A Test Bed in a Laboratory ... - Microgrid Symposiumsmicrogrid-symposiums.org/wp-content/uploads/2015/...A Test Bed in a Laboratory Environment to Validate Islanding and Black Start

From

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To S

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on

Clara Gouveia ([email protected]) Carlos Moreira ([email protected])

João Peças Lopes ([email protected]) Centre for Power and Energy Systems - INESC TEC

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

Aalborg 2015 Symposium on Microgrids

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

Outline

2

1.  MG as smart distribution cell

2.  Validation of MG operation concepts

3.  Smart Grids and EVs Laboratory

a)  Main Objectives

b)  Infrastructures

c)  Control Functionalities

d)  Experimental Tests

e)  Conclusions

f)  Future Work

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

3

Storage Device

MV

LV

MGCC

Wind Generator

Microturbine

Fuel Cell

PV Panel

Load Controller (LC)

Vehicle Controller (VC)

MicroGrid Central Controller (MGCC)

Microgeneration Controller (MC)

Load

EV EV

EV

EV

1.MG as smart distribution cell

DMS

CAMC

LC

MGCC

Control Level 1

Control Level 2

Control Level 3

MCLoadSVC OLTCDG CVC VC

4

Charging ra

te

Charging ra

te

Power

Reduce load

Reduce load

Voltages

Max

.

Min

.

Power

Increase load

Increase load

}  Technical challenges – Integrated management of EV and RES


5

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 generation technologies.

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

§  Provide self-healing capabilities to the distribution network, due to its ability of operating autonomously from the main grid and perform local service restoration strategies.


1.MG as smart distribution cell – Emergency Operation

6

MG faces severe challenges during islanding operation 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.

7

}  Microgrid and More microgrid European projects }  Main goals and achievements:

}  increase the penetration of RES and other micro-sources in order to contribute for the reduction of GHG emissions.

}  Development and demonstration of MicroGrids and Multi-Microgrids operation, control, protection, safety and telecommunication infrastructures.

}  To study the main issues regarding the operation of MicroGrids in parallel with the mains and in islanding conditions that may follow faults.

}  To identify the needs and develop the telecommunication infrastructures and communication protocols required.

}  InovGrid Project }  Main goals and achievements:

}  Definition of the reference model and specifications of smart metering infrastructure for the Portuguese utility - EDP Distribution.

}  Development of advanced functionalities such as coordinated voltage control, blackstart strategies using Distributed Generation, definition of new requirements for system protection and Medium voltage automatic reconfiguration capability.

}  Development of strategies to evaluate the potential costs and benefits of deploying the Multi-MicroGrid concept using multi-criteria decision aid methods.

2.Validation of MG operation concepts

8


}  Inovgrid reference architecture – Smart Grid Portuguese Demonstrator

9

}  Merge - Mobile Energy Resources in Grids of Electricity (FP7 funded project) }  Main goals and achievements:

}  Development of a management and control concept that will facilitate the actual transition from conventional to EV.

}  Identify potential smart control approaches to allow the deployment of EV without major changes in the existing network and power system infrastructures.

}  To identify the most appropriate ways to include EV into electricity markets through the smart metering infrastructure.

}  To provide quantitative results on the impact of integrating EV into the grid of EU national power systems.

}  To provide computational suite able to identify and quantify the benefits that a progressive deployment of the MERGE concept will bring to the EU national power systems, taking into account several possible smart control approaches.


10

}  REIVE – Smart Grids With Electric Vehicles (Portuguese funding – Innovation Fund from the Ministry of economics)

}  Main goals and achievements: }  Study, develop and test of technical solutions and pre-industrial prototypes for

the active and intelligent management of electricity grids with large scale integration of microgeneration and electric vehicles.

}  Develop a technical platform which: }  is able to identify and quantify the benefits of a progressive deployment of EV and

microgeneration technologies. }  includes innovative control solutions for microgeneration and EV systems.

}  Development of a laboratorial infrastructure – The MG and EV laboratory.

}  Support industrial partners in order to deploy the technologies and products resulting from the concepts and prototypes developed.

}  To propose a regulatory framework capable of: }  integrating EV users in a fair and non-discriminatory way, }  deal with the additional investments in the network control and management structures in

order to reliably accommodate a large number of EV.


