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美国几大牛完成的最新项目报告

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发表于 2009-1-26 06:05:25 | 显示全部楼层 |阅读模式
论文文献
标题: Detection, Prevention and Mitigation of Cascading Events
作者:
所属专业方向: 电力系统
摘要: Prevention and Mitigation of Cascading Events
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venkatasubramanian_pserc_s-29_project_report_2008.rar (4.34 MB, 下载次数: 81)

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发表于 2009-1-26 22:30:34 | 显示全部楼层
怎么没有介绍一下具体的内容啊
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    发表于 2009-1-27 04:48:57 | 显示全部楼层

    详细一些

    请问楼主是否可以详细的介绍一下报告的主要内容,谢谢
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    发表于 2009-1-27 20:28:53 | 显示全部楼层
    应该不错吧,下来看看,比较前沿了
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    发表于 2009-1-27 21:25:07 | 显示全部楼层
    请楼主补充一下内容。:)
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    发表于 2009-1-28 11:04:14 | 显示全部楼层
    Executive Summary
    3 n& J4 X5 [# `* |% I2 [$ V9 P6 T4 `4 VThe risk of cascading outages in power systems manifests itself in a number of ways.7 b& W0 ?/ Z; N1 `
    With the advent of structured competitive power markets, and with the lack of needed# ]( {% w' z9 N/ J( D
    investment in the transmission grid, electric power systems are increasingly being
    , s% V' E, i) I/ }2 T: j4 |operated close to their limits. Potential terrorist threats raise concerns about power system
    ) @& ]: h" B( r. _" u. n9 Ebeing placed in unforeseen operating conditions. Recent blackouts in North America and) U; N% R- Q7 C! X+ K' B5 S  {2 B
    in Europe show that the risk of cascading events is real with the cost of the 2003 North
    : Y6 a# C3 ^9 D% l, i1 EAmerican blackout estimated to be around $10 Billion. As the power system becomes# S* b& ~) m; W7 B7 e" \7 _3 Q
    more stressed there are a host of reasons (such as weak connections, unexpected events,
    6 C" j% E* I- M- W* ~" ^hidden failures in protection system, and human errors) for the loss of stability eventually" S! s& t$ y9 E' e5 a0 ~) R/ z' F
    leading to catastrophic failures.
    ! g8 r7 [  U( E2 v' L* o' }: S6 u3 J9 TWhen a power system is subjected to large disturbances control actions need to be taken
    & j; I4 Z% M# P: k% @$ s+ Qto steer the system away from severe consequences and to limit the extent of the3 k* p" w+ i; W: r, K
    disturbance. This is particular true if system is in an operating condition that makes it
    % h, x6 t5 Z; G, v! H! t! Nunusually vulnerable to catastrophic failure. In a previous PSERC project (S-19 that5 i9 K% q- B1 G
    ended in 2005), we developed novel algorithms for each of the following steps:
    1 ]  T9 P2 Y: t- ~, P& K6 Z1. Detection of major disturbances and protective relay operations leading to! z( ?& [% S! o
    cascading events. The detection algorithms improved capabilities of real-time! H  T4 z& o5 d0 y
    fault detection and analysis to classify the impact of a fault towards initiating
    # K8 q' s0 n; H! @4 zcascading outages.
    3 v4 `& y$ [5 t: J2. Wide-area measurement based detection and remedial control actions. The9 ]' U% H0 T. J8 C0 A6 a. r7 J' p
    wide-area mitigation algorithms include methods for reliably extracting modal  o+ O  m$ z8 K+ l& n5 p
    information on critical wide-area modes through real-time wide-area Phasor8 b4 F- ~5 v1 b7 S# a3 O
    Measurement Unit (PMU) measurements. They also provide specific control/ z9 u7 L& s5 q/ c. f* ]
    actions to damp out the oscillations when problems are detected.
    0 h1 @7 r; l' `3 n! M. O9 m. P9 x3. Adaptive islanding with selective under-frequency load shedding. The
    0 h! c7 u) F% V" z" uadaptive islanding algorithms suggest methods for controlled islanding of the
    7 B' M9 b. t6 |) w- s: T$ N! Lsystem should mitigation strategies fail.1 ~; ~0 }" P: ?- k
    The algorithms were shown to be effective using realistic computer models of test power: }; L3 b8 K( A1 k% e% l/ A
    systems. In this project, we focused on prototype implementations of those algorithms at
    2 K+ }& N% A1 ~7 {+ T' p3 Ycollaborating PSERC member utilities.
    3 z! k( K, Z) f  f: QVolume I: Detection of major disturbances and protective relay operations leading  j7 j4 h$ A( U- n( t% I5 R/ ^
    to cascading events (Lead: Mladen Kezunovic, Texas A&M University).# T+ S2 {) r4 ?5 J0 y; q0 F
    This research volume proposes a system-wide monitoring and control solution intended5 K# J5 l8 j- a
    for use at control centers. The solution includes steady state and dynamic analysis tools.
