(co-)simulation of power systems, controls, components for ...

Modelling and (Co-)simulation

of power systems, controls and components for

analysing complex energy systems

University College Dublin – 11th October 2013

Stifter Matthias – AIT, Energy Department, Complex Energy Systems

Workshop on Software Tools for Power System Modelling and

Analysis

About Co-Simulation

3 08.10.2013

Co-Simulation Motivation

Multi-domain problems not covered in one tool

Electrical power system

Communication system

Controls / SCADA

Different simulation time steps

Different concepts: continuous time and discrete event time systems

Use existing highly complex and detailed models

Integration of real components

Scalability and flexibility

Combine different dedicated simulation tools and domains

Analyse different subsystems and their interactions

4 08.10.2013

Co-Simulation Overview

Various types of modelling and simulation:

5 08.10.2013

re-unification of the separately modeled

subsystems equations co-simulation

„classical“ Simulation

model separation for simulation

closed simulation

distributed simulation

distributed modelling

closed modelling

number of integrators

number of modelers

=1

>1

=1 >1

Source: M. Geimer, T. Krüger, P. Linsel, Co-Simulation, gekoppelte Simulation oder

Simulatorkopplung? Simulation 2006.

Co-Simulation (1)

Coupling on model level

6 11.10.2013



Application 1 Application 2

Integrator level

Model level Model level

Integrator level

Model definition, equationsModel code export,

Model and integrator code export

Co-Simulation (2)

Coupling on integrator level

7 11.10.2013



Application 1 Application 2

Integrator level

Model level Model level

Integrator level

Equation evaluation (e.g. function call)

Integrator evaluation(distributed simulation)

Simulation challenge: power system and controls

System with controller to fulfilll certain functionalities: e.g., voltage control task

consists typically of the following parts:

Power system model

Component models

Controller /

SCADA

8 10.10.2013

Power Grid Simulation

Power System Analysis

ComInterface

transient/steady state

SCADAsystem

TCP, UPD, IEC 61850, IEC 60870-5-104

Controller

ComInterface

ComInterface

-

TCP, OPC

Component Simulation

-

TCP, OPC

Co-Simulation approach

In this simulation coupling, the individual simulators run in real time and parallel,

exchanging results and set-points.

PowerFactory Matlab / SimPowerSystem

PowerFactory 4DIAC (distributed control system)

4DIAC ScadaBR

9 10.10.2013

Controller Emulation

Power SystemAnalysis

ComponentSimulation SCADA Emulation

ASN.1 over TCP/IP

ASN.1 over TCP/IP

ASN.1 over TCP/IP

Grid Component

Simulation

(e.g., Distributed

Energy Resources)

Electricity Grid

Simulation

Supervisory Control

and Monitoring

Simulation

(Embedded) Control

System Development

and Simulation

Simulation challenge: dynamic EV charging

Need for simulation of :

impact of the electric vehicle energy demand

energy depends on trip length, temperature, etc.

test charging management strategies

charging power is not static

Hybrid system: discontinuity

taking place at discrete events

Need for simulation of the EV trip

to get the energy needed to recharge

Combine the power system simulation with the simulation of the discharging

10 10.10.2013

P

t

P

t

Recuperation

Dischargea) b)

Charge

Continuous System

Hybrid System

Simulation challenge: dynamic EV charging

11 20 May 2013

small scale distribution grid

medium/low voltage network with consumers

realistic battery model household load profiles

taken from measurement

campaign

charging control algorithm

distributed charging power

regulation

stochastic driving patterns

derived from real data

Simulation tools

12 08.10.2013

PSAT Power system analysis toolbox

Matlab/Simulink and Octave

continuous time-based

simulation

GridLAB-D multi-agent based power system

simulation

includes various energy-related

modules

discrete event-based simulation

4Diac / Forte framework for distributed

control systems

intended for event based

controls in real time

open source IDE and Runtime

Modelica dedicated multi-domain (physics)

simulation language

supports event handling

acausal simulation (continuous

time-based simulation)

Main challenge

coupling discrete event-based simulation with continuous time-based models.

