J. A. P. Lopes, "Smart EV grid interfaces responding to frequency variations to maximize renewable energy integration," in Electric Vehicle Integration into Modern Power Networks,

João A. Peças LopesINESC Porto / FEUP

([email protected])

Smart EV grid interfaces responding to frequency variations to maximize

renewable energy integration

EES-UETP Electric Vehicle Integration into Modern Power Networks

22 - 24 September 2010 Lyngby - Denmark

Introduction

Large scale deployment of EV

• Steady-state impacts related with voltage drops and branch overloads

Grid restrictions may limit the growth of EV penetration, if no additional measures are adopted. Solution:

Active management of EV batteries

• Dynamic issues EV participating in primary frequency control EV participating in AGC (secondary frequency control)

o

Introduction

• Renewable energies need to increase their penetration in the generation mix in order to reduce CO2 emissions

• There are renewable power sources characterized by some variability

• In isolated Grids if EVs participate in primary frequency control, major benefits to the integration of RES in large scale are expected

• When parked and plugged-in, EVs will either absorb energy (and store it) or provide electricity to the grid when (the V2G concept).

• Existing EV grid interfaces are passive devices that do not allow the required flexibility

The MERGE control concept

• A two level hierarchical control approach needs to be adopted:

• Local control housed at the EV grid interface, responding locally to grid frequency changes and voltage drops;

• Upper control level designed to deal with:• “short-term programmed” charging to deal with branch congestion,

voltage drops• Delivery of reserves (secondary frequency control);• Adjustments in charging acoording to the availability of power

resources (renewable sources).

EV Voltage / Frequency support modes

Voltage Control

Frequency Control

Local Control

Primary Control (local control)

Secondary Control

Coordinated Control

Conceptual Framework For EV Integration

• EV must be an active element within the power system

• The Upper Level control requires interactions with:

• An Aggregating entity to allow:

Reserve management Market negotiation

Ele

ctric

ity M

arke

t O

pera

tors

Delivery of Primary Reserve / Local Frequency ControlMethodology

Primary domain of application: Islanded grids (islands or networks operated in islanding conditions)

1. An isolated system has been characterized in terms of available generation and load. These components were modeled connected to a single bus system, where the several types of generation are then modeled individually together with the load.

2. A sudden change on wind power generation was simulated in order to assess its impact on the system’s frequency. Several scenarios were created for this purpose.

3. EV penetration was then characterized and the model for EV connections, featuring V2G, has been developed. This model was included in the single bus system and, finally, its effects on the system’s dynamic behaviour were evaluated running simulations in the same conditions as defined in 2.

Primary ReserveEV Electronic Grid Interface Modelling

• For frequency control the envisioned response from EVs is shown in the figure: When facing frequency deviations

EVs may slow down/speed up their charging or even inject active power into the grid

A dead band for battery premature exhaustion prevention is required

Prated MW/Hz proportional gain controls the reaction to frequency deviations

P

f

DeadBand

EV consumption

Pmax

Pmin

PInjection PConsumption

Droop control for EVs

V2G mode

• A PQ inverter control logic was adopted

• Set-points for active power controlled by a proportional gain that reacts to frequency deviations

actireacti

QP,

1sT1

Q

)ii(kvv ref* i,v i,v

PQ inverter control system

Control loop for EVs active power set-point

Primary ReserveEV Electronic Grid Interface Modelling

Primary ReserveEvaluation of the performance of grid

Case Study: small island normally fed from Diesel generation

Primary ReserveScenarios characterization

• Isolated system composed by: 4 diesel units 2 wind turbines (1 more for scenario

2) Mild PV penetration Load ranging from 1770kW to

4200kW

• Vehicles: 1 vehicle per household 2150 vehicles 323 (15%) EVs 3 EV types:

o 1xPHEV: 1.5kWo 2xEVs: 3kW and 6kWo Charging time: 4h

Scenario 1 Scenario 2

PTotal load (kW) 2172 2172

Pload (kW) 1770 1770

PEV load (kW) 402 402

PEV available (kW) 851 851

Pwind (kW) 900 1272

Psync1 (kW) 636 450

Psync2 (kW) 636 450

Scenario 1 Scenario 2

PDiesel1,2 (kW) 1500 1500

PDiesel3,4 (kW) 1800 1800

PWind (kW) 1320 1980

PPV (kW) 100 100

Installed power

Valley hour operation (load plus generation dispatch)