3. Smart Grids and Electric Vehicles Laboratory a) Main Objectives

11

Smart Grid Development and Testing

Power Systems

Power Electronics

ICT and cyber

security

Ø  Development and testing of prototypes

Ø  Development and testing of control devices and integrated management solutions

Ø  Development of tests of communication solutions for smart metering infrastructures

Ø  Testing EV batteries control and management

Ø  Testing microgeneration control and management solutions

Ø  Testing Active Demand Response and home area networks

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

12

3. Smart Grids and Electric Vehicles Laboratory b) 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 and

twizy §  Microgeneration and EV power electronic interfaces §  Electric panel, command and measuring equipment

13

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

14

The two 25 kW FLA battery bank are connected to two 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-f and Q-V droops.

The PV and wind turbine emulator can be coupled to the network through: §  Three DC/AC SMA Sunny Boy Inverters with 1.7

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

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

10 15 20 25 30 35 40 45 50

5

10

15

20

25

30

35

Time(s)A

ctiv

e po

wer

(kW

)

Pref= 18 kWPref= 24 kWPref= 30 kW

15

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

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

§  The inverter power is controlled in order to emulate the response of controllable power sources such as Single-Shaft Microturbines or Fuel Cells.

§  Enable the development and test of new frequency and voltage control strategies, in order to provide grid support during emergency conditions: -  Microgrid islanded operation. -  Microgrid restoration procedure.


16

DC/AC microgeneration prototypes

Solar DC/AC inverter prototype

Wind DC/AC inverter prototype


DC/AC microgeneration prototypes Main functionalities:

Ø  Single-phase DC/AC inverters. Ø  Solar inverter with MPPT power adjustment. Ø  Active power control for voltage grid support. Ø  Bi-directional communication with the MGCC.

Ø  Possibility of remote control. Experimental Objectives: Ø  Development and Test of new voltage control strategies, in order to provide

grid support. Ø  Integration of the new prototypes with the smart grid control and

management architecture.

17


18

Bidirectional EV charger prototype

§  A 3.6 kW single-phase bi-directional DC/AC inverter prototype is connected to the lithium battery bank.

§  The charging rate can be controlled in order to provide grid supporting functionalities.

§  Smart charging and V2G capabilities.

§  Bi-directional communication with the MGCC.

§  Possibility of remote control.


19

Electric panel - Command and data acquisition infrastructure

§  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.


20

MG control and communication architecture

SCADA

PC-‐uATX

PC-‐uATX

MC

GUI

PC-‐uATX

GUIVC

PC-‐uATX

GUI

LC SM

PC

DM&CS

MGCC

PC-‐uATX

PC-‐uATX

MC

GUI

PC-‐uATX

GUIVC

PC-‐uATX

GUI

LC SM

PC

Metering

Electric pannel Control

System Configuration and Parametrization

Database

Modbus RS-‐485

TCP-‐IP

LoadsGUIMGCC GUI


21

Microgeneration grid supporting functionalities §  Microgeneration prototypes are locally

controlled through active power – voltage droop:

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

-  Avoids microgeneration overvoltage tripping.

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 that can be extracted from the primary source)

Pmax

Deadband

P

ΔV

Pref

ΔV maxΔV min

3. Smart Grids and Electric Vehicles Laboratory c) Control Functionalities

22

EV grid supporting functionalities §  The EV bidirectional charger prototype is

locally controlled in terms of active power:

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

-  Part icipate in the MG frequency regulation in emergency conditions.

Pmax

Deadband

P

∆V

Pmin

∆V max

∆V min

V2G Smart Charging

Pref

∆V0

Control Rule: §  Voltage/ Frequency within dead-

band

§  Voltage / Frequency rises above the dead-band

§  Voltage / Frequency drops below the dead-band

The EV maintains its reference charging power Automatic increase of the EV charging power Autonomous decrease of the EV charging power or even power injection to the grid – V2G.

3. Smart Grids and Electric Vehicles Laboratory c) Control Functionalities

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 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.

3. Smart Grids and Electric Vehicles Laboratory d) Experimental tests

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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).

25

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

-6-30 3 6 9 121518

Acti

ve P

ower

(kW

)

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).

26

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.

