Model-Simulation-and-Measurement-Based Systems Engineering of Power System Synchrophasor Systems

Presenter Name
Title/Date
Seminar @ Oak Ridge National Laboratory
2017/08/22
Model-Simulation-and-Measurement-Based Systems
Engineering of Power System Synchrophasor Systems
Prof. Luigi Vanfretti
Rensselaer Polytechnic Institute, ECSE, Troy, NY
Web: ALSETLab.com
Email: vanfrl@rpi.edu luigi.vanfretti@gmail.com

About Me - http://ALSETLab.com - Dr. Luigi!
2
Other facts and numbers:
- Guatemalan and Italian Citizenships.
- Speak/write Spanish (native), English, Italian (spoken, poorly written), Norwegian (Basic)
- 36 years, married (March 4th, 2017) - no kids yet… but really want a dog!
- Lived in 4 countries, worked in 5…
2016 - 2017
Consultant.
2000 – 2005.
5 year Electrical Power
Engineering program @
Universidad de San Carlos
de Guatemala.
YOB.
1981
Guatemala
Visiting Researcher
@ The University of
Glasgow, Scotland
2006 – 2009
MSc and PhD @ RPI
2010
Post-Doc @ RPI
Fall 2004
Intern at INDE (National
Electrification Institute),
Substations Engineering
2010 – 2017, KTH Royal Inst. Of Tech.,
Stockholm, Sweden
2010: Associate Professor
2012: Docent (Habilitation)
2013: Associate Professor (‘tenured’)
2011 – 2017, SmarTS Lab. Research
Group
2011 -External
Scientific Advisor
(Consultant)
2011 – 2016
Special Advisor
R&D Division
All @ Statnett SF, Oslo, Norway
(Power System Operator)

Recruiting! @ ALSETLab
• I’m looking for graduate students to join my team!
• If you know someone that would be interested, please tell them to
check my website
• See: http://ALSETLab.com
3

New Course! Spring 2018 - CPS Modeling, Simulation and Analysis
• Understand cyber-physical systems and
how to model them.
• Lean about standardized modeling
languages and compliant tools
• Learn and become proficient with the
Modelica language
• Learn and apply model-based systems
engineering concepts and tools (UML,
SysML using Papyrus RT)
• Apply identification, control and
optimization techniques to CPS systems
• Apply its use for analysis of:
 Power systems
 Energy efficient building automation
 Multi-domain energy systems
 Cyber-physical systems design and
analysis 4

Outline
• Generalities
• About Me (Luigi)
• Recruiting for ALSETLab
• Potential New Course within Curent
• Motivation
 Cyber-physical power systems
 Modeling and Simulation Technologies in
CPS
• MBSE for Power Systems in Design and
Analysis
 Systems architecture and use cases
 OpenIPSL: Modelica for power systems
 RaPId: Validating models automatically
5
• MBSE for Power Systems for Real-Time
Synchrophasor Applications
 Real-time modeling
 PMU applications for monitoring
 PMU applications for control
 Embedded Wide-Area Controls
 GPS signal timing
• Conclusions

Context :
Smart Grids – Transformation of Electrical Power Networks to a Cyber-Physical Systems
6
Smart
Generic term used to refer to the process of digitalization of
different devices / contexts / etc.
(Micro/Mega)-
Grid
Autonomous
- Technical -
Automatic: do exactly as programmed, it has no choice!
Autonomous: a system has a choice to make free of outside influence - free will.
Semi-autonomous: e.g. unmanned vehicles – ability to choose and make decisions
through a pre-defined method.
Zero-Net
Energy
Total amount of energy used by a group (i.e. within a building, or a micro-grid) is
roughly equal to the amount of renewable energy created within  requires
transition in technology available.
Interconnected electrical networks with means of management (techno-and-
economical).
Interconnections between: generation, storage, consumption, and electrical energy
transport at different voltage levels.
What technology is needed for
Smart and Autonomous Cyber-Physical Power Grids?
How can it be developed?

Smart Grids = Cyber-Physical Power Systems
7
A Specific Example - Wide-area control systems (WACS): WACS include an ICT platform that merges the input measurement data and
transforms it to a useful input signal for controllable devices to perform a given function.
Power
System
Digital
Control
Systems
Controllable
Devices
Sensors
(eg. PMUs)
CommsComms
Physical System
“Cyber” system (comms, timing, embedded systems)
WACS consists of: (A) a number of synchronized phasor
measurements units (PMUs – a sort of GPS time-syncronized
distributed sensor) from geographically spread locations, sending
data through (B) a communication network (C) a computer system
termed phasor data concentrator (aggregates and time-aligns data
from different sensors), (D) a real-time computer system where
control functions are implemented, (E) a physical component that
varies electrical quantities following the control function, and (F)
using the GPS system for timing.
A
A
B
C
D
E
F
The future energy system will be a complex cyber-physical system comprised by
different domains interacting with interconnected electrical power apparatus,
through the cyber-system used to manage it.
WACS represent a true cyber-physical
system that requires, at a minimum:
Tools for design,
Tools for simulation and Tools for
hardware and firmware deployment
These kind of tools don’t really exist today
for a joint “cyber” & “physical” system.