Co-Simulation Interfaces and Mechanisms

13 10.10.2013

Co-Simulation: synchronous, sequentially

Co-Simulation run sequentially and blocks until the results are available

simulate same time step twice

simulate at next time step

14 10.10.2013

step ∆t

power flow

send result Ubus,Pmeas

notify INreceive

wait

send resultPset

notify OUTreceive

power flow

next step

simulate

send ready

wait send ready

Data exchange (OPC, TCP/IP)

Co-Simulation(parallel)

PowerFactoryt0 t1 t2

controller co-sim integration time

simulation time

t3

data exchange1 2

t0 t1 t2

continuous model co-sim integration time

simulation time

t3

1 2

t1-

data exchange

M. Stifter, R. Schwalbe, F. Andrén, and T. Strasser, “Steady-state co-simulation with PowerFactory,”

in Modeling and Simulation of Cyber-Physical Energy Systems, Berkeley, California, 2013.

Co-Simulation: asynchronous, parallel

Co-Simulation via external DLL

15 10.10.2013

stability (rms)

step ∆t

DSL model(external)

input invoke

result

store state

next step

simulate

PowerFactory

returnemit event

exec. event

Co-Simulation (sequential) via external DLL (digexdyn.dll)

t0 t1

∆tInt

t2

DSL integration time

simulation time

t3t3'

event

.

M. Stifter, R. Schwalbe, F. Andrén, and T. Strasser, “Steady-state co-simulation with PowerFactory,”

in Modeling and Simulation of Cyber-Physical Energy Systems, Berkeley, California, 2013.

Co-Simulation: real time synchronisation

Dynamic behaviour

C-HIL / Regler

Filters

Synchronisation with system time / scaled time base

16 10.10.2013

t0 t1 t2

parallel co-simulation

real-time

t3

1

2

∆tlag

∆tcommunication delay

Functional Mock-Up Interface for Model Exchange

FMI: A standarized API for describing

models of DAE-based modeling

environments (Modelica, Simulink, etc)

Functional Mock-Up Unit

model interface (shared library)

model description (XML file)

Executable according to C API

low-level approach

most fundamental functionalities

only

tool/platform independent

17 08.10.2013

Gaining popularity among tool vendors

CATIA, Simulink, OpenModelica, Dymola, JModelica, SimulationX, etc.

Simulation environment for FMI for Model Exchange

Simulation master algorithm not

covered by FMI specification

tool independence

Requirements

initialization

numerical integration

event handling

orchestration

Well suited for simulation tools

focusing on continuous time-based

modelling

What about plug-ins for discrete

event-driven simulation tools?

18 08.10.2013

The FMI++ library

High-level access to FMUs

model initialization, get/set

variable by name, etc.

High-level FMU functionalities

integrators, advanced event

handling, rollback mechanism,

look-ahead predictions, etc.

Open-source C++ library

tested on Linux and Windows

(MinGW/GCC and Visual Studio)

available at sourceforge.net

19 08.10.2013

synchronous interaction between discrete event-based environment and

a continuous equation-based component

http://sourceforge.net/p/fmipp/

Example Application: Controlled Charging

20 08.10.2013

GridLAB-D as co-simulation master

Discrete event-based simulator as

co-simulation master

GridLAB-D’s core functionalities

deployed as master algorithm

EV model:

agent based behavior over time

(individual driving patterns)

energy demand due to the trip

charging station handling

Interface

plugin validated tools and

continuous models via

standardized interface (FMI &

FMI++, etc.)

21 08.10.2013

Traffic Pattern / Electric Vehicles (GridLAB-D)

Charging Station

EV

Charging Station

EV

EVEV

EV Pset

Pcharge

Pset

Pcharge

+ -

+ -+ -

Charge Control

Charge Control

PSAT (Octave)

Power system analysis

power flow to determine bus

voltages

Network model:

medium voltage network with

low voltage networks

load presenting household and

charging station

Interface:

Connect to GridLAB-D via

Octave API

+ thin wrapper to access C

arrays instead of data types

22 08.10.2013

4Diac / FORTE

23 08.10.2013

Distributed control system

IEC 61499 reference model for

distributed automation

Model / control

Local voltage control (anxilliary

service) keep voltage limits

Interface:

TCP/IP socket communication

(ASN.1 format)

suitable for embedded system

environments

OpenModelica

multi-domain (physics) simulation

language

supports event handling

acausal simulation (continuous

time-based simulation)

Model

Industry proofed library for a

detailed Li-Ion battery model

constant current / constant

voltage charger

Interface

plug-in continuous time-based

models via FMI++

24 08.10.2013

Co-Sim Power System, EVs, Components and Controls

Open source based approach of electric vehicle energy management for

voltage control

25 08.10.2013

Traffic Pattern / Electric Vehicles (GridLAB-D)