    / D: ~' w( o- x! D6 g7 ?The tools may be used to check system stability, find the vulnerable elements, and send
    ' L. h: @0 A6 ycommands to the local tools for initiating detailed monitoring.5 Q8 `& I, @* h; i' p" J6 Y5 l
    The local monitoring and control tools are intended for installation at substations. They
    , w. C! A  A$ @8 ]7 ]! u$ N2 Y, whave the capability for advanced fault analysis and relay monitoring using neural network6 G6 ]* D' N% c7 c8 v/ Y' l
    ii
    ( r4 G% A% c3 t; ~* [for fault detection and classification, synchronized sampling for fault location, and event
    7 L5 g6 U# m  Y1 h+ a3 t) G) Ktree analysis for relay operation verification. The local monitoring and control tools can* M# A) a5 S' i; v$ @' M
    characterize a disturbance and make a correction if there is an unintended relay operation.
    4 ^$ k0 F% M9 ~# x; t( I. VThis information can be sent to a system monitoring and control tool for better security% l: y" g* t8 y) H/ d
    control.
    % i3 \* X/ [# V- {Implementation of the proposed algorithms requires assessment of data handling
    6 U) E% g  g+ F: x, V0 H# Hrequirements. Data handling includes obtaining, converting and storing data.
    % v. ~  B/ X& X1 G0 t  Q- @Consideration must also be given to integrating data from various sources: Supervisory
    , l3 X* x" j, r) J( F  s% j9 FControl and Data Acquisition (SCADA) systems, Intelligent Electronic Devices, and
    9 I$ K1 m& Z' e0 s7 i0 V* lother add-on high speed data acquisition systems. Data from system simulation packages( t) N% ~0 p' j* o/ H. a4 v3 o+ e
    is also needed to perform steady state analysis.
    2 D" Q- t) W5 i. @- y/ o0 F/ R# fSteady state and dynamic analysis cases were studied using a model of the entire Entergy
    & I6 I- \# W( u$ w9 }system. Vulnerability Index and Margin Index for each bus, generator, and transmission' V1 k- q. V* \+ v
    line were calculated to identify the vulnerability and security margin information for each- ^" N9 P: ~9 U9 W
    individual power system element. A 500kV Extra High Voltage transmission line was- `1 u5 A( \( x; \& d+ e( r" p( x
    modeled for evaluating local monitoring and analysis tools. The results indicate that& q: R7 S) {$ {4 G% c
    when using adequate training sets and time synchronized data, the new algorithms are( x  v/ J' c3 E! ~5 \4 o- W! C
    quite accurate and provide assessment of system conditions during cascades that are not
    ; H* p, k7 d( E5 p! ofeasible with any of the existing techniques.# O$ p' [% o9 v+ f( B9 F
    Volume II: Wide-area measurement based detection and remedial control actions
    " H- ^1 Y3 d1 y* `+ x(Lead: Mani V. Venkatasubramanian, Washington State University)% K. [. N7 a4 g4 K% C) {
    If persistent over an extended period of time (e.g., 30 minutes), poorly damped
    5 j4 v8 R7 o/ I- P7 }oscillations in a power system can lead to permanent damage of expensive power system
    * q& }* Q5 d) D; n4 wequipment and pose power quality issues. Negatively-damped oscillations can be even
    ! H. f* j) _. H2 \, D# {% }more problematic by resulting in sudden tripping of generators and/or widespread system* k7 p! u, R0 i7 Y; ?
