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DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
23 J���, 2016
H���������������L���C������������ �� D�����������G��� ��� D����� R�������19th P���� S������ C���������� C��������� (PSCC)G����, I����
S���� R������G�����1, S. C����������������2, R. H. J�������1,E. M. S������3, J. M������ D������4 ���M. W�����3
1Aarhus University, Denmark2Massachuse�s Institute of Technology, USA3Lawrence Berkeley National Laboratory, USA4Universidad Pontificia Comillas, Spain
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
O������
1 Introduction
2 Co-simulation with Hardware-in-the-Loop
3 Case Studies
4 Conclusions
H�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 2 / 14
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
O������
1 Introduction
2 Co-simulation with Hardware-in-the-Loop
3 Case Studies
4 Conclusions
H�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 3 / 14
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
M���������� High penetration of renewables (42% of the
consumption in Denmark in 2015 from windturbines)
� Flexibility required for generation-consumptionbalancing
� Demand response as a solution⌅ Help renewables integration⌅ Create market opportunities at distribution level
� Need tools for comprehensive assessment of newdemand response opportunities
Source: Energinet.dk (2015)H�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 3 / 14
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
M���������� High penetration of renewables (42% of the
consumption in Denmark in 2015 from windturbines)
� Flexibility required for generation-consumptionbalancing
� Demand response as a solution⌅ Help renewables integration⌅ Create market opportunities at distribution level
� Need tools for comprehensive assessment of newdemand response opportunities
Source: Energinet.dk (2015)H�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 3 / 14
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
C������������ E����������Virtual Grid Integration Laboratory (VirGIL)
FMI FMI
FMIFMI
Master Algorithm
Ptolemy IICommunication
Networks SimulatorOMNet++ FMU
Control ModelsSimulator
Modelica FMU
Building ModelsSimulator
Modelica, EnergyPlusFMU
Power Systems SimulatorPowerFactory
FMU
FMI standard: Functional Mockup InterfacePtolemy II (actor-oriented simulation so�ware)
Source: Chatzivasileiadis et al. (2016)H�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 4 / 14
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
C�����������
FMI
Hardware inthe Loop
Ptolemy II
FMI
FMIFMI
Ptolemy II
Master Algorithm
Ptolemy IICommunication
Networks SimulatorOMNet++ FMU
Control ModelsSimulator
Modelica FMU
Building ModelsSimulator
Modelica, EnergyPlusFMU
Power Systems SimulatorPower Factory
FMU
Extension
Coupling of co-simulation environment (VirGIL) with aHardware-in-the-Loop (HiL) infrastructure, ventilation sy-stem of large building, for demand response assessment
H�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 5 / 14
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
T��� B��: G������� D�������� L��
� Student residence in Aarhus (Denmark)� 12 floors, 159 apartments, 200 students� 3,400 sensors (5 s resolution)
⌅ indoor climate conditions⌅ electricity consumption⌅ domestic water⌅ district heating⌅ others
Source: www.vpp4sgr.dkH�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 6 / 14
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
O������
1 Introduction
2 Co-simulation with Hardware-in-the-Loop
3 Case Studies
4 Conclusions
H�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 7 / 14
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
C��S��������� ���� H�L � C��� S����
Grundfos Dormitory Lab
Distribution GridModel
Curtailment Service Provider
Ext
erna
l Dat
a P
rovi
ders
H�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 7 / 14
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
C��S��������� ���� H�L � C��� S����
Grundfos Dormitory Lab
Distribution GridModel
historical nodes load
PowerFactory
Curtailment Service Provider
Optimization & Control
node loads, line loads...
Ptolemy II
Exte
rnal
Dat
a P
rovi
ders
electricity price,wind speed...
H�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 7 / 14
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
C��S��������� ���� H�L � C��� S����
Grundfos Dormitory Lab
OpenADR Client
OpenADR Server DR shed
DR capability,fan load, DR yes/no
OMNeT++
Distribution GridModel
historical nodes load
PowerFactory
Curtailment Service Provider
Optimization E Control
DR shedfan load
node loads, line loads...
