control, energy management and protection for …control, energy management and protection for...

Prof. TRAN Q. Tuan

CEA-INES

Control, Energy Management and Protection for Microgrids:

Co-Simulation and Tests

5 – 8 Sept. 2017Montreal, Quebec, Canada

TRAN Q. Tuan – CEA-INES

PV systems integration into grids


Micro Grid at CEA-INES - Platform PRISMES


Challenges for Microgrids Control & Energy Management


Strategies of distributed control and management

• Rational use of components and infrastructure• Manage large number of components• Rational use of resources with cooperation

between components• More flexible system

CENTRALISED DISTRIBUTED

to

Objectives for Microgrids Control & Energy Management


Control & Management of Multi-level of grid

• Strategies of control and management forMicrogrid

• Strategies of control and management forMulti-Microgrids

• Strategies of control and management fordistribution grid

µgrid

µgrid

µgrid

Multi-µgrids Distribution grid

Multi-Agent system

Solutions for Microgrids Control & Energy Management


Distributed control in microgrid

Macsimjx Interface

Communication between agents

2 3 4 5 6 7 8 9 10 1149

49.5

50

50.5

51

Time(s)

Fre

quency(H

z)

System frequency

2 3 4 5 6 7 8 9 10 110

1

2

3

x 104

Time(s)

Active P

ow

er(

W)

Gen2 output

Gen4 output

Generator power

T.L Nguyen PhD Thesis


Agent Based Distributed Control of Islanded Microgrid– Real-Time Cyber-Physical Implementation

DG1 DG4

DG3

DG2

DG5

Load1

Load2

Agent1

Agent3

Agent2

Agent4

Agent5

Power

Control

Controller 1 Controller 4

Controller 3

Controller 5

Controller 2

Microgrid test case

DG controller diagram

Layer control structure



Loads

Hardware Agent

Source and

Controller

Source and

Controller

Source and

Controller

Source and

Controller

Hardware Agent

Hardware Agent

Hardware Agent

Hardware Agent

Source and

Controller

Communication network

Real time simulator

Hardware system

The testing setup

Web server interface

Aiomas_Agent 1

Aiomas_Agent 2

Aiomas_Agent 3

Aiomas_Agent 4

Hardware controllers and communication network

Data from web server sent to RPI clusterData from opal-rt sent to

web server

Optimal result from RPIsOptimal result

Aiomas_Agent 5

RPI4 RPI3

RPI5

RPI2

RPI1

Consensus processing



The transmission time in network

The consensus processing time The overall operation of MG


FMI Compliant Approach to Investigate the Impact of Communication to Islanded Microgrid Secondary Control

FMI (Function Mockup Interface): is a standard designed to provide an unified model execution interface for dynamic system models between modeling tools and simulation tools.

FMI compliant co-simulation approach to investigate the impact of communication system

General elements of a communication FMU

Pilot Support Package (PSP)

FMU block

An agent in Matlab/Simulink


FMI Compliant Approach to Investigate the Impact of Communication to Islanded Microgrid Secondary Control

DG4

DG3

DG5

Load1

Load2

Communication

Power

Control


Controller 3

Controller 5

Microgrid central controller

Controller 2

DG2

DG1

Centralized control

DG1

DG2

DG5

Load1

Load2

Agent1

Agent3

Agent2

Agent4

Agent5


Controller 3

Controller 5

Controller 2

Distributed control

Three communication test case from MGCC to LCs

The inter-agent latency time in the three test cases


Context and objectives:

A lot of different technologies for oceanenergy conversion are being developed.

Necessity to test the technologies on site (at sea), creation of marine test sites for demonstration and validation of Marine Renewable Energy Converters

Integration of these sites to the electric network: two major issues

Systems big enough to be connected to the grid.Intermittence and variability of the output powerprofile can cause damages to the grid

Example of a simulated output power profile over a year for a wave energy converter

Systems too small to be connected to theelectric grid via the offshore cable butoperationaldissipation and storage of the energyproduced

Experimental autonomous maritime platform for the study of marine energies and their integration into grid

H. Clemot PhD Thesis


Onshore prototype of a marine storage unit on a floating platform (Real Time Simulation platform)

Objectives:• Definition of the hardware architecture

for the platform• Development of the algorithms for

control• Study of power smoothing and energy

storage strategies for marine renewableenergy converters

• Determine the behavior of electric gridduring interactions with marinerenewable energy sources.

• Marine generator simulation• Grid simulation• Storage simulation or real system

storage

floating autonomous experimentation platform including power supply, dissipation system and grid simulator.


