OPAL-RT RT14 Conference: SESA Laboratory
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Transcript of OPAL-RT RT14 Conference: SESA Laboratory
The 7th International Conferenceon Real-Time Simulation Technologies
Montreal | 9-12 June, 2014
Dr. Sebastian Rohjans
OFFIS – Institute for InformationTechnology
The 7th International Conferenceon Real-Time Simulation TechnologiesMontreal | 9-12 June, 2014
THE SMART ENERGYSIMULATION ANDAUTOMATION LAB (SESA)
The 7th International Conferenceon Real-Time Simulation TechnologiesMontreal | 9-12 June, 2014
Future Energy Systems
Integration of high numbers of active components into control systems Supply-dependent and uncertainty about forecasts
Automated operational optimization required
LV LV
MV
The 7th International Conferenceon Real-Time Simulation TechnologiesMontreal | 9-12 June, 2014
Managing Complexity
Smart Grids are complex systems
Field Testing:
Expensive
Inflexible
Dangerous
Simulation
The 7th International Conferenceon Real-Time Simulation TechnologiesMontreal | 9-12 June, 2014
Simulation of Smart Energy Systems
Suitable consideration of all facets is essential!
Formal analysis vs. simulation
Integration of heterogeneous models and simulators
1° at 50 Hz1 cycle1 second1 minute1 hour1 day
Partial Differential Equations (PDE)
Ordinary Differential Equations (ODE)
Algebraic Equations/Phasors (AE)
Discrete Automata (DA)
Time Series (TS)
Probability Density Functions (PDF)
Static Rules/Descriptions (SR)
V
Hz
computational expensebased on the
model representation
„trusted“
„untrusted“
Model Representations
The 7th International Conferenceon Real-Time Simulation TechnologiesMontreal | 9-12 June, 2014
Simulation of Smart Energy Systems (cont`d)
Use case specific „functional“ combination Simplified discrete models
High-precision (dynamic) models
Automated composition and orchestration of heterogeneous models in dependence of Availability of models
Availability of time
Availability of budget
Inspected matter
Assessing the quality of conducted experiments Systematic „errors“
Statistical significance
A recurring process!
MS
MS
MS
NS
NS
NS
NS
NS
NS
NS
NS
NS
The 7th International Conferenceon Real-Time Simulation TechnologiesMontreal | 9-12 June, 2014
SESA-LabHard- and Software Integration Platform
Real-Time Automation Lab(University of Oldenburg)
Co-Simulation Platform(OFFIS – Institute for Information Technology)
The 7th International Conferenceon Real-Time Simulation TechnologiesMontreal | 9-12 June, 2014
mosaikmosaik – Modular Smart Grid Co-Simulation
Automated composition and orchestration of heterogeneous energy system models
Flexible mosaik-API for simulators, control strategies (MAS), etc.
Powerful description language for scenarios (rule-based instantiation and linking of models)
Smart Grid reference model
The 7th International Conferenceon Real-Time Simulation TechnologiesMontreal | 9-12 June, 2014
mosaikExample Scenario
# Starting Simulatorspypower = start('PyPower')hhsim = start('HouseholdSim')pvsim = start('CSV')
# Instantiating modelsgrid = pypower.Grid(gridfile=GRID_FILE)houses = hhsim.ResidentialLoads(
profile_file=PROFILE_FILE)pvs = pvsim.PV.create(20)
# Connecting Entitiesconnect_by_node_id(houses, grid)connect_randomly(pvs, grid.filter_name('node_*'))
The 7th International Conferenceon Real-Time Simulation TechnologiesMontreal | 9-12 June, 2014
mosaikmosaik – Modular Smart Grid Co-Simulation
Automated composition and orchestration of heterogeneous energy system models
Flexible mosaik-API for simulators, control strategies (MAS), etc.
Powerful description language for scenarios (rule-based instantiation and linking of models)
Smart Grid reference model
Event-based simulation (coordinated execution and data exchange)
After a testing phase with international partners it is now available as Open Source Software (http://mosaik.offis.de)
The 7th International Conferenceon Real-Time Simulation TechnologiesMontreal | 9-12 June, 2014
SESA-LabHard- and Software Integration Platform
Real-Time Automation Lab(University of Oldenburg)
Co-Simulation Platform(OFFIS – Institute for Information Technology)
The 7th International Conferenceon Real-Time Simulation TechnologiesMontreal | 9-12 June, 2014
SESA-LabTopology Independent Linking and Allocation of I/O (analog and digital)
...VPN Gateway Router/Firewall
Internet
HERO Cluster (High-End Computing Resource Oldenburg)
25 (max. 100) Sessions @ 1Gbit/s
...
...
6x BECKHOFF CX2020RT-Device-TargetsComponent Models
AgentsController
18x
Communication Simulation
D/A
EtherCAT
Ethernet
96x Ports
48x Ports
I/O-Switch
Station DisplaysSwitching StateUtilizationLabViewConsole
2x6x CPUs @ 2,6 GHz
Virtualization Servermosaik-SimulationDevelopment EnvironmentLicense Server
Control StationSCADA
IEC 60870
IEC
618
50
U
ML
CIM
(619
70/6
196
8)
OP
C U
A (
62
541)
Standard-compliant Information- and
Process Chain
Protocol Switch 18x
6x Cores (~140 Nodes)
...
Station ComputerControl SystemProtection SystemComponent ModelsAgentsController
3x BECKHOFF C6920
D/A
D/A
Projected Extensions(2014-2016)
RT-Grid-TargetPower Grid Models
Component Models
3x Cores (~70 Nodes)
OPAL-RT eMEGAsim
The 7th International Conferenceon Real-Time Simulation TechnologiesMontreal | 9-12 June, 2014
SESA-LabHard- and Software Integration Platform
Highly dynamic
Steady State
Opal-RT eMEGAsimReal-time simulator
Models created with Matlab/Simulink
The 7th International Conferenceon Real-Time Simulation TechnologiesMontreal | 9-12 June, 2014
First Tests eMEGAsimSimPowerSystems
mm
The 7th International Conferenceon Real-Time Simulation TechnologiesMontreal | 9-12 June, 2014
First Tests eMEGAsimSimPowerSystems
m
Ueff
Ieff
PLoad
PGeneration
Wait forreal time
The 7th International Conferenceon Real-Time Simulation TechnologiesMontreal | 9-12 June, 2014
Coupling Requirements
Real-time
Continuous
μs resolution Transients
Time domain Harmonics
Simulation time
Discrete event
sec resolution
Frequency domain
Tool A (eMEGAsim) Tool B (mosaik)
Latency handling
A B
Real-time!Information exchange!
fft,
wavelets,
ML?
Loss handling
Accuracy!
A B
Uncertaintyquantification
Effectivity!
A ! B
Scheduling
The 7th International Conferenceon Real-Time Simulation TechnologiesMontreal | 9-12 June, 2014
Future Developments
SimPowerSystems instead of Simscape
Interfacing between SPS and Simulink
General approach for RT scenario component
Event identification for dynamic simulation
Dynamic real-time scheduling
Framework for global uncertainty quantification
The 7th International Conferenceon Real-Time Simulation TechnologiesMontreal | 9-12 June, 2014
Summary
Transition towards Smart Grids implies significant changes in the overall energy system’s architecture and infrastructure
Continuously increasing level of the system’s complexity
For managing, analyzing, and understanding this novel Smart Grid system, simulation approaches have to be adopted
Although different approach already exist, most of them are still developed for a certain purpose and do not follow a modular, composable and integrative approach
However, as Smart Grid simulation is a highly interdisciplinary field of application, simulation suites (tools) should fill this gap