IEEE Workshop Microgrids · EPFL Lausanne| April 30, 2014 ... Advanced Training | Consulting Pre-incubation of Technology-based Companies IEEE Workshop Microgrids

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Clara Gouveia ( [email protected] )João Peças Lopes ([email protected])

Power Systems Unit - INESC TECEPFL Lausanne| April 30, 2014

Research and Technological Development | Technology Transfer and Valorisation | Advanced Training | ConsultingPre-incubation of Technology-based Companies

IEEE Workshop Microgrids

A Test Bed in a Laboratory Environment to Validate Islanding and Black Start Solutions for Microgrids

Outline

IEEE Workshop Microgrids: Evolution and Integration in modern power system2

1. MG as smart distribution cell

2. Smart Grids and EVs Laboratory

a) Main Objectives

b) Infrastructures

c) Control Functionalities

d) Experimental Tests

e) Conclusions

f) Future Work

The MG is a flexible, active and controllable LV system, incorporating: Microgeneration, Storage devices, Electric vehicles

3

1.MG as smart distribution cell

DMS

CAMC

LC

MGCC

Control Level 1

Control Level 2

Control Level 3

MCLoadSVC OLTCDG CVC VC

IEEE Workshop Microgrids: Evolution and Integration in modern power system

IEEE Workshop Microgrids: Evolution and Integration in modern power system 4

Ch

arg

ing

ra

teC

ha

rgin

g r

ate

Power

Reduce load

Reduce load

Voltages

Max

.

Min

.

Power

Increase load

Increase load

Technical challenges – Integrated management of EV and RES



Inovgrid reference architecture


6

The MG can be regarded as the cell of future Smart Grids:

Enhance the observability and controllability of power distribution systems.

Actively integrate electric vehicles and loads in the operation of the system.

Increase the connection capacities for different distributed generationtechnologies.

Promote the coordinated management of microgeneration, storage, electricvehicles and load, in order reduce system losses and improve power quality.

Provide self-healing capabilities to the distribution network, due to its ability ofoperating autonomously from the main grid and perform local service restorationstrategies.



1.MG as smart distribution cell –Emergency Operation


MG faces severe challenges during islanding operati on to maintain stability and quality of supply:

Inexistence of synchronous generation units -

the system is inertialess.

•Adoption of local control strategies compatible with the MG resources and power electronic devices:

Ensure voltage and frequency references.Provide voltage regulation.Provide frequency regulation, namely:

− Primary frequency regulation− Secondary frequency

regulation.− Load Control

Low X/R ratio and short-circuit power+

Unbalanced operation of LV network

•Possible degradation of power quality , due to the increase of voltage unbalance.

•Voltage unbalance causes: Decreases the life-time and efficiency of three-phase loads.Increases the system losses.Might compromise the MG synchronization with the MV network.

2. Smart Grids and Electric Vehicles Laboratorya) Main Objectives

8

Smart Grid Development and Testing

Power Systems

Power Electronics

ICT and cyber

security

Development and testing of prototypes

Development and testing of control devices and integrated management solutions based on Microgrid concept.

Testing communication solutions for smart metering infrastructures

Testing EV batteries control and management

Testing microgeneration control and management solutions

Testing Active Demand Response and home area networks

Developing and testing stationary storage and its control solutions for Smart Grids



2. Smart Grids and Electric Vehicles Laboratoryb) Infrastructure

Storage

Advanced metering and communication infrastructure

Electric Mobility

128 Lithium battery cells 25 kWh capacity Flooded Lead-Acid (FLA) and

Sunny Islands inverters 3kW wind micro-turbine and 15 kWp PV panels

Microgeneration

Electric infrastructure:

Renewable based microgeneration

Storage

Resistive load bank – 54 kW

LV cables emulators (50 A and 100 A)

Plug-in electric vehicles – Renault Fluenze ZE andtwizy

Microgeneration and EV power electronic interfaces

Electric panel, command and measuring equipment

10

3 kW wind micro-turbine

15 kWp photovoltaic panels

25 kWh capacity Flooded Lead-Acid (FLA) 128 Lithium battery cells




Commercial DC/AC microgeneration inverters


The two 25 kW FLA battery bank are connected totwo three-phase groups of grid forming inverters –SMA Sunny Island inverters, enabling: Testing MG islanding operation. The inverters provide the voltage and frequency

reference to the isolated system, based on P-fand Q-V droops.

The PV and wind turbine emulator can be coupled tothe network through: Six DC/AC SMA Sunny Boy Inverters with 1.7/ 2

kW nominal power. DC /AC SMA Windy Boy Inverter with 1.7 kW

nominal power.The main objective is to explore the microgenerationcommercial solutions and study potential limitations.

10 15 20 25 30 35 40 45 50

5

10

15

20

25

30

35

Time(s)

Act

ive

pow

er (

kW)

Pref

= 18 kW

Pref

= 24 kW

Pref

= 30 kW

12

Controllable microgeneration emulator - 4 quadrant A C/DC/AC inverter

The laboratory is equipped with a 20 kWthree-phase AC/DC/AC custom-made four-quadrant inverter.

