791 $a Ph.D.
792 $a 2017
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10243952