From Fault Recording to Disturbance Recording

Slides:



Advertisements
Similar presentations
Summary of Second Draft of the NERC Standard PRC Disturbance Monitoring and Reporting JSIS Meeting August 10, 2010 Salt Lake City, UT.
Advertisements

Project 1.3 Status Monitoring, Disturbance Detection, Diagnostics, and Protection for Intelligent Microgrids Dr Wilsun Xu C. Jiang,
Modeling Electrical Systems With EMTP-RV
Multi Functional Digital Fault Recorder
and Trend for Smart Grid
Frankfurt (Germany), 6-9 June 2011 Douglas Wilson Psymetrix Ltd, UK Douglas Wilson Psymetrix Ltd, UK D. Wilson – UK – Session 4 – Paper ID 0497 Connection.
Reliability Software1 Reliability Software Minimum requirements & Best practices Frank Macedo - FERC Technical Conference July 14, 2004.
Smart Grid Applications: Viewpoint of an Electrical Power Engineer Francisco de Leon October 2010.
Introduction to Phasor Measurements Units (PMUs)
IEC Substation Configuration Language and Its Impact on the Engineering of Distribution Substation Systems Notes Dr. Alexander Apostolov.
FRIENDS and WAR The mission of the Power Center for Utility Explorations is to explore all energy issues holistically and to develop innovative solutions.
CAISO Update JSIS Meeting March, Infrastructure 92 Connected PMUs 64 Substations 7 PDCs reporting (BPA, PG&E, SCE, SDG&E, APS, SRP and NVP) Redundant.
RiversidePublicUtilities.com Arts & Innovation RiversidePublicUtilities.com Challenges and Solutions for Large-Scale PV Integration on RPU’s Distribution.
Power Systems Consulting and Software 4 March 2004 BWEA Conference: UK Offshore Wind 2004 Integration of Offshore Wind Farms into the Local Distribution.
1 PCA2 On-load Protection Condition Analyser. 2 PCA2 online testing concept Concept introduction: PCA2 is a new system test approach intended to save.
SUBSTATION MODELING: PROTECTION AND AUTOMATION
Supervisory Systems.
Workflow Based Tools Simplifying All Job Functions.
Advanced Phasor Measurement Units for the Real-Time Monitoring
TECHNOLOGY DEMONSTRATOR OF 7-CHANNEL DIGITAL FLIGHT DATA RECORDER AS AVIONICS TEACHING AID USING STATIC MODEL AIRCRAFT Authors 1. Wg Cdr Nikhil Verma,
Network Architecture and Protocol Concepts. Network Architectures (1) The network provides one or more communication services to applications –A service.
Academic Experience with Wide Area Sensors by Virgilio Centeno Virginia Tech PSC, Distributed Generation, Advanced Metering and Communications March 9,
EPRI CIM for Dynamic Models Project Report Terry Saxton Xtensible Solutions May 13, 2009.
1 Some Issues about Big Data in Power Grid Gary Quan.
Zoran Gajić ABB AB Vasteras, Sweden
Monitoring of Active Distribution Networks in Steady State and Transient Conditions by means of accurate synchrophasors measurements Mario Paolone École.
Synchrophasor: Implementation,Testing & Operational Experience
Page 0 Eastern Interconnection Phasor Demonstration Enhanced Wide-Area Visibility In the Eastern Interconnection for Reliability Management Transmission.
Enhanced State Estimation by Advanced Substation Monitoring PSerc Project Review MeetingTexas A&M University November 7, 2001 College Station, TX PIs:
Prepared By :.  Introduction  Techniques Used  Case Study  Advantages  Application  Conclusion OUTLINE.
Accurate Fault Location Using Detailed Transmission Line Models NSF/EPRI Workshop M. Kezunovic Texas A&M University March 29, 2002.
1 Application of Synchrophasor Technology To CREZ System CREZ Technical Conference January 26, 2010 Navin Bhatt American Electric Power.