The inverter power is controlled in order toemulate the response of controllable powersources such as Single-Shaft Microturbines orFuel Cells.

Enable the development and test of newfrequency and voltage control strategies, inorder to provide grid support duringemergency conditions:- Microgrid islanded operation.- Microgrid restoration procedure.



13

DC/AC microgeneration prototypes

Solar DC/AC inverter prototype

Wind DC/AC inverter prototype



DC/AC microgeneration prototypes

Main functionalities:

Single-phase DC/AC inverters.

Solar inverter with MPPT power adjustment.

Active power control for voltage grid support.

Bidirectional communication with the MGCC.

Possibility of remote control.

Experimental Objectives:

Development and test of new voltage control strategies, in order to providegrid support.

Integration of the new prototypes with the microgrid control andmanagement architecture.

14



15

Microgeneration grid supporting functionalities

Microgeneration prototypes are locallycontrolled through active power – voltagedroop:

- Provide voltage support to the LVnetwork due to low X/R ratio.

- Avoids microgeneration overvoltagetripping.

Control Rule:

Voltage within pre-defined limits

Voltage rises above the dead-band

Voltage drops below the dead-band

The unit maintains its reference power

Automatic reduction of the injected power

Automatic increase of power(limited to the maximum power thatcan be extracted from the primarysource)

2. Smart Grids and Electric Vehicles Laboratoryc) Control Functionalities


16

Bidirectional EV charger prototype

A 3.6 kW single-phase bidirectionalDC/AC inverter prototype isconnected to a lithium batterybank.

The charging rate can becontrolled in order to provide gridsupporting functionalities.

Smart charging and V2Gcapabilities.

Bi-directional communication withthe MGCC.

Possibility of remote control.



17

EV grid supporting functionalities

The EV bidirectional charger prototype islocally controlled in terms of active power:

- Provide voltage support to the LVnetwork due to low X/R ratio.

- Participate in the MG frequencyregulation in emergency conditions.

Control Rule:

Voltage/ Frequency within deadband

Voltage / Frequency rises abovethe dead band

Voltage / Frequency drops belowthe dead band

The EV maintains its reference chargingpowerAutomatic increase of the EV chargingpower

Autonomous decrease of the EV chargingpower or even power injection to the grid– V2G.

2. Smart Grids and Electric Vehicles Laboratoryc) Control Functionalities


18

Electric panel - Command and data acquisition infras tructure

Six 400 V busbars and thirty feeders commanded through contactors. Busbars interconnecting switches. Feeders equipped with a metering equipment. SCADA system to support the laboratory operation and monitoring.



Mic

roG

rid

1M

icro

grid

2

19

MG control and communication architecture



20

Test system configuration:

Two PV strings connected to a DC/AC solar power converter prototype.

The wind-turbine emulator. EV charger prototype. 52 kW resistive bank. MG node is interconnected to

the main grid through a 100A LV cable emulator, which has a 0.6 Ω resistance.

20 kW four quadrant AC/DC/AC inverter

Experimental tests:

Interconnected mode of operation – Test voltage regulation strategies.

2. Smart Grids and Electric Vehicles Laboratoryd) Experimental tests


21

Interconnected Mode of Operation



PV EV WT 4Q

20 40 60 80 100 120 140 160 180 200-8

-6

-4

-2

0

2

4

Act

ive

Pow

er (k

W)

Time (s)

1 2 3 4 5 6 7

Node 3 Node 4

20 40 60 80 100 120 140 160 180 200230

240

250

260

Vol

tage

L-N

(V

)

Time (s)

1 2 3 4 5 6 7

•High integration of µG at off-peak hours may cause overvoltage problems (1-5).

•Adopting droop based strategies enables local active power control in order to reduce voltage in problematic nodes (2,4-5).

•Coordination between µG and EV is achieved through droop strategies also avoiding wasting RE (6,7).

22

Interconnected Mode of Operation



Node 3 Node 4

200 250 300 350190

200

210

220

230

240

250

260

Vol

tage

L-N

(V)

Time (s)

8 9 10

PV EV WT 4Q CL1 CL2

200 250 300 350

-6

-3

0

3

6

9

12

15

18

Act

ive

Pow

er (k

W)

Time (s)

8 9 10

•EV may also contribute to avoid undervoltage problems through P-V droop strategy (9,10)

•For larger voltage disturbances the EV storage capacity can also contribute to ensure adequate voltage levels (10).

23

Test system configuration:

Two PV strings connected to a DC/AC solar power converter prototype.

The wind-turbine emulator. EV charger prototype. 52 kW resistive load bank. MG node is interconnected to

the main grid through a 100A LV cable emulator, which has a 0.6 Ω resistance.