    blackout such as occurred in the August 10, 1996 western power system blackout.- ~4 K/ \6 G8 }% E  |$ i8 [7 I$ ~
    In this research project, we designed, developed and implemented an Oscillation
    7 @. x& U0 \- V) HMonitoring System (OMS) that uses wide-area PMU measurements for automatically
    : Z: {. H- X# |  k. h" {2 ^monitoring for poorly damped and/or negatively-damped oscillatory modes. OMS
    , z- K% j- W$ s! S1 v; dincludes two complementary engines that provide real-time modal analysis: 1) an' u; c5 }3 w  e2 ]
    automatic Prony-type analysis of power system responses following routine events such5 F  N7 d0 o4 T9 b
    as line tripping and generator outages; and 2) an engine for continuous estimation of. i" f6 I/ d$ \. s4 b# U: v
    poorly damped mode frequencies and their damping ratios from routine ambient noise( p* }- I$ T+ Q" y" T! |5 p! r4 {/ @
    PMU measurements. The algorithms were structured as a rule-based expert system for* d' Y& r+ N, [2 c
    simplifying the Prony analysis of nonlinear PMU responses in real-time while avoiding8 Y, G- T' @: a" P1 P. k& D
    false alarms and incorrect estimates. The OMS can issue operator alerts as well as initiate
    + t7 {% S' k+ striggers to start appropriate control actions to improve damping of problematic oscillatory
    ; u* F6 \; \1 u: u# Q7 l6 Smodes. A wide-area damping control strategy that uses Static VAR Compensators was
    2 Z5 B" {0 [% b* v; H. q% jdeveloped in the previous PSERC project. Another damping control strategy was
    # o) F2 a  v+ j% ?4 {4 Gdeveloped in this project. It uses HVDC modulation to improve the damping of inter-area
    5 l& E" p# S; n" q& }9 |5 aoscillatory modes./ \3 S- [$ @6 J9 r  l& F
    iii5 N( Q4 F$ l' K* {. U% |
    A prototype version of OMS has been integrated into real-time monitoring capability of
    3 m( g" d# r+ l$ n! jthe Phasor Data Concentrator at TVA. At present, it monitors PMU data from within/ }! N3 l4 `$ N8 l, r5 Z, W
    TVA for estimating the frequency, damping, and mode shape of oscillatory modes. We. ]9 N4 F( w% W* R' x3 {
    are also collaborating with the Electric Power Group and Bonneville Power& E6 g$ m2 |9 d; g! R# U
    Administration (BPA) to implement a version of the Prony-type first engine of OMS at
    7 b% S. t, _/ @' M- @0 _) Ytwo PSERC companies: BPA and the California Independent System Operator. An offline
    6 h- m9 ~, i3 lversion of three Prony type algorithms from this project has been integrated into an7 ^, i. A# J8 |* V+ [
    event analysis software package being developed by Electric Power Group Inc., and the- j& b. p- Y4 L: T, M7 s9 D
    package aimed at off-line modal analysis of PMU measurements is available to PSERC& T; w5 Q, G+ o8 _
    members.
    / B7 Y1 H7 V, |4 w3 ^* d9 GVolume III: Adaptive islanding with selective under-frequency load shedding (Lead:
    % ^8 Y, f$ ]; n8 E" r  [- AVijay Vittal, Arizona State University)# M1 w: {1 g* o
    The main objective of this portion of the research project was to develop a fast and0 Z: Y4 l6 h# s0 z( F6 \
    accurate assessment tool to determine the timing of conducting controlled islanding3 c( d% ?7 c# _5 J
    scheme in real time for preventing cascading events that could lead to a large scale
    # ~. l6 n7 P0 l. `$ w$ b: nblackout. This work demonstrated an event-initiated controlled islanding scheme using* q' G# t) ?) E0 _
    phasor measurement units and decision trees to stabilize power systems following severe3 h- m" X: I' Z3 ]# U, d
    contingencies. The demonstration was performed on a test system provided by Entergy.# t' ~' X  X  U0 J
    A control scheme for must be designed very carefully since the costs can be quite high" @" j! a3 `  ?9 [" L& e3 ^
    for unneeded controlled separation operation and for failure to operate when needed.
    + z8 C) g  e5 u( YNormally, there are two major issues associated with the design of a controlled separation' Q, U9 M2 N4 N- I) J5 T% p  Z" M
    scheme:
    1 v. A6 J+ |. P6 A: m( x% ]: H9 mi. Where to island? This issue mainly focuses on searching for the optimal cut set/ {1 o: q% V6 V0 t2 T( a9 u  E) ~
    in the system to satisfy certain constraints, such as (a) coherent generators should) |+ O  c: ?+ y6 X2 d
    stay in one island and (b) the load/generation imbalance of each island should be
    ' Y% c* t9 X' f5 L% W/ g, O* g. Jminimized. Much of the research effort of a previous PSERC project (S-19)3 s: j" y' j8 |7 `% g
    focused on addressing this issue. Due to the large computational burden
    , G" n( m1 k$ q5 T9 Rassociated with this aspect, the controlled separation cut set is usually obtained  F4 z+ k* W; I" ?* y
    offline.
    ! o" {+ J$ ]9 h; Y* U1 ]+ i1 z+ Q4 Dii. When to island? The second issue is to accurately determine the timing of
      f6 f0 Q  P% ?7 ~controlled separation. This is the main focus of this research. The objective was to" y5 O  K1 q6 I, N% \4 e$ u3 p7 W
    develop an online transient stability prediction scheme to determine whether
    - _, W* }6 h* {, S, U9 h* icertain contingencies can initiate severely unstable swings and cause cascading
    3 \! ~: |( S) ievents. If so, controlled separation should be initiated to prevent a large scale. Z8 _( d; t7 Y: D6 a8 W* G0 B& f
    blackout.