WELCOME TO SEMINAR ON SCADA WELCOME TO SEMINAR ON SCADA Presented by: ANIL KUMAR RAUT Adm No:33IE/2k.
CASE STUDY Disturbance event comparing PMU and SE voltage angle difference in ERCOT Prakash Shrestha Operations Engineer Advanced Network Application.
Communication Delays in Wide Area Measurement Systems (WAMS) Biju Naduvathuparambil, Matthew C. Valenti, and Ali Feliachi Lane Department of Comp. Sci.
©2009 Mladen Kezunovic. Improving Relay Performance By Off-line and On-line Evaluation Mladen Kezunovic Jinfeng Ren, Chengzong Pang Texas A&M University,
Doc.: IEEE /0121r1 Submission January 2010 Craig Rodine, Electric Power Research InstituteSlide 1 Some High-Level Smart Grid Requirements Date:
A Trust Based Distributed Kalman Filtering Approach for Mode Estimation in Power Systems Tao Jiang, Ion Matei and John S. Baras Institute for Systems Research.
Texas A&M University, Department of Aerospace Engineering AN EMBEDDED FUNCTION TOOL FOR MODELING AND SIMULATING ESTIMATION PROBLEMS IN AEROSPACE ENGINEERING.
November 16, 2012 Synchrophasor Meeting Dynamic Model Validation Project Jonathan Rose Engineer, Resource Integration Sidharth Rajagopalan Engineer, Dynamic.
ECE 476 Power System Analysis Lecture 22: System Protection, Transient Stability Prof. Tom Overbye Dept. of Electrical and Computer Engineering University.
Use of Synchronized Sampling in Fault Location ECEN Computer Relays Project #1 Presented by: Fahad Saleh Alismail UIN: Monday 03/03/2014.
Name Of The College & Dept
Lecture 24 Transient Stability Professor Tom Overbye Department of Electrical and Computer Engineering ECE 476 POWER SYSTEM ANALYSIS.
TIMING APPLICATIONS OF GPS High Energy Transmission with High Precision GPS Time Gaurav Sharma John Hannah Vivekanand Sivaraman.
Imagination at work. Paddy McNabb Senior Engineer January 2016 Grid Stability Applications Wide Area Monitoring System.
Smart Grid Big Data: Automating Analysis of Distribution Systems Steve Pascoe Manager Business Development E&O - NISC.
ARM and GPS Based Transformer monitoring system with area Identification Student Name USN NO Guide Name H.O.D Name Name Of The College & Dept.
1 PEBB-based Power Electronic Systems to Support MVDC Studies Herbert L. Ginn III, Mississippi State University.
SEMINAR PRESENATATION ON WIDEAREA BLACKOUT (AN ELECTRICAL DISASTER) BY:Madhusmita Mohanty Electrical Engineering 7TH Semester Regd No
1 Dr.Wang Yingtao Engineer Power System Department CEPRI,China Nov 2006 R&D OF REAL TIME DYNAMIC MONITORING SYSTEM IN CHIHA.
Discovery Across Texas: Technology Solutions for Wind Integration in ERCOT Using Synchrophasor Technology for Wind Integration and Event Monitoring in.
Announcements Design Project has firm due date of Dec 4
SIGNAL CONDITIONING Signal conditioning is stage of instrumentation system used for modifying the transduced signal into a usable format for the final.
What’s new at GPA?.
IG BASED WINDFARMS USING STATCOM
PSCAD models.
A Future Oriented Data Platform for the Electric Power Grids
APPLICATIONS OF GPS IN POWER ENGINEERING
Setting-less Protection: Laboratory Experiments and Field Trials
SMART GRID BASED FAULT IDENTIFICATION SYSTEM
ECEN 460 Power System Operation and Control
MICROSECOND TIME KEEPING TO IMPROVE POWER SYSTEM CONTROL & OPERATION
Sakis Meliopoulos. , George Cokkinides. , Hussain Albinali
ECEN 460 Power System Operation and Control
Autonomous Integrated Power System Operation & Control
Accurate Fault Location Using Modeling and Simulation
WISP Follow on Reporting.
M. Kezunovic (P.I.) S. S. Luo D. Ristanovic Texas A&M University
Multichannel Link Path Analysis
Presentation transcript:

From Fault Recording to Disturbance Recording Sakis Meliopoulos Georgia Power Distinguished Professor School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta, Georgia 30332

Outline Why FR  DR Requirements/data processing Historian for Disturbance Play Back Conclusions

Why FR  DR Following the 2003 blackout, numerous engineers worked for months to align and synthesize fault recorded data for the purpose of re-creating the disturbance and the evolution of the blackout There must be a BETTER WAY

FR  DR: How For Disturbance Recording and playback: Recording system requirements Storage schemes (what to store – data processing - model) Playback and system synthesizing

The SuperCalibrator Concept as a Data Compressor What to Store The SuperCalibrator Concept as a Data Compressor Fact: A plethora of data is available at the substation level The SuperCalibrator is conceptually very simple: Utilizes all available data (Relays, DFRs, PMUs, Meters, etc.). Utilizes a detailed substation model (three-phase, breaker-oriented model, instrumentation channel inclusive and data acquisition model inclusive). At least one GPS synchronized device (PMU, Relay with PMU, etc.) Results on UTC time enabling a truly decentralized State Estimator. Extracts the Real Time Model of the System form all available measurements mentioned above. Recently this approach has been extended to dynamic state estimation with build in fault locating: PMU data of phasors, frequency and rate of frequency change are used to provide the dynamic state of the system in a reliable and robust way

Distributed Dynamic State Estimation Implementation System is Represented with a Set of Differential Equations (DE) The Dynamic State Estimator Fits the Streaming Data to the Dynamic Model (DE) of the System

SuperCalibrator Measurement Set Conversion of Non-Synchronized Measurements into Phasors α is a synchronizing unknown variable cos(α) and sin(α) are unknown variables in the state estimation algorithm. There is one α variable for each non-synchronized relay

Dynamic State Estimation – Block diagram Dynamic State Estimation Problem is Converted to Static by Integration Least Squares Solution Bad Data Detection Bad Data Identification and Removal

Dynamic State Estimation: Numerical Experiments Test System: 3 generating substations and an infinite bus connected through overhead transmission lines Substation 1: Substation of interest where DSE is performed Simulated 3 phase fault near Substation 3 DSE uses PMU and other relay measurements in the first substation DSE algorithm estimates local and neighboring substation states

Numerical Experiments: Post Fault DSE Performance Simulated and Estimated Voltage Magnitude at Substation 3 (neighboring substation) for post fault condition Simulated and Estimated Voltage Phase angle at Substation 3 (neighboring substation) for post fault condition

Distributed Dynamic State Estimation Implementation 1 Physical Arrangement Data Flow Data/Measurements from all PMUs, Relays, IEDs, Meters, FDRs, etc are collected via a Local Area Network in a data concentrator. The data is used in a dynamic state estimator which provides the validated and high fidelity dynamic model of the system. Bad data detection and rejection is achieved because of high level of redundant measurements at this level.

Distributed Dynamic State Estimation: Implementation 2

The USVI WAPA System Provides an Excellent Testbed for the Distributed Dynamic State Estimator The USVI WAPA system is a small 270 MW, Five Substations, 35 kV/13 kV System. 17 relay/PMUs. Faults create large swings of the generators as manifested by the frequency oscillations in the Feb 20, 2008 event. In addition events are more frequent in the USVI system than mainland systems.

Distributed Dynamic State Estimation During a Fault The Dynamic State Estimator Operates at 10 times per second What happens when a fault occurs? Introduce the Fault Location (F) as another State to be Estimated

Historian for Disturbance Play-Back Substation Storage Scheme Full Model + Model Changes + Data System FULL MODEL stored once a day in WinIGS format – time of day can be arbitrarily selected, for example at 2 am. (example storage follows) Report system changes by exception – UTC time (example storage follows) Storage of state data: at each occurrence of the state estimator, the estimated states are stored in COMTRADE-like format. (example storage follows)

Substation Storage Scheme FULL MODEL + Model Changes + Data System FULL MODEL stored once a day in WinIGS format. Time of day can be arbitrarily selected, for example at 2 am. Example storage: MODEL 3 DEV_TITLE Long Bay Substation NUMERIC_ID 77 NET_LAYER 3 GEO_COORDINATES 18.339260000 -64.920927000 COORDINATES -137 2 -144 -1 -137 4 -138 -1 -145 0 -145 7 -145 4 -141 6 COORDINATES -141 -2 -142 2 INTERFACES FDR-9B 3-0A0B2 FDR-8B FDR10B FDR-YH1 3-0B0D 3-0A0B1 FDR-7B INTERFACES FDR-YH2 PARAMETERS LONGBAY VIWAPA VIWAPA END_MODEL MODEL 123 DEV_TITLE Feeder #11, Long Bay to East End Substation - Section 1 NUMERIC_ID 246 COORDINATES -145 7 -145 10 -141 13 -132 13 -126 10 -120 6 -114 4 -109 3 COORDINATES -107 1 -105 -2 CIRCUITS 1 INTERFACES 3-0B0D_N 3-0B0D_A 3-0B0D_N 3-0B0D_B 3-0B0D_N 3-0B0D_C 3-0B0D_N UG350_N INTERFACES UG350_A UG350_N UG350_B UG350_N UG350_C UG350_N PARAMETERS 5 7 14.40 3868.0 0.0 0.0 0.0 CABLE PARAMETERS VI34KV750KCM-CU-TS -0.10802 -3.09671 CKT1 CABLE VI34KV750KCM-CU-TS -0.00119 -2.92351 PARAMETERS CKT1 CABLE VI34KV750KCM-CU-TS 0.11108 -3.09234 CKT1 CABLE CONDUIT8 PARAMETERS -0.00656 -2.93099 CKT1 COPPER 4/0 0.00667 -3.18108 CKT1 PARAMETERS 1 CKT1 5499.0 25.0000 34.5000 ……… Substation Model Transmission Line Model