Four quadrant AC/DC/AC inverter

Experimental tests:

Islanded mode of operation – Test frequency regulation strategies:

– Primary frequency control– Secondary frequency control– Load Control



24

Islanded Mode of Operation


MG frequency and EV active power response during MG islanding


Frequency -With P-f droop Frequency - Without P-f droop

-10.5

-7.5

-4.5

-1.5

1.5

4.5

Act

ive

Pow

er(k

W)

50 75 100 12548.2

49.2

50.2

51.2

52.2

53.2

Time (s)

Freq

uenc

y (H

z)

Active Power - With P-f droop

Active Power - Without P-f droop

Freq

uen

cy (

Hz)

Act

ive

Pow

er (

kW)

EV participation on primary

frequency control

Contributes to reduce frequency excursions

25

Implementation of Central Secondary control strateg y



• Runs at the MGCC• Coordination PQ and VSI µG

inverters.

∆=∆

×∆=∆

=

∑=

PPMS

fpPPR

Rfp

n

ii

iMS

ii

i

1

Power set-points determined based on reserve capacity (R)

26

Islanded Mode of Operation – MG storage response to secondary frequency control


With Secondary Control Without Secondary Control

49.5

49.75

50

50.25

50.5

Fre

quen

cy (

Hz)

100 150 200 250 300 350-15

-10

-5

0

5

10

15

Time (s)

Act

ive

Pow

er (

kW)

a)

b)


27

Implementation of coordinated emergency load contro l



Characterize the MG operating state

Determine the severity of the disturbance

Determine the amount of load to shed

Evaluate the MG security during islanded operation

The algorithm determines:• MG storage capacity• Microgeneration reserve capacity• Imported/ Exported power

Power unbalance resulting from:

unbalanceshed PRP −=∆

In case the MG does not have enough reserve capacity, the algorithm activates selective load shedding scheme

The algorithm evaluates:• MG has enough storage

capacity to support the disturbance.

• If frequency remains within admissible limits

Temporary load

shedding


28

60 70 80 90 100 110 120

-10

-5

0

5

10

15

Time (s)

Act

ive

Pow

er (

kW)

Islanded VSI SSMT Total load

Frequency based load shedding MGCC enables partial load reconnection

MGCC enables Secondary control

VSI power dead-band


60 70 80 90 100 110 12048.8

49

49.2

49.4

49.6

49.8

50

50.2

Time (s)

Fre

quen

cy (

Hz)

IslandedBase CaseCase 1Case 2


29

60 70 80 90 100 110 12048.8

49

49.2

49.4

49.6

49.8

50

50.2

Time (s)

Fre

quen

cy (

Hz)

IslandedBase CaseCase 1Case 2

Simulation results

Experimental Results

Frequency based load shedding

MGCC enables partial load reconnection



MG Blackstart

The procedure is constituted by the following steps:

1. MG status determination

2. MG preparation

3. MG energization

4. Synchronization of the running MS to the MG

5. Connection of EV

6. Coordinated reconnection of loads and non-controllable MS

7. Enable EV charging

8. MG synchronization with the main grid


31

BlackStart Procedure – MG frequency



Frequency - With P-f droop Frequency - Without P-f droop

-2

-1

0

1

2

Act

ive

Pow

er(k

W)

0 50 100 150 200 250 30049.6

49.8

50

50.2

50.4

Time (s)

Fre

quen

cy (

Hz)

4 6 7 8

0 50 100 150 200 250-2

-1.5

-1

-0.5

0

0.5

1

1.5

Time (s)

Act

ive

Pow

er (

kW)

With P-f droop Without P-f droop

32

BlackStart Procedure – EV power response



5 6 7 8

The Smart Grids and EV laboratory plays a key role in theconsolidation of innovative solutions for the development of microgridconcept :

Development of microgeneration and EV grid-coupling inverter prototypesincorporating innovative control strategies.

Local control strategies provide to system operators additional operationresources , in order to deal with the crescent integration of DER resources andEV.

Local control strategies are also complemented by advanced MG controllers to beinstalled at the consumers premises – the Energy Box and at the MV/LVsubstations, the MGCC. The coordination of microgeneration and EV charging increases the system

efficiency, while maintaining voltage within admissible limits. The participation of EV in the MG frequency regulation can reduce the

unbalance between the generation and load within the islanded system. Higher control levels will be responsible for coordinating the devices installed in the

field: Loads, EV, microgeneration and storage.

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2. Smart Grids and Electric Vehicles Laboratorye ) Conclusions


Conceptualization of innovative SCADA / DMS systems for low-level gridcontrol, based on Microgrid management and control functionalities.

Development and testing of active demand side management solutionsinvolving the definition of in house functionalities, ancillary services provisionand remuneration schemes.

34

2. Smart Grids and Electric Vehicles Laboratoryf ) Future Work


Smart Grid Development and Testing

Power Systems

Power Electronics

ICT and cyber

security

Development and testing of Microgeneration, DG andEV control and management tools.

Development of advanced forecasting tools forEV and PV based microgeneration.

Developing and testing stationary storageand its control solutions for Smart Grids

Documents

IEEE Workshop Microgrids · EPFL Lausanne| April 30, 2014 ... Advanced Training | Consulting Pre-incubation of Technology-based Companies IEEE Workshop Microgrids