on-line voltage instability risk identification based on

March 07, 2008G.N.Taranto 1/23

CRIS International Workshop on Critical Infrastructures – WAMS

On-line Voltage Instability RiskIdentification Based on Phasor

Measurements

Glauco N. Taranto

Rio de Janeiro, RJ

COPPE/UFRJPrograma de Engenharia Elétrica



Acknowledgements

Dr. Sandro Corsi (Centro Elettrotecnico Sperimentale Italiano)

Acknowledgements



Presentation Outline

Introduction

PMU

Voltage Stability

Background for the Method Utilized

Proposed Algorithm for Identification

Results

Italian System

Brazilian System (Preliminary Results)

Concluding Remarks

Presentation Outline



Introdução

PMU

First experiments back to the seventies

The pioneers: Profs. Phadke and Thorp

In Brazil: MedFasee Project (2003)

Technology for synchronization

Loran-C (in the past – 100 kHz)

GPS (presently – 2 MHz)

Applications

Monitoring (low sampling rate)

Protection and Control (high sampling rate)

Introduction



Localization of PMUs in TVA (USA)Introduction



Voltage Stability

Short term

From miliseconds to a few seconds

Large perturbation

Induction motor starting, HVDC

Long term

From seconds to many minutes

OLTC, OEL

IntroductionIntroduction

Work Focus



Background

Based on:

Measurements of voltage and current phasors

Thevenin equivalent

Impedance matching

Background



Background (Thevenin)

LThThL IZEVrrr

−=

ThL ZZ =

1 equation

2 unknowns

Maximal power

transfer

Background



Installation Layout

Source: Sakis Meliopoulos, IREP 2007

Background



VIP – Voltage Instability Prediction

Source: K. Vu and D. Novosel, “Voltage Instability Predictor (VIP) - Method and

System for Performing Adaptive Control to Improve Voltage Stability in Power

Systems,” US Patent No. 6,219,591, April 2001.

Finding: relying only on voltage magnitudes

to detect voltage instability is neither helpful

nor reliable!

Background



Fundamentals

⎟⎠

⎞⎜⎝

⎛= −

Th

L

EV θβ coscos 1

0≈ThRassumingEth is

unknownMethods already proposed:

1) LMS

2) Tellegen´s Principle

Fundamentals



Conceptual Analysis

Known Variables Estimated Variables

ZL(Ω) IL(A) VL(V) ETh(V) ZTh(Ω) ETh(V) ZTh(Ω)

1 9 2 18 21 1,5 19 0,5

2 8 2,22 17,76 21 1,46 19 0,56

Step

20 V (?)

1 Ω(?)

LVIL ZL

Hint!

Eth = 20 V

Zth = 1 Ω

Fundamentals



Proposed Algorithm

Step 1 – Estimate the initial value of Etho

Step 2 – Compute Xtho

Step 3 – Compute Eth(i) according to the logics of

the previous numerical example

Step 4 – Compute Xth(i) given Eth

(i)

Step 5 – Increment (i) and return to Step 3.

Proposed Algorithm



Results

The proposed algorithm was applied to the entire Italian System from

real data

System Characteristics:

2549 buses (380 kV and 220 kV networks)

2258 transmission lines and transformers

325 generators

50 GW of load

Dynamic models for OLTCs, OELs, voltage regulators and speed governors

Application to load and “transit” buses

Sampling rate – 20ms (1 phasor/cycle in 50Hz)

Results



380 kV Network

Milan

Florence

Results



Brugherio 380kV BusResults



Baggio 380kV BusResults



Sensitivity to the Sampling RateResults



Tests in the Rio Area

Tests are still preliminaryMade possible via Anatem from CEPELCase and models obtained from ONS webpage (February/2007)Load ramp increaseSummary submitted to SEPOPE 2008

Results



Preliminay Tests in the Rio Area

I

I

V

I

Results



Cachoeira Paulista 500kVZ_Thevenin x Z_carga

Results



Concluding Remarks

The phasor measurements can efficiently be utilized in voltage

instability prevention.

High sampling rates are necessary.

Prediction of voltage instability in a region can be made without

extensive use of the communications resources.

It is possible to proposed more sophisticated control logics relying on

data synchronization via GPS.

Comprehensive results from the Italian System and preliminary ones

from the Brazilian System encourage further research on this topic.

Concluding Remarks


CRIS International Workshop on Critical Infrastructures – WAMS Rio de Janeiro, RJ

THANKS !e-mail: [email protected]

on-line voltage instability risk identification based on

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