§  Four quadrant AC/DC/AC inverter

Experimental tests:

§  Islanded mode of operation – Test frequency regulation strategies:

–  Primary frequency control –  Secondary frequency control –  Load Control


27

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 droopActive Power - Without P-f droop

Freq

uenc

y (H

z)

Act

ive

Pow

er (

kW)

EV participation on primary

frequency control

Contributes to reduce frequency excursions

28

Implementation of Central Secondary control strategy


•  Runs at the MGCC •  Coordination PQ and VSI µG

inverters.

⎪⎪⎪

⎩

⎪⎪⎪

⎨

⎧

Δ=Δ

×Δ=Δ

=

∑=

PPMS

fpPPRR

fp

n

ii

iMS

ii

i

1

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

29

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 Fr

eque

ncy

(Hz)

100 150 200 250 300 350-15

-10

-5

0

5

10

15

Time (s)

Act

ive

Pow

er (k

W)

a)

b)

30

Implementation of coordinated emergency load control


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 −=Δ

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


31

60 70 80 90 100 110 120-10

-5

0

5

10

15

Time (s)

Act

ive

Pow

er (k

W)

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)

Freq

uenc

y (H

z)

IslandedBase CaseCase 1Case 2


32

60 70 80 90 100 110 12048.8

49

49.2

49.4

49.6

49.8

50

50.2

Time (s)

Freq

uenc

y (H

z)

IslandedBase CaseCase 1Case 2

Simulation results

Experimental Results

Frequency based load shedding

MGCC enables partial load reconnection

33

Ø  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


34

BlackStart Procedure – MG frequency


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

0 50 100 150 200 250 30049.6

49.8

50

50.2

50.4

Time (s)

Freq

uenc

y (H

z)

4 6 7 8

0 50 100 150 200 250-2

-1.5

-1

-0.5

0

0.5

1

1.5

Time (s)

Activ

e Pow

er (k

W)

With P-f droop Without P-f droop

35

BlackStart Procedure – EV power response


5 6 7 8

Ø MG voltage regulation capabilities Ø  P-V droop strategy is able to maintain the voltage within admissible limits,

avoiding overvoltage tripping of the microgeneration units.

Ø  When having more than one microgeneration unit controlled with P-V droop, they are able to share the voltage disturbance without relying in complex communication infrastructures.

Ø  The coordination of microgeneration and EV charging increases the system efficiency, while maintaining voltage within admissible limits.

Ø  From the consumers perspective it will reduce its power consumption and maximize the use of its microgeneration installed capacity.

Ø MG frequency regulation capability Ø  The participation of EV in the MG frequency regulation can reduce the unbalance

between the generation and load within the islanded system.

Ø  This will enable a more efficient management of the MG storage capacity.

36

3. Smart Grids and Electric Vehicles Laboratory e ) Conclusions

Ø  The industrial development of smart grid related products enhances the importance of experimental demonstration facilities.

Ø  The MG and EV laboratory plays a key role in the consolidation of innovative solutions for the development of smart grid:

Ø  Development of microgeneration and EV grid-coupling inverter prototypes incorporating innovative control strategies.

Ø  Local control strategies provide to system operators additional operation resources, in order to deal with the crescent integration of DER resources and EV.

Ø  Local control strategies are also complemented by advanced MG controllers to be installed at the consumers premises – the Energy Box and at the MV/LV substations, the MGCC.

Ø  Higher control levels will be responsible for coordinating the devices installed in the field: Loads, EV, microgeneration and storage.

37

3. Smart Grids and Electric Vehicles Laboratory e ) Conclusions

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

Ø  Development and testing of active demand side management solutions involving the definition of in house functionalities, ancillary services provision and remuneration schemes.

38

3. Smart Grids and Electric Vehicles Laboratory f ) Future Work

Smart Grid Development and Testing

Power Systems

Power Electronics

ICT and cyber

security

Ø  Development and testing of Microgeneration, DG and EV control and management tools.

Ø  Development of advanced forecasting tools for EV and PV based microgeneration.

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

Documents

A Test Bed in a Laboratory ... - Microgrid Symposiumsmicrogrid-symposiums.org/wp-content/uploads/2015/...A Test Bed in a Laboratory Environment to Validate Islanding and Black Start