Power modules and ESSsupercapacitors

Test the power electronics interface and their control system Evaluate power quality at the point of conexion to the electrical grid Test different control and energy management strategies without or with energy storage systems



1 MW 5 MW



With storage


Real-time evaluation of Energy Management for a grid-connected Microgrid

BATTERY 1

BATTERY 2

BATTERY 3ESS

INVERTER

PV

INVERTER

EMSSERVER1

PVAS CONTROL PC

Ethernet

Modbus TCP/IP

SERVER2AC Electrical Grid

DC Electrical Grid

Modbus TCP/IP Communication Grid

Ethernet Communication Grid

E. Amicarelli PhD Thesis


Real-time evaluation of Energy Management for a grid-connected Microgrid: High Forecasted PV Power

without intra-day optimization

with intra-day optimization

Profiles of photovoltaic, battery, consumption and grid exchange


Microgrid of PRISMES platform (CEA/INES)

Load125 kVA

Load0 à 11 kW

Power

Communication

PC local control

PC remonte control

PV simulator

Inverter

Diesel Genset44 kVA

AC Bus

XtenderInverter

18 kW

Battery420 Ah/ 48V

Senarios:

PV system: 10 kWc

Max load: 17 kW

Min Load: 2.2 kW

P_Diesel: 20 kW

E_bat: 18 kWh

P_bat (charge): 6 kW

P_Bat (Dis.): -6 kW

Test time : 2h

Real time evaluation of Energy Management (EMS) for an Island Microgrid

G. Coukoi PhD Thesis


Power variation (Testing)Power variation (Simulation with dynamic programming)

Battery

Bidirectional

inverter

AC Bus

Load

Diesel generator PV array

inverter

˜=

EMS

800 1600 2400 3200 4000 4800 5600 6400 7200-5

0

5

10

15

20

Time [s]

Po

wer

[kW

]

PLOAD forecast

PPV forecast

PINV optimal

PDiesel optimal

PBatt optimal

800 1600 2400 3200 4000 4800 5600 6400 7200-10

-5

0

5

10

15

20

Time [s]

Po

wer

[kW

]

PLOAD measured

PPV measured

PINV measured

PDiesel measured

PBatt measured

It shows that test results are accorded with the simulation results



800 1600 2400 3200 4000 4800 5600 6400 7200226

227

228

229

230

231

232

233

234

235

Time [s]

Vo

ltag

e[V

]

V1 measured

V2 measured

V3 measured

800 1600 2400 3200 4000 4800 5600 6400 720049

49.5

50

50.5

51

Time [s]

Fre

qu

en

cy[H

z]

Frequency measured

After these tests, proposed

strategies are tranfered to

Brkina Faso

Frequency and voltages are maintained in limits



Objective:

CH12 – Vond

CH11 – IVP

CH10 – VVP

CH3 – Courant de commande de la source DC

VReseau

- Study behaviors of PV inverters face to faults in microgrid

- Validate the proposed solutions for protection

Test Bench

Scenarios: different faults on microgrid

Real time evaluation of microgrid protection


Fusible

FD1N2N3

N4 N5 N6 N7

10m 20m 20m 20m 10m

N8 N9 N10 N11 N12

20m 20m 20m 20m 10m

10m

10m

15m

5m

N13 N14 N15 N16

20m 20m 20m

N17 N18 N19 N20

20m 20m 20m20m20m

N21

N22

N23

N24

1

c

b

a

20/0.4

400kVA aaa

a a a

b b b b

b

bb

ccc

c c c

Fusible

FD2

PV

Fusible

FD1N2N3

N4 N5 N6 N7

10m 20m 20m 20m 10m

N8 N9 N10 N11 N12

20m 20m 20m 20m 10m

10m

10m

15m

5m

N13 N14 N15 N16

20m 20m 20m

N17 N18 N19 N20

20m 20m 20m20m20m

N21

N22

N23

N24

1

c

b

a

20/0.4

400kVA aaa

a a a

b b b b

b

bb

ccc

c c c

Fusible

FD2

PV

288.9 288.95 289 289.05 289.1 289.15 289.2-15

-10

-5

0

5

10

Temps (s)

Cou

rant

(A)

Instance of SC

disconnection

288.5 288.6 288.7 288.8 288.9 289 289.1 289.2 289.3 289.4 289.5

1000

2000

3000

4000

5000

6000

7000

Temps (s)

Cou

rant

(A)

Fuse current FD1

Instance of SC

Fuse FD1 activated

321.3 321.35 321.4 321.45 321.5 321.55 321.6

-10

-5

0

5

10

15

Temps (s)

Cou

rant

(A)

SC 1 (feeder with PV system) SC 2 (without PV system)

