Power System Stability Impact Assessment using Time-Series
from Phasor-Time-Domain Simulations
Dr. Rafael Segundo
KTH SmarTS Lab (rafael.segundo@kth.se)
Prof. Luigi Vanfretti
KTH SmarTS Lab (luigiv@kth.se), Statnett SF (luigi.vanfretti@statnett.no)
REAL-SMART Poster Session
Imperial College London November 29, 2013 – London, UK
Rafael Segundo, KTH, Recent Trends in Power Grid Monitoring, Imperial College London, Nov 29th 2013.
https://workspace.imperial.ac.uk/realsmart/Public/MeetingsEvents/Real-SmartMiniConferenceReport.pdf
Introduction
 Dynamic impact assessment of detailed time-domain simulations is
part of the off-line analysis workflow within the iTesla toolbox
(www.itesla-project.eu).
 The aim is to develop offline criteria to support online analysis
functions.
 After performing a dynamic simulation for a specific contingency, an
appropriate post-contingency severity index needs to be
determined in order to classify the impact of the contingency.
 To do so, a set of scalars, vectors and matrices define the stability
index that provides a measure of how severe the contingency is.
2
Main Challenges
 Only time series are available (no model information).
 The design requirements are:
 fast computation, as numerous contingencies have to be
evaluated for each operating condition
 provide a good measure of how severe the contingency is.
 indicate the severity of the instability/stability
Static concerns
1. Post-fault
overloads of
lines
2. Post-fault bus
under- or overvoltages
Dynamic concerns
3. Smallsignal stability
4. Transient
stability
5. Voltage
stability
3
Indexes for static problems
Post-fault overloads
Useful to observer if the post-fault flows
surpass the network capacity. Monitoring the
power flows through the transmission lines
right after an outage occurs.
Post-fault under/over voltage
Useful to observer whether the deviation of
voltages surpass those acceptable in the
operational standards. Monitoring the voltage
across the transmission network right after an
outage occurs.
Indexes for dynamic problems
Small signal stability
Voltage stability (distant to bifurcation)
P^l i m
(Pa ; Va )
(Pb; Vb)
( P^a; V^a )
Margins
Power (p.u.)
^b)
( P^b; V
Vl i m = V^l i m
Pl i m
(Pc ; Vc)
( P^c; V^c )
Pre-contingency
Post-contingency
Voltage (p.u.)
Angular distance of each mode to a pre-defined
damping ratio. Eigenvalues estimation from the
dynamic simulation sequence. Prony and ERA
methods used.
Compute the distance to loadability boundary.
Transient stability (angular deviation)
N
T
J   M k  ( k (t )   k ()) dt
2
k 1
0
Evaluation of transient stability using the integral of
the square of the angular deviation from
equilibrium.