• Sudden shortfall on wind speed may jeopardize current power quality standards under EN 50.160 for isolated systems

• Large frequency excursions due to wind power changes become a limiting factor to the integration of Intermittent Renewable Energy Sources like wind power)

0 1 2 3 45

6

7

8

9

10

Time (s)

Win

d Sp

eed

(m/s

)

Disturbance applied to the case study

Primary ReserveScenarios characterization

• A single bus model of the system was developed using Matlab/Simulink: Wind speed suffers time domain

changes Electrical component and their links

in a steady state frequency domain model

• To each generation a dynamic model was assigned: diesel generator 4th order

model, with frequency regulation performed through conventional proportional and integral control loops

Wind generator simple induction machine

Isolated system single-line diagram

Primary ReserveGrid Modelling

0 1 2 3 4 5 6 7 8 9 1049

49.5

50

50.5

Time (s)

Syst

em F

requ

ency

(Hz)

0 1 2 3 4 5 6 7 8 9 100.5

1

1.5

2

2.5

3

Time (s)

P Die

sel (M

W)

0 1 2 3 4 5 6 7 8 9 10-0.5

0

0.5

1

1.5

Time (s)

P Win

d (MW

)

0 1 2 3 4 5 6 7 8 9 10-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

Time (s)

P EV (M

W)

PW = 1.3 MW; EV - charge mode

PW = 1.3 MW; EV - freq. control

Primary ReserveResults – Scenario 1

0 1 2 3 4 5 6 7 8 9 1049

49.5

50

50.5

Time (s)

Syst

em F

requ

ency

(Hz)

0 1 2 3 4 5 6 7 8 9 100.5

1

1.5

2

2.5

3

Time (s)

P Die

sel (M

W)

0 1 2 3 4 5 6 7 8 9 10-0.5

0

0.5

1

1.5

Time (s)

P Win

d (MW

)

0 1 2 3 4 5 6 7 8 9 10-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

Time (s)

P EV (M

W)

PW = 2.0 MW; EV - charge mode

PW = 2.0 MW; EV - freq. control

Primary ReserveResults – Scenario 2

• It is possible to verify that system dynamic performance was improved dramatically when EVs are participating in frequency control

• Further sensitivity analysis is still needed to identify the best control parameters for the droop control mode of the electronic grid interface used by the EVs

• The presence of a considerable amount of storage capability connected at the distribution level also allows the operation of isolated distribution grids with large amounts of IRES and/or microgeneration units connected to it

0 1 2 3 4 5 6 7 8 9 1049.3

49.4

49.5

49.6

49.7

49.8

49.9

50

50.1

50.2

50.3

Time (s)

Syst

em F

requ

ency

(Hz)

PW = 1.3 MW; EV - charge mode

PW = 1.3 MW; EV - freq. control

PW = 2.0 MW; EV - freq. control

Primary ReserveConclusions

17

Implementation of EV Grid Interfaces

Design Requirements Converter Functions

Grid physical connection

⁄Three-Phase

vSingle-Phase

►Three Leg Converter

Two Leg Converter

Battery charge+V2G capability

⁄AC/DC conversion

+DC/AC conversion

►

Rectifier+

Inverter

Grid “clean” interface ⁄ Low harmonic contentSmall displacement

factor

►Controlled Three Level Converter

Power Electronic Converter: The “Black Box” interface between the Low Voltage Grid (AC) and EV Battery (DC)

18

Implementation of EV Grid InterfacesPOWER CONVERTER – SINGLE & THREE PHASE TOPOLOGIES

Three-Phase, Three-level, Bidirectional Converter:

Power Convert

er

Matrix of switches

Power Convert

er

Time Variant Non-linear

System

19

Low Level Control:Closed loop control which outputs high frequency signals for each switch

Three‐Phase currents control : Sliding‐Mode Vectorial Control‐ Nearly sinusoidal phase currents = Low harmonic distortion‐ Currents in phase with voltages =  Small displacement factor‐ Static and dynamic phase current following‐ Capacitor voltage equalization‐ Robustness = immunity to disturbances

Grid/Battery charging current control: Proportional‐Integral external loop‐ “Current source” converter behaviour‐ Dynamic current following and near to zero static error

High Level Control:Defines a current reference to Low Level Control

Charge Control  Grid/battery requirements: charging current, end of charge, Minimum and maximum SOC levels …Droop‐control Grid frequency or voltage control: set‐point, dead‐band and slope