Ptolemy II
Exte
rnal
Dat
a P
rovi
ders
electricity price,wind speed...
H�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 7 / 14
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
C��S��������� ���� H�L � C��� S����
Controller
Ventilation Fans Model
Indoor CO2 Model
Grundfos Dormitory Lab
airflow
static pressure
OpenADR Client
external CO2
DR capability
fan load
indoor CO2 generation
DRshed
OpenADR Server DR shed
DR capability,fan load, DR yes/no
OMNeT++
+
historical apartments load
all buildingloadDistribution Grid
Model
historical nodes load
PowerFactory
Curtailment Service Provider
Optimization z Control
DR shedfan load
node loads, line loads...
Ptolemy II
fan load
Exte
rnal
Dat
a P
rovi
ders
electricity price,wind speed...
HiL
H�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 7 / 14
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
D����������� G���M��������� PowerFactory (integrated
in VirGIL via FMI standard)� Grid data provided by DSO� Test bed electricity
consumption from sensors� Assumptions:
⌅ 3 times more densearea
⌅ all buildings similarpower consumption
H�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 8 / 14
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
H���������������L��� C��������� Ventilation fans interaction
Secured API (HTTP-Modbus)Controller Air Handling Unit API
HTTPS POST (SupplyFanPressure)
HTTPS POST (ExhaustFanPressure)
HTTPS 201
HTTPS GET (SupplyFanPower)
HTTPS GET (ExhaustFanPower)
HTTPS GET (Airflow)
HTTPS GET (SupplyFanPressure)
HTTPS 201
HTTPS 200
HTTPS 200
HTTPS 200
HTTPS 200
HTTPS GET (ExhaustFanPower)
HTTPS 200
� CO2 sensor data: MongoDB query in Ptolemy IISource: Rotger-Griful et al. (2016)
H�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 9 / 14
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
O���� C���������� Communications Networks
⌅ OMNet++⌅ Demand response protocol: OpenADR
� Demand response controller:⌅ Ptolemy II⌅ Multiple control strategies
� Master algorithm⌅ Ptolemy II
� Prior execution time analysis⌅ simulation time < real time
H�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 10 / 14
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
O������
1 Introduction
2 Co-simulation with Hardware-in-the-Loop
3 Case Studies
4 Conclusions
H�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 11 / 14
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
L��� F�������� ��� O������ RES I����������� Strategy: 1-minute load reference based on measured
on-site wind speed
� Observations:⌅ Building CO2 level OK⌅ Capable of following signal
H�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 11 / 14
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
A�������� S������� � P������ R�������� Strategy: Primary reserves for up-regulation! reduce
consumption
� Observations:⌅ Inner fan controller limits response time⌅ Aggregation required for market participation (� 300
systems)H�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 12 / 14
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
L��� A���������� ���� L��� F��������� Strategy: 15 ventilation systems following 1-minute varying
reference (white noise added)
� Observations:⌅ 2% transformer load change in few seconds⌅ Communication protocol e�ect (tuning time between
polling events)H�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 13 / 14
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
O������
1 Introduction
2 Co-simulation with Hardware-in-the-Loop
3 Case Studies
4 Conclusions
H�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 14 / 14
Introduction Co-simulation with HiL Case Studies Conclusions
DEPARTMENT OF ENGINEERING
AARHUS UNIVERSITY AU
C����������� Propose co-simulation with Hardware-in-the-Loop (HiL) to
support demand response development� Extend the VirGIL co-simulation platform with HiL of
ventilation system� Proposed HiL approach can be deployed to other systems� Case studies:
⌅ Ventilation system can respond to fast demandresponse requests
⌅ Ancillary services regulations should reduceparticipation barriers for demand response resources
⌅ Communication protocol parameters can a�ect theloading of power components
H�L C������������ ��� D����� R������� S���� R������G����� 23 J���, 2016 14 / 14