Substation Storage Scheme Full Model + MODEL CHANGES + Data Report system changes by exception – UTC time MODEL_CHANGE TIME 1267771497 450123 TYPE XFMR_TAP DEVICE_ID 1265 VALUE R12 END_MODEL_CHANGE TIME 1267771791 609355 TYPE BREAKER_OPERATION DEVICE_ID 3409 VALUE CLOSE . . . SOC + Fractional Second March 05, 01:44:57.450123 File Format – Each line begins with a keyword optionally followed by one or more arguments.

Substation Storage Scheme Full Model + MODEL CHANGES + Data Storage of state data: at each occurrence of the state estimator, the estimated states are stored in COMTRADE-like format. The following File Types Are Used: Configuration Files: Description of State Names Types and Locations State Data Files: State Values plus Model Change Information Triggered Event Files: Waveform data recorded for each triggering event in COMTRADE format.

Substation Storage Scheme Full Model + MODEL CHANGES + Data Storage of state data: at each occurrence of the state estimator, the estimated states are stored in COMTRADE-like format. Configuration File – One for Each Day File Naming Standard: CompanyName_SubstationName_SOC.scf File Content: <Title or Brief Description> <SOC> <uSec> <Number of States> <State Name>, <State Type>, <Bus Name>, <Phase>, <Power Device ID> . . . Where: SOC: is the Second of Century Time Code defined as the number of seconds elapsed since midnight of January 1, 1970 (in UTC time) uSec is a fractional second value in microseconds. Above structure repeated each time the set of states changes

Substation Storage Scheme Full Model + MODEL CHANGES + Data Storage of state data: at each occurrence of the state estimator, the estimated states are stored in COMTRADE-like format. State Data File – One for Each Day File Naming Standard: CompanyName_SubstationName_SOC.sdf File Content: STATE_VECTOR <SOC> <uSec> <State Value> <State Value> <State Value>. . . . . . MODEL_CHANGE TIME 1267771791 609355 TYPE BREAKER_OPERATION DEVICE_ID 3409 VALUE CLOSE END_MODEL_CHANGE

Substation Storage Scheme Full Model + MODEL CHANGES + Data Storage of state data: at each occurrence of the state estimator, the estimated states are stored in COMTRADE-like format. Triggered Event Files – One for Each Event File Naming Standard: CompanyName_SubstationName_SOC.cfg CompanyName_SubstationName_SOC.dat File Content: Standard COMTRADE Waveform File Format

Re-Construction of System State System Operation “Play Back” over a user specified time interval (t1 to t2) Reconstructed state is presented via graphical visualization Techniques, ( 3-D rendering, animation etc) with multiple user options.

Wide Area Monitoring and Disturbance Play-Back The SuperCalibrator at each substation stores the streaming data with (a) time tags, (b) network status, and (c) substation real time model at the time. This data can be “played back” for any user specified past time interval. Various visualizations allow the user to observe specific performance parameters of the system. Examples are: (a) voltage profile evolution, (b) transient swings of the system, (c) electric current flow, etc.

Conclusions The Dynamic State Estimator fits PMU data to the Dynamic Model of the System: Enables a powerful method to study system dynamics and predict performance. Fault Location Estimation has been integrated into the Dynamic State Estimator. Substation storage scheme (historian) that enables automated Disturbance Play Back. The implemented historian of (full model) + (model changes) + (data) has been presented. Comments and suggestions are welcome. Need for standards for disturbance+model storage and playback that include coincident system models.