keynote-1 - UKSim

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Computational Challenges in the
Simulation of Modern Electrical Power
Systems



Roy
Crosbie

California State University, Chico

CICSyN 2010

Liverpool

28 July 2010



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Acknowledgements

The research described in this presentation is based on the work of a
research team at the McLeod Institute of Simulation Sciences at
California State University, Chico, USA.


Team Members

Richard Bednar,
Professor Emeritus

Roy Crosbie,
Professor Emeritus and Institute Director

Nari Hingorani,
Visiting Research Professor

Dale Word,
Associate Professor, Electrical & Computer Engineering

John Zenor,
Professor Emeritus


Financial support by the
US Office of Naval Research

is gratefully
acknowledged

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CICSyN, Liverpool, 28 July 2010



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Conference Themes


Computational Intelligence > System Modeling & Simulation



Communication Systems> Real
-
time Simulation & Control



Networks> Distributed Power System Control

CICSyN, Liverpool, 28 July 2010

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Traditional Approach to

Simulation of Power Systems

A.
Steady State Load Flow Studies

B.
Dynamic Simulation of Transient Behavior


Seminal Analysis by
Dommel


Nodal Circuit Analysis + Implicit Trapezoidal Integration


Non
-
linearities

require iterative procedures


Electromagnetic Transients Program (EMTP)


50 microsecond maximum integration steps






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Modern Power Systems


Much greater use of power converters (ac to dc & dc to ac)



High
-
voltage d.c. transmission



Renewable energy generation (solar, wind etc.)



Independent power systems for ships etc.


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CICSyN, Liverpool, 28 July 2010



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23 ODEs, 12 switches, 2 PWM controllers with sine/triangle comparison PI control plus power calculations









6
-
pulse Back
-
to
-
Back

Converter System


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, Liverpool, 28 July 2010



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Distributed Energy System

(Adel
Ghandakly
)


Booster Rectifier

Unit

Inverter

Rectifier

Unit

Battery Storage
Unit

PowerGrid

Load

Photo Voltaic Unit

Wind Turbine Unit

DSPEC

Integration System
Monitoring & Control

WTPEC

PVPEC

BSPEC



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Power System for Electric Ship

Questions?

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, Liverpool, 28 July 2010



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High
-
Speed

Real
-
Time Simulation

Why Real
-
Time?


Simulation running at true speed allows connection to real hardware


Hardware can be tested in absence of real system


Plant operators, pilots etc. can be trained under realistic conditions


Why High
-
Speed?


For many systems frame times can be tens of milliseconds or longer


Systems with fast dynamics or rapid switching need shorter frames


Power electronic systems often need microsecond frame times



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CICSyN, Liverpool, 28 July 2010



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Choice of Technology


Many real
-
time simulations use a real
-
time version of
Linux running on a high
-
performance PC


Operating system jitter (of the order of 10
μ
S) limits
minimum frame time


Higher
-
performance is possible from systems with
Pentium or PowerPC based processors but only with
custom designs


Initial solution: arrays of digital signal processors
inserted in PCI bus of conventional PC with Windows
OS running on host


off
-
the
-
shelf components; no
problems with OS jitter

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TS201 Board Architecture

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, Liverpool, 28 July 2010



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DSP Issues


Scheduling Processor Tasks


Equalizing processor execution times


Minimise inter
-
processor data transfers


Internal Data Transfer


Common memory vs. link ports


External Data Transfer


Digital and analog outputs and inputs


Code efficiency


Hand
-
coding vs compiler efficiency


Identify efficient HLL code sequences


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Software Issues


Choice of numerical integration algorithm


Euler vs Runge
-
Kutta vs implicit trapezoidal vs state
-
transition methods


Analyse and monitor accuracy and stability of numerical integration


Combine differential equations with integration algorithm before coding


Minimize total mathematical operations



Hand coding vs optimizing compiler


Hand coding may be needed if compiler can’t exploit processor architecture


Use HLL constructs that produce more efficient code

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CICSyN, Liverpool, 28 July 2010



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Real
-
Time Simulation with FPGA


FPGA offers competitive alternative to DSP; shorter frame times



Can be programmed using Simulink blockset, VHDL, M
-
code



Full 6
-
pulse model ported to larger FPGA



Soft processor used for slow Ethernet interface



Direct programmed high
-
speed Ethernet interface

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ML506 Board

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FPGA
Performance
vs

DSP

Model/Platform

Minimum Frame
Time

Processor

Clock Rate

6 Pulse BTB
-

Hammerhead
Board, 23 ODEs

16 µs

AD 21160 DSP

80Mhz

6 Pulse BTB
-

TigerSharc
Board, 23 ODEs

3.85µs

AD TS101 DSP

250Mhz

6 Pulse BTB
-

TigerSharc
Board, 23 ODEs

2.02µs

AD TS201 DSP

500Mhz

12 Pulse BTB
-

TigerSharc
Board, 39 ODEs

4.5µs

AD TS201 DSP

500Mhz

6 Pulse BTB
-

Xilinx ML506
Board,
Virtex

5, 23 ODEs

450nS

Virtex

5 FPGA

100Mhz

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FPGA Based Performance vs DSP