Core Technologies
What technologies will be needed for smart grids?
• In general, we have two types of “data”
that can be used to take decisions:
measurements and/or simulations
• These tools should aim at answering
critical questions:
 What can be learned from the past?
 What actions can be taken now?
 What actions can be taken in the future?
Learning from measurement data
Deriving actionable information from measurement
and simulation data
Tools
Modeling
and
Simulation
Sensor
Networks
(e.g. PMUs)
Tools using both
models and
sensor data
Simulation-
based Tools
Measurement-
based Tools
The development of these tools highly depends
on the evolution of M&S Technologies and
Sensor Networks Data (e.g. PMU)

Tomorrow’s Tools: learning from the past and predicting the future
What happened in the past?
What is happening now?
What will happen really soon (sec.
to min)?
What will happen in the future
x min to y hrs to days?
Why did it happen?
How could it be avoided?
Why is it happening?
How can it be avoided?
Why will it happen?
Why will it happen?
Increaseinuncertainties(largerneedtomakepredictionsfromdata)
Increaseofopportunitytolearnfromdata
Learning
from data
Deriving actionable
information!
Data Mining and
Pattern Recognition
Automated Diagnosis
Event reconstruction,
model validation, post-
mortem optimization
Real-Time Monitoring
Real-Time Analysis
Real-Time Control and
System Protection
Short-term
measurement-based
Prediction
Remedial control
actions
Predictive Analysis
Probabilistic
Forecasting
Optimization
Tools
Modelingand
Simulation
SensorNetworks
“data”
“data”
Advancedandhighervalueapplicationsrequiretheright
combinationof“data”fromM&SandSensorData
The development of these tools highly depends on the
evolution of M&S and Sensor Networks

“Smart Grids”
Is our technology in power systems prepared for the 4th Industrial revolution?
• Has the sensor networks evolved sufficiently to enable the fourth industrial revolution?
• Are our Modeling and Simulation (M&S) tools prepared to fulfill the needs of cyber-physical systems?
Is Model Systems-Based Engineering a framework for this evolution?

11
… looks like
we are stuck
in 80s-90s
1980s Today1990s-2000s
Evidence: what can we learn from multiple historical timelines?
Comparing technology development in three different engineering fields

12
Evidence: what can we learn from ‘smart grid’ development?
Two Examples Highlighting “unspoken” Truths
The Royal Sea Port’s ‘Active House’ Smart Meters
From the technical perspective: Why were these failures not identified and avoided from an early stage?
Is it really that hard to develop a “systems-of-systems”/cyber-physical system
requiring experts of two or more domains?
New kind of integration of tech and user needs:
• Inadequate understanding of user requirements.
• Lack of a cohesive approach for ‘system-of-system’ design –
different suppliers NOT able to speak the same language and
working in the same framework
• Product integration and deployment w/o testing and verification.
Two domains, previously loosely related, & release ’to the wild’:
• Cyber-security requirements and metering requirements
should have been jointly defined, designed and assessed.
• Meter experts perhaps are not security experts
• Both domain experts NOT working in the same framework.
• Lack of joint integration testing, verification and validation

Large Number of Vendors for the Final System
Meeting a “system-of-systems” challenge with
Model and Simulation-Based Systems Engineering
13
A Flying Micro-Grid!
M&S used to test
prototypes in variety of
environments.
M&S are used to train users in
the operational environment –
enhancing learning.
Simulation costs 1/10 of
running actual scenarios.
Scale of networks: cost-
prohibitive or technically
impossible for field tests.
M&S used to test and
validate networking
protocols in laboratory -
environment acting as a test
bed.

The Multiple Roles of Modeling and Simulation in building:
Complex Cyber-Physical ”Systems-of-Systems”
14
Large Number of Vendors for the Final System
A Flying Micro-Grid!
M&S used to test
prototypes in variety of
environments.
M&S are used to train users in
the operational environment –
enhancing learning.
Simulation costs 1/10 of
running actual scenarios.
Scale of networks: cost-
prohibitive or technically
impossible for field tests.
M&S used to test and
validate networking
protocols in laboratory -
environment acting as a test
bed.

Model and Simulation-Based Systems Engineering
an evolving framework for multi-domain multi-physics system design, manufacturing and operation
15
Multi-
Domain
Model
Integration
System
Modeling
Transformations
(Meta-
Modeling)
Integrated Modeling Hubs
Design Space
Exploration
(Tooling)
Implementation
(Code Generation)
Testing
V&V
Model Updates
Requirements Allocation and Design + Integration
DB
Requirements
DB System Components & Models
Multi-Domain Model Integration Abstraction Layers, Behavior and Transformations

The Multiple Roles of Modeling and Simulation to develop
Cyber-Physical Power Systems (aka ‘smart grids’)
16
Implementation &
Rapid Prototyping
(software-in-the-loop
real-time simulation)
Implementation &
Testing
(hardware-in-the-loop
System Performance
(deployment and demonstration)
Validation
Verification
Testing
Testing Against Use Cases
Testing with other elements
and within the environment
Testing each component
in isolation and
with other elements
Unit Design
Models
Units
(SW, HW, Data)
Component
Design Models
Components
(SW, HW, Data)
Device Models Subsystems
Overall System
Models (incl. grid)
User
Requirements &
Models
Operational
System
User Cases and Requirements
(HLA Design using UML Spec and CIM)
System Level
Design & Specifications
(physical modeling and
off-line simulation)
Implementation
(Production Code
Generation)
Integrated
Systems
Subsystem
Integration & Tests
(hardware-in-the-loop
Conceptual Application for the Development of a WT Synchro phasor-Based Controller
Are today’s power system modeling and simulation approaches/tools fit to meet the challenges of the
cyber-physical world?

Validation
Verification
Testing
Testing AgainstUse Cases
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System
Use Cases and Structure (System Architecture)
Using SGAM for Synchrophasor Applications for TSO/DSO
• PMU application defined as use cases.
17
Actors and Scenarios
Primary substation
Transmission
system
Distribution system
To TSO
PMU
PMU
Load bus of
interest for
voltage stability
analysis
PMU
Synthesized steady state model
Voltage stability indices
Use Case
Detailed definition of
actors, step-by-step
scenarios, and all
information objects
exchanged between
actors.
SGAM Layers
Contribution towards the MBSE Foundations in Cyber-Physical Power Systems
Mapping of each layer/

Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System
Information Modeling and Exchange
CIM as foundation for future MBSE in Power Grids
18
UML class diagram shows set of
classes represent the CIM classes
and attributes for a Generator.
The Common Grid Modeling Standard (CGMES) V.2.5.
Dependencies Between Profiles
CIM Provides means to model Behavior, Structure,
Parametrics and Requirements
Physics not fully
defined!

Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System
Model to Model Transformation
From the CIM Model to Simulation through Transformation
19
Add Physical Behavior!
Proposed Mapping
Methodology
Model
Transformation
CIM Model (UML – RDF)
Modelica
Tool
Simulation Results
OpenIPSL

Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System
From the CIM Model to Simulation through Transformation
20
Model
Transformation
This classes compose an internal
structure of CIM2Modelica Factory for
storing the values from the CIM model
SysML (Papyrus)
UML class diagram shows set of
classes represent the CIM classes
and attributes for a Generator.
Modelica
Tool
Simulation Results
Model Transformation through Mapping Rules: Example Mappings
SysML component diagram shows
the definition of Modelica model
stereotypes.
<!DOCTYPE model SYSTEM "cim_iteslalibrary_pwpin.dtd ">
<pwPinMap cim_name="Terminal" rfd_id="" package="iPSL.Electrical.Connectors " name="PwPin"
stereotype="connector”>
<attributeMap cim_name="IdentifiedObject.name" mo_name="InstanceName" datatype="String"
variability="none" visibility="none">name</attributeMap>
<attributeMap cim_name="SvVoltage.angle" mo_name="vi" datatype="Real” variability="none"
visibility="public" flow="0">0</attributeMap>
<attributeMap cim_name="SvVoltage.v" mo_name="vr" datatype="Real" variability="none"
<attributeMap cim_name="SvPowerFlow.p" mo_name="ir" datatype="Real" variability="none"
<attributeMap cim_name="SvPowerFlow.q" mo_name="ii" datatype="Real" variability="none"
</pwPinMap>
OpenIPSL
The mapping rules are used to read
value from CIM model and are used to
create instances of iPSL/OpenIPSL
classes.
Class name and package name as data type,
and Instance name from
IdentifiedObject.name (CIM attribute)
The attributes are represented in the mapping
rules (values come from the CIM model)

Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System
Model to Model Transformation Engine
CIM2ModelicaFactory Workflow
(2) Create
Components
(3) Link Components
Model
Transformation
SysML (Papyrus)
Modelica
Tool
Simulation Results
OpenIPSL
(1) Read
Mapping Rules

Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System
CIM2ModelicaFactory Workflow - SysML
Model
Transformation
SysML (Papyrus)
Modelica
Tool
Simulation Results
SysML Model showing the Structure, Attributes and added Physical Behavior
OpenIPSL

Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System
Model to Model Transformation Engine
CIM2ModelicaFactory Workflow: Output Model and Simulation
model IEEE_9BUS_CIM "something here"
iPSL.Electrical.Branches.PwLine Ln46(R=0.017000000923871994,X=0.09200000017881393,G=0,B=0.07900000363588333) "something here" annotation();
iPSL.Electrical.Buses.Bus BUS4 "something here" annotation();
iPSL.Electrical.Loads.PSSE.Load Ld8(angle_0=-91.6318588256836,V_0=1.0116652250289917,P_0=1,Q_0=0) "something here" annotation();
iPSL.Electrical.Machines.PSSE.GENROU.GENROU Gn2(S_b=0,M_b=320,V_b=18,V_0=1.030107021331787,angle_0=-
82.5199966430664,P_0=177.21009826660156,Q_0=12.977800369262695,R_a=0,Xl=0.10000000149011612,H=3.3299999237060547,D=0.6700000166893005,S10=1.0099999904632568,S12=1.019999980926513
7,Tpd0=6,Tpq0=0.5350000262260437,Tppd0=0.05000000074505806,Tppq0=0.05000000074505806,Xd=1.7200000286102295,Xpd=0.23000000417232513,Xppd=0.20999999344348907,Xq=1.659999966621399,X
pq=0.3700000047683716,Xppq=0.20999999344348907) "something here" annotation();
iPSL.Electrical.Branches.PSSE.TwoWindingTransformer
T3(R=0,X=0.0625,G=0,B=0,ANG1=0,S_n=0,CW=0,CZ=0,t2=1,VNOM2=13.800000190734863,VB2=1.0229270458221436,t1=1,VNOM1=230,VB1=237.44049072265625) "something here" annotation();
T1(R=0,X=0.05860000103712082,G=0,B=0,ANG1=0,S_n=0,CW=0,CZ=0,t2=1,VNOM2=230,VB2=235.93170166015625,t1=1,VNOM1=16.5,VB1=1.0381430387496948) "something here" annotation();
T2(R=0,X=0.0575999990105629,G=0,B=0,ANG1=0,S_n=0,CW=0,CZ=0,t1=1,VNOM1=18,VB1=1.030107021331787,t2=1,VNOM2=230,VB2=235.92709350585938) "something here" annotation();
iPSL.Electrical.Machines.PSSE.GENSAL.GENSAL Gn1(S_b=0,M_b=275,V_b=16.5,V_0=1.0381430387496948,angle_0=-
94.33999633789062,P_0=58.78450012207031,Q_0=27.511499404907227,R_a=0,Xl=0.05999999865889549,H=9.550000190734863,D=1.600000023841858,S10=1.0099999904632568,S12=1.0199999809265137,
Tpd0=8.960000038146973,Tppd0=0.05000000074505806,Tppq0=0.05000000074505806,Xd=0.36149999499320984,Xpd=0.15080000460147858,Xppd=0.10000000149011612,Xq=0.23999999463558197,Xppq=0.1
0000000149011612) "something here" annotation();
iPSL.Electrical.Machines.PSSE.GENROU.GENROU Gn3(S_b=0,M_b=300,V_b=13,V_0=1.0229270458221436,angle_0=-87.72000122070312,P_0=89.55909729003906,Q_0=-
12.135199546813965,R_a=0,Xl=0.15360000729560852,H=2.3499999046325684,D=0.4699999988079071,S10=1.0099999904632568,S12=1.0199999809265137,Tpd0=5.889999866485596,Tpq0=0.600000023841
8579,Tppd0=0.05000000074505806,Tppq0=0.05000000074505806,Xd=1.6799999475479126,Xpd=0.2320999950170517,Xppd=0.20999999344348907,Xq=1.6100000143051147,Xpq=0.3199999928474426,Xppq=0
.20999999344348907) "something here" annotation();
// manully implemented
iPSL.Electrical.Events.PwFault f_BUS8(R = 0.1, X = 0.009999999776482582, t1 = 0.9, t2 = 1.1) "something here" annotation();
23
equation
connect(Ln46.p, BUS4.p);
connect(T2.n, BUS7.p);
connect(T2.p, BUS2.p);
connect(Ld8.p, BUS8.p);
connect(Gn2.p, BUS2.p);
connect(Ln45.n, BUS5.p);
// manually implemented
connect(f_BUS8.p, BUS8.p);
connect(Gn1.PMECH0, Gn1.PMECH);
connect(Gn1.EFD0, Gn1.EFD);
end IEEE_9BUS_CIM;