(OpenModelica)(OpenModelica)

Charging Station

EV

Charging Station

EV

EVEV

EV Pset

Pcharge

Power System Analysis

(PSAT/Octave)

Pset

Pcharge

+ -

+ -+ -

Battery Model

Battery Model

Charge Control

Charge Control

Uactual

Pcharge

Uactual, Pcharge

ASN1 (TCP/IP)

FMIFMI

AP

I In

terf

ace

Distributed Control System(4DIAC)

Results

Voltage during charging process

26 08.10.2013

Simulation time step varies with time due to updates of control algorithm

Results

Reduced charging power has

impact on battery’s SOC

Increased number of updates

controller notifies the simulation

core more frequently, thus

increasing the simulation step

resolution.

Investigate interesting dynamic

effects more precisely.

27 08.10.2013

Co-Sim Power System and Control

Electric Vehicle charge management for voltage control

28 10.10.2013

Battery Model(OpenModelica)Battery Model

(OpenModelica)

(GridLAB-D)

Charging Point Group

Charging Point Group

EVEV

battery model(OpenModelica)

charging point groupelectric vehicle

Pset

Pcharge

FMI

Pcharge,V

distribution grid(PowerFactory)

trip data

API

schedule ChargingManagement

battery charger

driving behaviour distributions(departure, duration, length)

ChargingManagement

chargingmanagement

charging point

sim

ula

tio

n c

on

tro

l

Pcharge,Pset

P. Palensky, E. Widl, A. Elsheikh, and M. Stifter, “Modeling intelligent energy systems: Lessons learned from a flexible-demand EV charging management,”

Smart Grids, IEEE Transactions on (accepted), 2013.

Co-Sim Power System, Components and Control System

Detailed battery model based on chemical equations + Energy management

Power Flow for every time step

29 10.10.2013

control system

PV system + inverter

SCADA

simulation results

power system

Co-Sim Power System with Electrical Energy Storage

Detailed battery model based on chemical equations + Energy management

Power Flow for every time step

30 10.10.2013

F. Andrén, M. Stifter, T. Strasser, and D. Burnier de Castro, “Framework for co-ordinated simulation of power networks and components in smart grids using

common communication protocols,” in IECON 2011 - 37th

Co-Sim Power System, Communication and Control

Co-Simulation with PowerFactory API: Loose Coupling via Message Bus

31 10.10.2013

M. Ralf, K. Friederich, F. Mario, and S. Matthias, “Loose coupling architecture for co-simulation of heterogeneous components – support of controller

prototyping for smart grid applications,” in submitted to IECON 2013 - 39th Annual Conference on IEEE Industrial Electronics Society, Vienna, Austria, 2013.

Electric Vehicle Simulation Environment

32 10.10.2013

33 10.10.2013

EV Simulation Environment

Mobility

Simulation

Power Grid

Simulation

CP & EV

Simulation

Scenario &

Use-Case

Results

traffic data

trip data

power demand

EVSim - Architecture

Architecture

Specification for the simulation scenario

EV + battery, plug types including efficiency (temperature, losses)

locations and charging points

distributed generation (location based)

34 10.10.2013

Power SystemPower SystemCharge ManagementTransportationSimulation

Charging PointSimulation

Charging Station

Agents / EventsAgents / Events

Charging Station

Electric Vehicle SimulationEVSim

EVEV

EV EV + -

EV + - Pset

PowerFactory

EV Charge Controller

PDG

Uactual

Charging Controller

SOC

Pcharge

EVSim - Functionality

Configuration

simulation time: start / stop / step-size / loop / real-time

temperature dependency / performance of the battery

Output (csv)

SOC, power

Interfacing / co-simulation

OPC

OCPP (Open Charge Point Protocol)

Behaviour

connection / disconnection handling, authorisation

time to plug / unplug

charging noise

Charging algorithm

G2V, V2G, matching with local generation

35 10.10.2013

EVSim – Parameters and Interface

Internal variables and parameters

36 10.10.2013

events, behavior

Pset

Emax

SOC, Eactual

plugtype

1/3 phase

SLA

Ewish

status

temperature profile

Pactual

Electric Vehicle

- battery capacity - battery Type - range ideal - range real - charge Pmax

- discharge Pmax

- reactive power Qmax,min

- charge efficiency - charge temp. perf. - battery performance - time of stay / leave