Communications
Controller
Converter Left
0
.
398
1
.
622
Main Communicator Loop
1
.
630
Main Controller Loop
1
.
506
Main Converter Right Loop
1
.
406
Main Converter Left Loop
1
.
869
1
.
878
1
.
757
1
.
790
1
.
669
Step Size
2
.
02
us
Step Time
Begins
Main
Communicator
Loop Begins
0
.
239
0
.
251
0
.
263
Start Signals Sent by Communicator
Main
Controller
Loop Begins
End Signals Sent to Communicator
End Signal
Received by
Communicator
Communicator
Ends
Converter Right
1
.
990
0
.
121
is used to send and receive handshaking variables
between that processor and the communicator
.
Interrupt Handler
Main
Converter
Right Loop
Begins
Main
Converter
Left Loop
Begins
This is the delay between when a new simulation frame begins
and when the processor is sent handshaking variables
.
0
.
118
0
.
130
0
.
142
.
230
Converter
Left Loop
Setup
Time
TBD
FPGA
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CICSyN, Liverpool, 28 July 2010



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The Need for
Multi
-
Rate

Real
-
Time Simulation


CSU, Chico developed HSRT simulations with frame rates up to
2 MHz (500 nS frame times)


These frame rates are needed for power electronic components
but not for slower system components such as motors,
mechanical components, thermal effects etc.


Multi
-
rate real
-
time simulations simulate different subsystems at
different frame
-
rates on different simulation platforms.


The slower components are simulated in real
-
time using a
commercial RTOS, often with Simulink support, for faster,
cheaper model development.


Multi
-
rate also improves performance of non real
-
time
simulations.


Multi
-
rate raises questions of stability and accuracy.


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Multi
-
Rate Example:

Unmanned Underwater Vehicle

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Converter
Controller
VTB Battery
Model
Controller/Converter Model
(CSU Chico)
VTB Synchronous,
Permanent Magnet Motor
Model
UUV Physical Model
(Glasgow)
Vehicle Control Inputs
VTB Multi-Rate Solver (USC)
Low Rate
High Rate
Medium Rate
Low rate
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CICSyN, Liverpool, 28 July 2010



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Multi
-
Rate Results


Multi
-
Rate Configuration


Converter, Switch Controller

2 µsec


Feedback Controller


800 µsec


Motor/Propeller


50
-
100 µsec


Battery, Ship


.1 sec


Graphics



.1 sec



Multi
-
Rate Performance on 2.16 GHz Mac Running Windows XP


All components at 2 µsec:



.001x real time


Multi
-
rate, Motor/Propeller 50 µsec


1.2x real
-
time


Multi
-
rate, Motor/Propeller 100µsec


2.0x real
-
time

20

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UUV Effects of
Multirate


Ship at .1sec vs .001 sec (Identical Plots)

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UUV VTB 3D Model Output

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Power System Control



Hierarchical control combines local controllers at stations
and system wide control at control centers


As more and more raw data is being sent from stations to
control centers communication channels are overloaded


On
-
line real
-
time simulators at stations can reduce data
volume through processing of raw data


This can facilitate more rapid detection of critical behavior
and more rapid action to minimize its effect



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CICSyN, Liverpool, 28 July 2010



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Power System Communication



Regional
Control
Center

Local Station

Local Station

Local Station

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Power System
ControlNetwork

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CICSyN
, Liverpool, 28 July 2010



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Acknowledgement

The following material is based on:

Power System Stability: New Opportunities for Control

By
Anjan

Bose

Chapter in

Stability and Control of Dynamical Systems and
Applications,

Derong

Liu and
Panos

J.
Antsaklis

eds


http://gridstat.eecs.wsu.edu/Bose
-
GridComms
-
Overview
-
Chapter.pdf



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Power system networks in North America & Europe are
the world’s’ largest man
-
made interconnected networks



All the rotating generators in one network rotate
synchronously



Any large disturbance (e.g. equipment short circuit) can
make the power system unstable.

CICSyN, Liverpool, 28 July 2010

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Power System Networks:

Stability



____________________ .. ____________________




Power System Networks:

Control


Control uses a combination of isolating switches,
continuous control of voltage and power, and power
-
electronic switch
-
based control.



These controls are all local (equipment/control in same
substation)



Regional and system
-
wide control is mainly limited to
adjusting generation levels to adjust to slowly changing
power loads


CICSyN
, Liverpool, 28 July 2010

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Power System Networks:

Communication


System
-
wide control needs communication between
contol centre and substations (microwave, telephone
lines, increasing use of optical fibre)



Lower costs, increasing bandwidth, GPS time
synchronization, improved power electronics offer
opportunities for fast distributed controls



Increasing amount of data gathered at substations at
mS rates is too voluminous for real
-
time transmission
and control. OK for later study.



CICSyN, Liverpool, 28 July 2010

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Power System Networks:

New Technologies


Faster, cheaper computers


Embedded in equipment


Provide intelligence in the control loops



Low
-
cost broadband communications


Greater volume of real
-
time data


Possibilities for decentralizing control




Better power electronic controls


FACTS


Flexible AC Transmission Systems

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Future Research


The Goal


Automatic global control for system
-
wide transient stability.



The Need


Computation to analyze the situation and compute necessary control
actions, has to match the time
-
frame of current protection schemes
(milliseconds).



“Whether this is possible with today’s technology is unknown. However,
the goal is to determine what kind of communication
-
computation
structure is needed to make this feasible.” (Bose)


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Conclusion


Modern electric power systems provide research
opportunities that synthesize the conference
themes: computational intelligence,
communication systems and networks

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