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____________________ .. ________________________________________ .. ____________________
Computational Challenges in the Computational Challenges in the Simulation of Modern Electrical Simulation of Modern Electrical
Power SystemsPower Systems
Roy CrosbieRoy CrosbieCalifornia State University, ChicoCalifornia State University, Chico
CICSyN 2010Liverpool
28 July 2010
____________________ .. ________________________________________ .. ____________________ 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 EmeritusRoy Crosbie, Professor Emeritus and Institute DirectorNari Hingorani, Visiting Research ProfessorDale Word, Associate Professor, Electrical & Computer EngineeringJohn Zenor, Professor Emeritus
Financial support by the US Office of Naval Research is gratefully acknowledged
2CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________ Conference ThemesConference Themes
• Computational Intelligence > System Modeling & Simulation
• Communication Systems> Real-time Simulation & Control
• Networks> Distributed Power System Control
CICSyN, Liverpool, 28 July 20103
____________________ .. ________________________________________ .. ____________________ 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
4CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________ Modern Power SystemsModern 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.
5CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________
23 ODEs, 12 switches, 2 PWM controllers with sine/triangle comparison PI control plus power calculations
6-pulse Back-to-Back 6-pulse Back-to-Back Converter SystemConverter System
6
CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________
Distributed Energy System Distributed Energy System (Adel Ghandakly)(Adel Ghandakly)
Booster RectifierUnitBooster RectifierUnit
InverterRectifierUnit
InverterRectifierUnit
Battery Storage UnitBattery Storage Unit
PowerGridPowerGrid
LoadLoad
Photo Voltaic UnitPhoto Voltaic Unit
Wind Turbine UnitWind Turbine Unit
DSPECDSPEC
Integration System Monitoring & Control
WTPECWTPEC
PVPECPVPEC
BSPECBSPEC
____________________ .. ________________________________________ .. ____________________ Power System for Electric ShipPower System for Electric Ship
Questions?
8
CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________
High-Speed Real-Time Real-Time SimulationSimulation
Why Real-Time?Simulation running at true speed allows connection to real hardwareHardware can be tested in absence of real systemPlant operators, pilots etc. can be trained under realistic conditions
Why High-Speed?For many systems frame times can be tens of milliseconds or longerSystems with fast dynamics or rapid switching need shorter frames Power electronic systems often need microsecond frame times
9CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________ Choice of TechnologyChoice 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 μS) 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
10CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________ TS201 Board ArchitectureTS201 Board Architecture
11CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________ DSP IssuesDSP 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
12CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________ Software IssuesSoftware 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
13CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________ Real-Time Simulation with FPGAReal-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
14CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________ ML506 BoardML506 Board
15CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________ FPGA Performance vs DSPFPGA 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
16CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________ FPGA Based Performance vs DSPFPGA 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
1.8781.757
1.7901.669
Step Size2.02us
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 TimeTBDFPGA
17CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________
The Need for The Need for Multi-RateMulti-RateReal-Time SimulationReal-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.18
CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________
Multi-Rate Example: Multi-Rate Example: Unmanned Underwater VehicleUnmanned Underwater Vehicle
19
Converter
Controller
VTB BatteryModel
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
19CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________ Multi-Rate ResultsMulti-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
2020CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________
UUV Effects of Multirate UUV Effects of Multirate Ship at .1sec vs .001 sec (Identical Plots)Ship at .1sec vs .001 sec (Identical Plots)
2121CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________ UUV VTB 3D Model OutputUUV VTB 3D Model Output
2222CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________ Power System ControlPower 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
23CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________ Power System CommunicationPower System Communication
Regional Control Center
Local Station
Local Station
Local Station
CICSyN, Liverpool, 28 July 2010 24
____________________ .. ________________________________________ .. ____________________ Power System ControlNetworkPower System ControlNetwork
25CICSyN, Liverpool, 28 July 2010
____________________ .. ________________________________________ .. ____________________ AcknowledgementAcknowledgement
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
CICSyN, Liverpool, 28 July 201026
____________________ .. ________________________________________ .. ____________________
• 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 201027
Power System Networks: Power System Networks: StabilityStability
____________________ .. ________________________________________ .. ____________________
Power System Networks: Power System Networks: ControlControl
• 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 201028
____________________ .. ________________________________________ .. ____________________
Power System Networks: Power System Networks: CommunicationCommunication
• 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 201029
____________________ .. ________________________________________ .. ____________________
Power System Networks:Power System Networks:New Technologies 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
CICSyN, Liverpool, 28 July 201030
____________________ .. ________________________________________ .. ____________________ Future ResearchFuture Research
The GoalAutomatic global control for system-wide transient stability.
The NeedComputation 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)
CICSyN, Liverpool, 28 July 201031
____________________ .. ________________________________________ .. ____________________ ConclusionConclusion
Modern electric power systems provide research opportunities that synthesize the conference themes: computational intelligence, communication systems and networks
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