Charging Point

- group ID - location - plugtype / phases - active power Pact

- reactive power Qact

- current I1act,I2act,I3act

- voltage Ubus

- connection Status - time of connection - time of departure

Charge Controller

Optimize

Echarge=∑[Emax,Ewish]

Global or location based contraints:

Pactual(t)=[Pmin,Pmax]∑Pactual = Pgeneration

Umin < Uactual < Umax

SLA(EV)

Pset

Pmax, Pmin

SLA

RFID

SOC, Eactual

Ewish

Emax

Charging Group - Total Pactual

Pmax, Pmin

Pactual

Generation - Total Pgeneration

Pgeneration

Pactual

Uactual

agentsT

Validation of charging management

Real and simulated EVs for charging management validation

37 10.10.2013

Charge Controller

Real World

Electric Vehicle Simulation EnvironmentEVSim

Charging Station

EV

Data ExchangeInterface

(OPC)

Charging Station

Charging Station

EV

ECAR DVCharging

Management

DEMSDistributed

Energy Management

System

Charging Station

EV

EV

RenewableGeneration

0

50

100

150

200

250

300

350

400

450

500

550

06:0

0

06:3

0

07:0

0

07:3

0

08:0

0

08:3

0

09:0

0

09:3

0

10:0

0

10:3

0

11:0

0

11:3

0

Pow

er

[kW

]

time [hh:mm]

Tolerance rangePactPset

-40

-20

0

20

40

60

06:0

0

06:3

0

07:0

0

07:3

0

08:0

0

08:3

0

09:0

0

09:3

0

10:0

0

10:3

0

11:0

0

11:3

0

Pow

er

[kW

]

time [hh:mm]

Level Pset

ΔP

Tolerance range, Pset and Pact during simulation and deviation

Simulation of EVs and power system

Impact of unbalanced charging in low voltage networks

38 10.10.2013

Voltages a the charging point for symmetrical

loaded phases (3 times 3.68kW). Note the

voltage rise due to PV generation

1439,1151,863,576,288,0,00 [-]

222,66

221,82

220,97

220,13

219,28

218,44

DA61368_60240880: Leiter-Neutral Spannung, Betrag L1 in V



1439,1151,863,576,288,0,00 [-]

222,66

221,82

220,97

220,13

219,28

218,44




Voltages for unsymmetrical loaded phase (red:

11.04kW). Note the rise in the other phase

(green) due to neutral point displacement.

Temperature dependency

Region Lungau (Upper Austria) – approx. 6000 EVs

39 10.10.2013 Charging power for opportunity charging on a winter and summer day

Micro-simulation of region

Lungau, generating trip data

Simulation of EVs, control and power system

Local supply - demand match in medium voltage networks

40 10.10.2013

Uncontrolled and controlled charging of 306 EVs

with 11 kW during two sumer days.

Note: wind is accumulated on top of PV generation

0

100

200

300

400

500

600

700

800

00:0

0

04:0

0

08:0

0

12:0

0

16:0

0

20:0

0

00:0

0

04:0

0

08:0

0

12:0

0

16:0

0

20:0

0

Pow

er

[kW

]

time [hh:mm]

Generation from Wind

Generation from PV

Uncontrolled 11kW

Controlled 11kW; SOC-Level: 50%

Controlled 11kW; SOC-Level: 25%

Charging Mode

empty Evs

P-peak [kW]

Charged Energy [kWh]

DER Energy [kWh]

DER Coverage

[%]

uncontrolled 11kW

135 883 12613 3971 26%

controlled 11kW/SOC50

197 552 7267 3971 50%


218 353 5051 3971 71%

Charging Mode

empty EVs

P-peak [kW]

Charged Energy [kWh]

DER Energy [kWh]

DER Coverage

[%]

uncontrolled 11kW

15 751 9964 8079 54%


55 366 6832 8079 89%


66 324 6229 8079 99%

Two days simulation in winter

Two days simulation in summer

Summary

Multi-agent based simulation tool, time-continuous multi-physics

simulation, controls and power system simulation, e.g.:

GridLAB-D, OpenModelica, PSAT, 4Diac, PowerFactory

Open source software can be used for co-simulation environments

A number of interfaces possibilities exist to couple simulation tools.

Model and integrator based coupling can be realised.

Proprietary interfaces are light-weighted but not very general, not usable

for other tools, no simulation time step synchronisation

Functional Mockup Interface for model exchange + co-simulation.

41 08.10.2013

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