Why open standard-based modeling languages?
• Modeling tools first gained adoption as
engineers looked for ways to simplify
SW development and documentation.
• Today’s modeling tools and their use
cases have evolved.
• Now: need for addressing both system
level design and SW
development/construction.
24
(2015)

Key: standardized and open language specification
is a (computer) modeling language, it is not a tool!
• Modelica is a free/libre object-oriented modeling
language with a textual definition to describe physical
systems using differential, algebraic and discrete
equations.
• A Modelica modeling environment is needed to edit
or to browse a Modelica model graphically in form of
a composition diagram (= schematic).
• A Modelica translator is needed to transform a
Modelica model into a form (usually C-code) which
can be simulated by standard tools.
• A Modelica modeling and simulation environment
provides both of the functionalities above, in addition
to auxiliary features (e.g. plotting)
25
http://modelica.readthedocs.io/en/latest/#

modeling and simulation environment (tool) tasks
26
Modelica Model
Flat model
Hybrid DAE
Sorted equations
C Code
Executable
Optimized sorted
equations
Modelica
Model
Modelica
Graphical Editor
Modelica
Source code
Translator
Analyzer
Optimizer
Code generator
C Compiler
Simulation
Modelica
Textual Editor
Frontend
Backend
"Middle-end"
Modeling
Environment

Acasual Modeling and it’s Implications on Model/Tool Development
• Acasual Modeling implicitly leads to faster development
and lower maintenance for models (and even tools)
• The acausality makes Modelica library classes more
reusable than traditional classes containing assignment
statements where the input-output causality is fixed.
• Modelica Compiler performs Causalization
o It flattens the model and then transform and sort all
equations that give the model description.
o Aim is to match each equation to a variable, hence
the term “matching” process, doing an Index
reduction of the DAEs and transform them to ODEs
27
Approach used by
Modelica Tools
Approach used
by Power System
Tools
User Defined Models
in some PS Tools and
Generic Tools
(Simulink)

The OpenIPSL Project
• http://openipsl.org
• Built using the Modelica language:
• Distributed with the MPL2
license:
28
Free as in Puppy!
Needs a lot of your love and care to grow and be happy!
Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System

The OpenIPSL Library – Key Feautures
OpenIPSL is an open-source Modelica library for
power systems
• It contains a set of power system components
for phasor time domain modeling and
simulation
• Models have been validated against a number
of reference tools (mainly PSS/E)
OpenIPSL enables:
• Unambiguous model exchange
• Formal mathematical description of models
• Separation of models from tools/IDEs and
solvers
• Use of object-oriented paradigms
29
OpenIPSL
Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System

The OpenIPSL Library – WT Example
30

The OpenIPSL Library – Network Example
31
Resulting Parameter Declaration
Resulting Class Instantiation
Class Connections

Many Application Examples Developed!!!
The OpenIPSL Library – Application Examples
32
Klein-Rogers-Kundur 2-Area 4-Machine System
IEEE 9 Bus IEEE 14 Bus
Namsskogan Distribution Network

Open-Standarized Model Exchange and Simulation: FMI and FMUs
• FMI stands for Functional Mock-up Interface:
o FMI is a tool independent standard to support both
model exchange and co-simulation of dynamic models
using a combination of xml-files and C-code, originating
from the automotive industry
The FMI Standard is now supported by more than 40
different simulation tools.
• A Functional Mock-up Unit (FMU) is a model which has been
compiled using the FMI standard definition
33

Model Validation – why?
• What was measured: • What was
simulated:
34
2 3 4 5 6 7 8 9
-2
-1.5
-1
-0.5
0
0.5
1
P(pu)
Time (sec)
Measured Response
Model Response
The quality of the models used by off-line and
on-line tools will affect the result of any
computations
Good model: approximates the simulated response
as “close” to the “measured response” as possible
Validating models helps in having a model
with “good sanity” and “reasonable accuracy”:
Increasing the capability of reproducing actual
power system behavior (better predictions)

Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System
Model Validation:
Methods and Tooling for Validating Power System Models
• RaPId is a toolbox providing a general framework to solve
system identification problems.
• The SW is modular and extensible, with a plug-in SW
architecture allowing to use different optimization, simulation
and signal processing techniques.
• A common application of RaPId is to attempt to tune the
parameters of the model so as to satisfy the user-defined
fitness function
35

Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System
Model Validation:
• RaPId was developed in MATLAB.
o The MATLAB code acts as wrapper to provide
interaction with several other programs (which
may not need to be coded in MATLAB).
• Optimization process can be set up and ran
from the GUI or more advanced users can
simply use MATLAB scripts for the same
purpose
• Plug-in Architecture:
o Completely extensible and open
architecture allows advanced users to add:
 Identification methods
 Optimization methods
 Specific objective functions
 Solvers (numerical integration routines)
36
A number of optimization algorithms are available:
• Particle Swarm Algorithm (PSO)
• Genetic Algorithm (GA)
• Naïve method
• Knitro Algorithm
PSO
GA

Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System
Model Validation:
37

Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System
Model Validation:
38
Video!
Excitation System Parameter Estimation for the MOSTAR
Generator
https://www.youtube.com/watch?v=X8X89l1HBjo
https://github.com/ALSETLab/RaPId

Modelica and FMI
Modern computer technologies opening new opportunities
• Validating power system models requires to develop new methods and new tools
itself:
o The tools for model validation can be built independent from a specific power system simulator,
thanks to the development of the Modelica library which allows to run the models with different tools
and using FMUs.
o Model validation tools developed in this approach will provide additional flexibility to couple in a
modular fashion: simulation, optimization and signal processing tools.
39
Model
Database
Power System
Model Definition in
Modelica
Model
Validation
Tools
(RaPId)
Simulation
Signal
Processing
Optimization
New Method Implemented
To Deal with Validation Problem

Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System
Beyond System Level Design and Analysis:
Model Transformation Advances and Challenges
40
Challenge: Bottleneck in Model Transformation
Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System
• CIM does not consider the requirement for
support in model transformation for
component-level design.
• Power system analysis and design tools do not
support means for model exchange, and do not
model/capture low-level device functions.
• There are still limitations for using real-time
code generated by some Modelica compilers
(need for special parallelization methods to be
supported in large network simulation.
• FMI support for real-time?
• Etc., etc.,…
For the reminder of the work, we thus use a the typical Mathworks-based workflow for Modeling-Code Generation and
Real-Time HIL simulation using a proprietary solution.

2011 - 2012
• We carried out the first implementation of the lab through 2011, mostly by MSc
student (Almas), myself and a little help from technicians.
• First implementation was fully operational around Dec. 2011.
• A paper with the implementation done in 2011 was presented in the IEEE PES
General Meeting  Experience as basis for next implementation.
• A proof of concept application built using openPDC  Experience was basis for
defining the needs for the environment to develop prototype apps.
First Architecture First Implementation
2010:
• I started working on the development of a lab. around August/September 2010.
• Not a lot of people where doing this back then (for power systems), it was also seen as “unnecessary” or “useless” by many of the ‘experts’.
• I prepared a white paper for negotiations internally in the university on the potential use of RT-HIL technology:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-63372
• Procurement process for the simulator was carried out in 2010 / RT Target arrived somewhere in March/April 2011.
- L. Vanfretti, et al, "SmarTS Lab — A laboratory for developing applications
for WAMPAC Systems," 2012 IEEE Power and Energy Society General
Meeting, San Diego, CA, 2012, pp. 1-8.
doi: 10.1109/PESGM.2012.6344839
- M. Chenine, L. Vanfretti, et al, "Implementation of an experimental wide-
area monitoring platform for development of synchronized phasor
measurement applications," 2011 IEEE Power and Energy Society General
Meeting, San Diego, CA, 2011, pp. 1-8.
doi: 10.1109/PES.2011.6039672
Research Infrastructure (Lab.) Dev. (1/3)
A Laboratory for Testing, V&V of PMU Applications
41

ECS
42
M. S. Almas, M. Baudette, L. Vanfretti, S. L⊘vlund and J. O. Gjerde, "Synchrophasor network, laboratory and software applications
developed in the STRONg2rid project," 2014 IEEE PES General Meeting | Conference & Exposition, National Harbor, MD, 2014, pp.
1-5. doi: 10.1109/PESGM.2014.6938835
S3DK
Most Important SW
Technologies
Developed
Khorjin
BabelFish

43

Modeling for Real-Time Simulation
for Synchrophasor Applications
First Version published in SEGAN:
H. Hooshyar, F. Mahmood, L. Vanfretti, M. Baudette, Specification,
implementation, and hardware-in-the-loop real-time simulation of
an active distribution grid, Sustainable Energy, Grids and
Networks, Volume 3, September 2015, Pages 36-51, ISSN 2352-
4677, http://dx.doi.org/10.1016/j.segan.2015.06.002
Second version published in IECON:
H. Hooshyar, L. Vanfretti, C. Dufour, “Delay-free parallelization for
real-time simulation of a large active distribution grid model”, in
Proc. IEEE IECON, Florence, Italy, October 23-27, 2016.
New version in EMTP-RV!
All source files available in Github!:
https://github.com/ALSETLab/ADN-RT-EMTP-Model
44

Testing, V&V: Experimental Work in the Development, Implementation and
Testing of PMU Apps using RT-HIL Simulation
45
(1) A real-time simulation model of active
distribution networks is developed to test the
PMU application.
(2) The real-time
simulation model is
interfaced with phasor
measurement units
(PMUs) in HIL
(3) PMU data is streamed into a PDC, and the
concentrated output stream is forwarded to an
application development computer
(4) A computer with
development tools
within the LabVIEW
environment
receives the PMU
data.
All data acquisition
is carried out using
the corresponding
standards (i.e. IEEE
C37, IEC 61850).
(5) During development,
implementation and testing,
the application is fine-tuned
through multiple HIL
experiments.