Validation par essai

Inverter current

PV Inverters are very sensitive face to faults

SC on the adjacent feeder can provide a non desirable disconnection

Inverter current



with the proposed solution

=> Non-desired disconnection is avoided

Solution: Using FRT characteristic (Fault Ride Through)

0.2 0.4 0.6 0.8 1 1.2 1.40

0.2

0.4

0.6

0.8

1

1.2

1.4

Time(s)

Vo

ltag

e(p

u)

Voltage-time Characteristic

Vpv without using the proposed solution

Vpv with using the proposed solution

Moment

de CC

Temporisation

du FD2

FD2 fond

Tens

ion

(pu)

Temps (s)

Gabarit de tension

Vpv sans utilisation du gabarit

Vpv avec utilisation du gabarit

0.2 0.4 0.6 0.8 1 1.2 1.40

0.2

0.4

0.6

0.8

1

1.2

1.4

Time(s)

Vo

ltag

e(p

u)




Moment

de CC

Temporisation

du FD2

FD2 fond

Tens

ion

(pu)

Temps (s)

Gabarit de tension



0.2 0.4 0.6 0.8 1 1.2 1.40

0.2

0.4

0.6

0.8

1

1.2

1.4

Time(s)

Vo

ltag

e(p

u)




Moment

de CC

Temporisation

du FD2

FD2 fond

Tens

ion

(pu)

Temps (s)

Gabarit de tension



0.2 0.4 0.6 0.8 1 1.2 1.40

0.2

0.4

0.6

0.8

1

1.2

1.4

Time(s)

Vo

ltag

e(p

u)




Moment

de CC

Temporisation

du FD2

FD2 fond

Tens

ion

(pu)

Temps (s)

Gabarit de tension



0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.80

0.2

0.4

0.6

0.8

1

1.2

1.4

Time (s)

Vo

ltag

e (p

u)

PV voltage

Classic Voltage/time Characteristique

New Voltage/time Characteristic

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.80

0.2

0.4

0.6

0.8

1

1.2

1.4

Time (s)

Vo

ltag

e (p

u)

PV voltage

Classic Voltage/time Characteristique

New Voltage/time Characteristic

Temps (s)

Tens

ion

(pu)

Tension du PV

Gabarit classique de tension

Nouveau gabarit de tension



The proposed co-simulation structure

Relays

Simulated network

MCR

Measurement

Control signal

Simulated microgrid

OpenIEC61850

Virtual Machine


Project: PV 50.2 Realized at CEA-INES in collaboration with RTE Context: for 200000 to 300000 PV inverters < 250 kW in France

What is their behavior face to degraded frequency? Is there the massive disconnection at 50.2 Hz (called "common mode“)? Do disconnections present a risk to the stability of the electrical network?

Objectives: Evaluate PV inverters behaviors in grid perturbations(frequency and voltage) by real time tests (OPAL-RT)

Works carried out: Developing methodologies for real time testing and creating the different scenarios by tacking into account

frequency/voltage uncertainty Real time testing for different PV inverters (Types of inverters: # manufac., size, mono or three phase…)

- Measure of the disconnection and reconnection threshold (frequency/voltage) of each inverter- Measure the disconnection and reconnection time of each inverter- Test the sensitivity of the inverters (operating power, rate of change of the frequency…)

Evaluate PV inverters behaviors in grid perturbations


Inverter

under test

=

~

PV

simulator

A

V

A

V

A

V

Generator of

I(V) curve

IMPP

VMPP I

AC

1

IAC

2

IAC

3

VA

C1

VA

C2

VAC

3

Network

model

Real time

simulater

OPAL-RT

Recording and

analyse

Measure and acquisition

+

-

L

1L

2L

3N

Simulation for different

power (irradiation)

Variation: frequency,

voltage, impedance…

VA

C1

VA

C2

VAC

3

IAC

1

f

5 Agilent 34410A: Measure

Description of the test bench


PV Simulator PV2 x 12 kWc900 V max

2 x 32A DC max

Controlable load125 kVA

Inverterunder test

AC bus5 DMM HP344101 Frequency1 Iac3 VacSwitch of Ethernet com.

3 Amplifies- 5kVA / +15 kVA

Real time simulatorOPAL-RT

Description of the test bench


Over-Frequency: Some tested inverters do not respect standards.

Under-Frequency: All tested inverters respect standards

Voltage: Some tested inverters do not respect standards.

No impact of the rate of change in frequency (verified with tests with different speed ramp) on the

disconnect frequency value

No impact of the operation power on disconnection / reconnection.

From disconnections based on frequency / voltage criterion of these PV inverters

=> RISK FOR NETWORK STABILITY!

Remarks

31

THANK YOU

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