    ( ^* j. d6 L7 b) n/ _& X3 e% bTaking advantage of synchronized phasor measurements, we developed a decision tree2 @8 v8 L' G' u: p9 ~
    based transient stability assessment scheme for online application. The synchronized. \  k  m* ~8 {" u& |1 g+ H
    signals and high sampling frequency give PMUs the capability of observing different
    / ?1 V9 i* T2 ~4 G8 ]; [states across the whole system in a common time frame with great accuracy. System
    " C9 V7 U8 v$ I. e. \transient behaviors can also be accurately captured compared to the traditional SCADA
    # H: l9 y9 G, xsystem. The decision tree technique is an effective data mining tool to solve the
    . [1 s6 d6 W' m, j$ Q7 bclassification problems in high data dimensions. It can be used to uncover critical system& l) I, N& ?* Y0 ^, H% N+ ^
    attributes that contribute to an objective such as transient stability or voltage security. The
    1 W9 s( Q$ s- P9 g) dsplitting rules and the corresponding thresholds in the decision trees help to build a: O% R7 G# l3 h" I+ f2 D5 Q
    nomogram in terms of these critical system parameters and guide system operators5 E' G4 `) {- e  i! _! @2 {; n
    effectively.+ A: N& J8 B0 ?7 Z
    The project results indicate that out of step swings can be accurately predicted only a few# w4 n& X. O. J- {9 \3 w
    cycles after the initial disturbance using properly trained decision trees. This is much3 q( Y' z$ o8 Q3 `* S8 A. @) r  {; h
    faster than the traditional analysis method. The decision trees also identify transient
    1 t; T" |0 M* p9 _5 k3 s# L7 ?4 ostability indicators that are good candidates for new PMU locations. With an effective8 M* S4 [9 X' U0 x
    controlled islanding strategy, the system can be stabilized faster with less amount of load. N+ R' s; L+ Q  J: F! f
    to be shed than the uncontrolled separation case.
    2 n7 F) U- d) JWe developed a software platform that implements the entire approach based on data1 H, m5 x  Z; W# x! f! G- D" K. Z  `
    provides the DSATools suite of software from Powertech Labs. The approach also uses
    7 j' s2 H. Q8 T/ A! {commercially-available software called CART developed by Salford Systems for) t8 |9 m: d% S" l" j* ]( W
    decision tree training and testing.
    3 T  @0 C$ E$ i* X9 s9 q" FNext Steps to Advancing this Research
    & q( j0 n4 u5 G7 F: OAt Texas A&M University, future steps to implementing algorithms for the detecting,
    + j8 K  h6 F8 I; Tclassifying, and mitigating cascading events require selection of a utility test set-up.; D# l& R" M8 T6 h+ m; _/ S7 V" M+ F
    Currently discussions with several utilities under auspices of DOE-CERTS, EPRI, and8 K2 O: R# c# l4 _2 v9 e7 u
    ERCOT are under way to determine whether such arrangements for the final testing work
    / l" ]2 B. k7 W; Zcan be made.& C9 m1 _. K5 V3 _5 j
    The Washington State University team will continue to work with PSERC utilities and
    4 X* [1 `2 l  d; k. Wsoftware vendors for field implementations as well as testing, tuning and enhancement of
    ) C- W% R: j! N/ a0 d. nOMS capabilities. Future research needs to focus on determining correct operator actions
    ' b  e* Q( O: G8 v4 M0 Was well as automatic control actions to improve the damping of problematic oscillatory
    * q$ z6 k& W/ V& r/ \modes when such problems are detected by OMS.
    0 l6 Q5 W- V" n' d* eAt Arizona State University, future steps to implementing the controlled islanding work& S$ E. D" B- X# P
    would require testing and implementation at an electric utility. Some of this work is being
    - u) H4 B9 z; x" v! d6 `0 \! adone in a CERTS project and discussions are under way to consider implementation at a* S( X. `+ V7 W
    specific company.
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    发表于 2009-1-28 14:14:02 | 显示全部楼层
    具体是哪几个大牛出的报告啊?
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     楼主| 发表于 2009-1-29 12:05:11 | 显示全部楼层
    Mani V. Venkatasubramanian, Project Leader,8 O7 q, p+ J/ l: ^2 c  Z
    Washington State University1 k- E2 X! T- h7 Z2 ^5 q) |" s. ]' |
    Mladen Kezunovic, Texas A&M University* K9 O8 ?( |0 Z' }5 R+ Y4 W
    Vijay Vittal, Arizona State University
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    发表于 2009-1-29 17:24:57 | 显示全部楼层
    Vijay Vittal还写了HVDC的书。
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    [LV.1]初来乍到

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    发表于 2009-1-29 21:38:33 | 显示全部楼层
    提示: 作者被禁止或删除 内容自动屏蔽
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