PMU-Based Real-Time Monitoring Applications
46
(1) Monitoring & Visualization (2) Mobile Apps
(3) Inter-Area Oscillation Assessment (4) Forced Oscillation
Detection
(5) Real-Time Voltage Stability
Assessment
(1)-(2) M. S. Almas, et al, "Synchrophasor network, laboratory and software applications developed in the STRONg2rid project," 2014 IEEE PES General Meeting | Conference & Exposition, National Harbor, MD, 2014, pp. 1-5. doi:
10.1109/PESGM.2014.6938835
(3) V. S. Perić, M. Baudette, L. Vanfretti, J. O. Gjerde and S. Løvlund, "Implementation and testing of a real-time mode estimation algorithm using ambient PMU data,"Power Systems Conference (PSC), 2014 Clemson University, Clemson, SC, 2014, pp. 1-
5.
doi: 10.1109/PSC.2014.6808116
(4) M. Baudette et al., "Validating a real-time PMU-based application for monitoring of sub-synchronous wind farm oscillations," Innovative Smart Grid Technologies Conference (ISGT), 2014 IEEE PES, Washington, DC, 2014, pp. 1-5.
doi: 10.1109/ISGT.2014.6816444
(5) J. Lavenius and L. Vanfretti, “Real-Time Voltage Stability Monitoring using PMUs”, Workshop on Resiliency for Power Networks of the Future, May 8th 2015. Online: http://www.eps.ee.kth.se/personal/vanfretti/events/stint-capes-resiliency-
2015/07_JanLav_Statnett.pdf
Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System

Transmission Network
Distribution Network
Aggregated load
Effect of both networksEffect of distribution networkEffect of transmission network
More stable with wind gen. @ distribution network
Decoupled Voltage Stability
Assessment of Distribution & Transmission Networks
47
A. Bidadfar, H. Hooshyar, M. Monadi, L.
Vanfretti, Decoupled Voltage Stability
Assessment of Distribution Networks using
Synchrophasors,” IEEE PES General
Meeting 2016, Boston, MA, USA. Pre-print:
link.

Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System
Component Design
for Wide-Area Control Systems
48
(1) RT-HIL Assessment of ECS
• Auto Mode: (Voltage regulation)
• Manual Mode: Field (Current
Regulation)
• PSS Functionality (Multi-Band PSS)
(2) Development of Damping Control
Models (PSS) for RT-SIL
Stabilizers Δω, ΔPa, MB-PSS, and the Phasor POD
where developed for SIL testing.
(1) M. S. Almas and L. Vanfretti, "Experimental performance assessment of a generator's excitation control system using real-time hardware-in-the-loop simulation," IECON 2014 - 40th Annual Conference of
the IEEE Industrial Electronics Society, Dallas, TX, 2014, pp. 3756-3762. doi: 10.1109/IECON.2014.7049059
(2) M. S. Almas and L. Vanfretti, "Implementation of conventional and phasor based power system stabilizing controls for real-time simulation," IECON 2014 - 40th Annual Conference of the IEEE Industrial
Electronics Society, Dallas, TX, 2014, pp. 3770-3776. doi: 10.1109/IECON.2014.7049061
(3) M. S. Almas and L. Vanfretti, "RT-HIL testing of an excitation control system for oscillation damping using external stabilizing signals," 2015 IEEE Power & Energy Society General Meeting, Denver, CO, 2015,
pp. 1-5. doi: 10.1109/PESGM.2015.7286100
(3) Interfacing Control
Models with ECS System
Stabilizers models where testing
both for the MB-PSS and our target
control (Phasor Oscillation
Damper) with the ECS in the loop.

Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System
Component Implementation, Rapid Prototyping and Testing
for Wide-Area Control Systems
49
A, B
A
B
Controller Configuration Interface Software-Hardware Layers Testing
E. Rebello, M. S. Almas and L. Vanfretti, "An experimental setup for testing synchrophasor-based Damping control systems," Environment and Electrical Engineering (EEEIC), 2015 IEEE 15th International Conference on, Rome, 2015, pp. 1945-1950. doi: 10.1109/EEEIC.2015.7165470
E. Rebello, L. Vanfretti and M. Shoaib Almas, "Software architecture development and implementation of a synchrophasor-based real-time oscillation damping control system," PowerTech, 2015 IEEE Eindhoven, Eindhoven, 2015, pp. 1-6. doi: 10.1109/PTC.2015.7232288
E. Rebello, L. Vanfretti and M. Shoaib Almas, "PMU-based real-time damping control system software and hardware architecture synthesis and evaluation," 2015 IEEE Power & Energy Society General Meeting, Denver, CO, 2015, pp. 1-5. doi: 10.1109/PESGM.2015.7285812
A
B
S3DK

Component Implementation, Rapid Prototyping and Testing
exploiting the availability of models for new applications
• Testing:
o Using the 2-Area Four machine Klein-Roger-Kundur power system model.
o In RT-SIL and RT-HIL.
• Results:
• Several local and remote synchrophasor input signals tested
• There is a big difference in the perfromance of the controller in RT-SIL and RT-HIL.
• These results highlight the importance of considering the effect of the hardware
implementation when looking at software simulation results.
50
G. M. Jonsdottir, M. S. Almas, M. Baudette, M. P. Palsson and L. Vanfretti, "RT-SIL performance analysis of synchrophasor-and-active load-based power system damping controllers," 2015 IEEE Power &
Energy Society General Meeting, Denver, CO, 2015, pp. 1-5.
doi: 10.1109/PESGM.2015.7286372
G. M. Jonsdottir, M. S. Almas, M. Baudette, L. Vanfretti, and M. P. Palsson, “Hardware Prototyping of Synchrophasor and Active Load-Based Oscillation Damping Controllers using RT-HIL Approach”, IEEE
PES GM 2016, July 17-21, Boston, Massachusetts, USA
The load control algorithm developed
d/dt
max
min
Load control algorithm
Load
Modulation
Phasor
POD
Local/Remote
Measurements
Oscillatory
Content Load Change
Signal
Switch>0
Idea:
Develop an algorithm to control
industrial load, in particular
aluminium smelters for damping
of inter-area oscillations.
Input Signal 1: V+
Area1
Input Signal 2: (Vφ Area1 - Vφ Area2)/2
Scenario: 5% change in Vref of G1
Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System

Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System
Challenge in Component Implementation and Prototyping
Component Level Functionality also Requires Portability
51
Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System
Challenge: Different RT Targets Required Complete Re-Implementation of
Controls in each Platform
Opal-RT Target
(Mathworks-Based Workflow)
NI-cRIO Target
(LabView Workflow)
Matlab/Simulink Model
LabView FPGA Model

Three level design
Khorjin
Phasor
POD
Load Control
Algorithm
NI-cRIO
RT processor FPGA
20ms 100µs
Load
Modulation
Analog
Output
C37.118
Phasor
POD
Analog
Output
SVC
Control signal
Network
communication
Raw
synchrophasors
LabVIEW Network
published Shared Variables
Input Signal
Selection
Phasor
POD
Load Control
Algorithm
NI-cRIO
PC
RT processor FPGA
20ms 100µs
20ms
Load
Modulation
Analog
Output
C37.118
Phasor
POD
Analog
Output
SVC
Control signal
The hardware prototype controller design
Remotely run VI
• Runs on a PC.
• S3DK used to unwrap PDC
stream.
Real-Time Software VI
• Runs on the real-time processor
of the cRIO.
• Manages the signal selection
Core FPGA Software VI
• Runs on the FPGA
• The load control and SVC
control implemented.
NI-cRIO
Two level design
Real-Time Software VI
• Runs on the real-time processor of the cRIO.
• Khorjin used to unwrap PDC stream.
• Input signal selected
Core FPGA Software VI
• Runs on the FPGA
• The load control and SVC control
implemented.
S3DK is executed on a PC with a non real-time
operating system => Non-deterministic delay
S3DK
Khorjin
Networking Protocol Tools and Source Code
for Synchrophasor Applications – Real-Time Control Example
Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System

Networking Protocol Tools and Source Code
for Synchrophasor Applications – Real-Time Control Example
G1
G2
Area 1
Local
Loads
900 MVA
900 MVA 900 MVA
20 kV / 230 kV
25 Km 10 Km
900 MVA
20 kV / 230 kV
967 MW
100 MVAR (Inductive)
-387 MVAR (Capacitive)
220 Km Parallel
Transmission Lines
Power Transfer
Area 1 to Area 2
10 Km 25 Km
900 MVA900 MVA
20 kV / 230 kV
G4
900 MVA
20 kV / 230 kV 900 MVA
Area 2
Bus1 Bus2
Local
Loads
1767 MW
100 MVAR (Inductive)
-537 MVAR (Capacitive)
Load
Control Load
Modulation
G3
SVC
ΔVref
Scenario: 5% change in Vref of G1
Total delay in RT-HIL setup:
S3DK: 200-500 ms Khorjin: 50-76 ms
Hardware prototype controllers
tested:
• In RT-SIL and RT-HIL.
• In RT-HIL using S3DK and
Khorjin.
In RT-HIL using S3DK
o Blue line far from green line.
o Larger delay (S3DK) can only run in a
non-deterministic computer (... under
windows).
o PDC adds to latency.
In RT-HIL using Khorjin.
o Protocol client runs in RT-Target
avoiding delays from: PDC and parser
in PC.
Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System

Tool-ing Evolution
54
S3DK(LabViewandC++)
BabelFishV1(LabViewandC++)
BabelFishEngine(LabviewOnly)
Khorjin(LabView,C++)
IEC 61850
Mapping
C37.118.2
Module
61850-90-5
Module
•Focus on Performance
•Not necessary to be
user friendly
•Gateway for IEC
transition
•Executes on
embedded systems
with low requirements
•Developed entirely in
LabView.
•Only requires IP
address, Port number
and Device ID of the
PMU/PDC stream
Reading
Module
(C++)
Interfacing
Module
(Active X)
GUI
Module
(LabView)
Why only Labview?
Derive Requirements for Embedded Computers
•Real-time reading from
PMU/PDC (DLL)
•Interfacing with
LabView via ActiveX
(minimum delay)
•LabView presentation
layer
•Client/Server
Architecture
•Multi-Threading
•LabView VI/API
•Calls C++
Methods
•Toolbox-like
functions
Why Khorjin?
Support for COTS Embedded Computers
S3DK
(LabView & C++)
BabelFishV1
(LabView & C++)
BabelFish Engine
(LabView Only)
Khorjin
(C++)
Development: 2011 - 2013 Development: 2014 – 2016 …
PMU_CFG-
2_PACK
CMD
NamesofPMUs
Elements
PMU_DA
TA_PACK

Repositories Currently Available at GitHub
• S3DK: https://github.com/ALSETLab/S3DK
• BabelFish: https://github.com/ALSETLab/BabelFish
• Audur: https://github.com/ALSETLab/Audur
• Khorjin: Will be available at GitHub…
55
L. Vanfretti, V. H. Aarstrand, M. S. Almas, V. S. Perić and J. O. Gjerde, "A software development toolkit for real-time synchrophasor applications," PowerTech (POWERTECH), 2013 IEEE
Grenoble, Grenoble, 2013, pp. 1-6.
doi: 10.1109/PTC.2013.6652191
L. Vanfretti, I. A. Khatib and M. S. Almas, "Real-time data mediation for synchrophasor application development compliant with IEEE C37.118.2," Innovative Smart Grid Technologies
Conference (ISGT), 2015 IEEE Power & Energy Society, Washington, DC, 2015, pp. 1-5.
doi: 10.1109/ISGT.2015.7131910
L. Vanfretti, M.S. Almas and M. Baudette, “BabelFish – Tools for IEEE C37.118.2-compliant Real-Time Synchrophasor Data Mediation,” SoftwareX, submitted, June 2016.
S.R. Firouzi, L. Vanfretti, A. Ruiz-Alvarez, F. Mahmood, H. Hooshyar, I. Cairo, “An IEC 61850-90-5 Gateway for IEEE C37.118.2 Synchrophasor Data Transfer,” IEEE PES General Meeting
2016, Boston, MA, USA. Pre-print: link.
S.R. Firouzi, L. Vanfretti, A. Ruiz-Alvarez, H. Hooshyar and F. Mahmood, “Interpretation and Implementation of IEC 61850-90-5 Routed-Sampled Value and Routed-GOOSE Protocols for
IEEE C37.118.2 Compliant Wide-Area Synchrophasor Data Transfer,” Electric Power Systems Research. March 2016. Submitted. August 2016. First Revision.
L. Vanfretti, G.M. Jonsdottir, M.S. Almas, E. Rebello, S.R. Firouzi and M. Baudette, "Audur – A platform for Synchrophasor-Based Power System Wide-Area Control System
Implementation," submitted for review, Software X, February 28, 2017.

Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System
Challenge in Component Implementation and Prototyping
Networking & Protocol Models and Software (Libs. / Source)
56
Challenge: Joint (integrated) modeling of networking, IT and power grid physics through
the whole Model & Simulation - Based Systems Engineering Framework.
Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System
Through SGAM, but need to
create CIM profile
Potential for use of Modelica
Synchronous – library of
components is needed…
Software Models with ICT
Behavior
Network Protocol
Client/Server Source
(with some help from
Khorjin, maybe!)

Validation
Verification
Testing
in isolation and
with other elements
Design
User
Requirementand
Specifications
Verification
Validation
Integration
Implementation
Development
Natural Language
Models
Hardware & Software
Use Case:
WT Control
Product:
WT Control
System
Verification and Validation
for Timing System-Dependent Applications
57
Case Study: GPS Vulnerability and Impact on Synchrophasor Applications
Challenge: Joint (integrated) modeling, simulation and TV&V including Timing Systems through the whole Model &
Simulation - Based Systems Engineering Framework.
Real-Time
Simulator
Substation Clock
Arbiter Model 1094 B
GPS Antenna
Phasor
Measurment
Units (PMUs)
IRIG-B
Communication
Network
(Managed Ethernet
Switch)
PMU
Stream
Monitoring application
displaying real-time electrical
quantities
Sychrophasors received in external controllers
based on NI-cRIOs with deployed algorithm for
protection (islanding detection) and control
application (power oscillation damping)
Legend
GPS Signal
Hardwired
PMU stream
PDC stream
To WAMPAC
Feedback Signal
3-phase Voltage and current signals
to the low-level interface of PMUs
Feedback signal from
external controller to RTS
To External Controllers for synchrophasor
protection/control applications
Unwraps PDC stream and provides
raw measurements in LabView
enviroment
S3
DK
SEL 421 (1)
SEL 421 (2)
Power system test-
case model executed
in real-time in Opal-RT
Phasor Data
Concentrator
SEL-5073
PDC stream
The loss in time synchronization signal shows an erroneous
increase in line loading from 80% to 92 % and shows an
increase from 625 MW to 752 MW within a span of 550 s
after the disconnection of time signal from PMU2
Impact on Near-Real-Time MonitoringImpact on Real-Time Control
M.S. Almas and L. Vanfretti, “Impact of Time-Synchronization Signal Loss on PMU-based WAMPAC Applications,” IEEE PES General Meeting 2016,
Boston, MA, USA. Pre-print: link.

Conclusions: The Cyber-Physical Future… is in our hands!
• We need to spend significant efforts to face the challenges of the cyber-
physical future of power systems!
• Model & Simulation-Based Systems Engineering (MBSE) gives a proven
foundation for developing complex cyber-physical systems from design to
manufacturing to operation.
• We need to focus in the development of
o Tools for multi-domain and multi-physics modeling
o Tools and models for design,
o Tools for simulation and
o Tools for hardware implementation
o Capable of taking into account interactions (ICT, cyber and physical
security, etc) from different parts of the “cyber-physical” system while
managing the basic functions of the grid.
• We have only began to develop these foundations – we can’t do it alone:
Systems View is key.
• We also need to think about the socio/economical/phylosophical
implications of software pervasiveness.
• The cyborg-world is upon us! Let’s be prepared!
58
Power
System
Digital
Control
Systems
Controllable
Devices
Sensors
(eg. PMUs)
CommsComms
Physical System
“Cyber” system (comms, timing, embedded systems)

59
Luigi Vanfretti Tin RabuzinAchour
Amazouz
Mohammed
Ahsan Adib
Murad
Francisco
José Gómez
Jan Lavenius Le Qi Maxime
Baudette
Mengjia
Zhang
Tetiana
Bogodorova
Giusseppe
Laera
Joan Russiñol
Mussons
The OpenIPSL can be found online
• http://openipsl.org
RaPId, a system identification software that uses OpenIPSL can be
found at:
• https://github.com/ALSETLab/RaPId
• http://dx.doi.org/10.1016/j.softx.2016.07.004
Thanks to all my current and former
students, friends and developers that
have supported the effort!
Our work on OpenIPSL has been published in the
SoftwareX Journal:
• http://dx.doi.org/10.1016/j.softx.2016.05.001
Marcelo Castro Miguel Aguilera

Model-Simulation-and-Measurement-Based Systems Engineering of Power System Synchrophasor Systems

More Related Content

What's hot (19)

Similar to Model-Simulation-and-Measurement-Based Systems Engineering of Power System Synchrophasor Systems (20)

More from Luigi Vanfretti (17)

Recently uploaded (20)

Model-Simulation-and-Measurement-Based Systems Engineering of Power System Synchrophasor Systems

Editor's Notes