EV Grid Interfaces

20

EV Grid Interfaces

Charge Control: provides the charging current reference within the battery constraints

High Level Control: outputs the battery charging current reference for the Low Level Control

21

EV Grid Interfaces

Droop Control: outputs the droop charging current reference to the Charge Control

Reacts to Voltage and Frequency local deviations according to respective droop functions Central control units establish and communicate droop defining parameters

ChargingCurrent Reference

=

Frequency Droopor

Voltage Droop

within

output of

BatteryCharge

Constraints

22

Secondary frequency control

• Load variations or changes in generation output (namely from variable generation units) provoke load / generation imbalances that lead to:1. frequency changes and 2. inter-area power unbalances regarding scheduled power flows

• EV battery charging can be considered as very flexible loads, capable of providing fast reserves (through the aggregators)

• An increased robustness of operation can be achieved

• The reserve levels can be reduced (depending on the hour of the day, taking into account that the number of grid plugged vehicles)

Secondary ReserveAGC operation with EV• Modification of the active power set-points of generators and EV

• Some modifications need to be introduced in conventional AGC systems: redefinition of the partipation factors and introduction of an additional block to communicate with EV aggregators

• These control functionalities to be provided by EV are intended to keep the scheduled system frequency and established interchange with other areas within predefined limits, enabling further deployment of IRES

B

-KI/s

fp1

fpm

fpA1

fpAk

fi

Pif1

PifnPifREF

fi

++ -

+

+-

+

+ +-

k

i

m

i 1

inii

1

inii PaPe

ini1Pe

inimPe

ini1Pa

inikPa

Pref1

Prefm

Prefa1

Prefak

fREF

++

-+

+-

++

ACE

Aggregators

Secondary Reserve Evaluating the Contribution of EV for Secondary Frequency Control

• Definition of a case-study: Portugal /Spain (European interconnected system) Grid selection Modeling

• Setting up a contingency / disturbance

• Evaluating the system dynamic performance:Without the participation of EVWith the participation of EV

Secondary ReserveCase-Study – Definition

• 30% EV penetration 20% PHEV 1.5 kW 40% EV1 3 kW 40% EV2 6 kW

• EV load was following a smart charging scheme

Installed capacity

0

2

4

6

8

10

12

1 5 9 13 17 21

% o

f EV

Cha

rgin

g

Hours

Percentage of EV charging during a typical day, under a smart charging strategy (EV 30% of total fleet)

• Portuguese transmission/generation network, including existing tie lines with Spain (equivalent)• Technical constraints Portugal will not export more than 1500 MW or import more than 1400 MW

Secondary ReserveCase-Study – Definition

• Example of a windy day in the Portuguese system in the Autumn of 2009

Secondary ReserveCase-Study – Dynamic Modeling• Transmission system with 2 control areas (Portugal and Spain)

• 5 tie lines interconnecting areas 1 and 2 at 400 kV

• Generator equivalents per technology at each substation node: Conventional generator 4th order model synchronous machine

o Thermal units simple governor and a three stage thermal turbine with reheato Hydro units governor with transient droop compensation and a typical hydro turbineo IEEE type 1 voltage regulator was used

Wind generators 3rd order model squirrel cage simple induction machineo undervoltage relay setting 0.9 p.u.

• Voltage levels: 150 kV, 220 kV and 400 kV

• One AGC per area

Governor Turbine Synchronous Generator

R1

Pref(AGC signal)

Proportional Control

+-

+-

Pmec

PeCvopen

Cvclose

Pmecmax

0

Secondary ReserveCase-Study – Disturbance and Scenario Definition

• Event 300 ms fault at line 15-16• Impact of EV in the AGC operation:

1. EV are not used for AGC operation

2. EV are obtaining active power set-points from the AGC, through the aggregation units

C15H

C16TC2

H

C17N

W10

W11W2 W1

W4 W5

W7

400 kV150 kV

400 kV

220 kV

400 kV

150 kV

400 kV220 kV

400

kV22

0 kV

~

C1H

C3H

~ ~C4TG

W3

~

C7H~ W6

~C6H~C5

H

~

C8H

~

C9TG

W8

~

C12TC

~

C11TC

~

C14H

~ ~ ~

150 kV220 kV

~C10H

W9

~

C13TC

1

400

kV22

0 kV

211 10

1213

14 1516

17

18

19

22

21

23

8

7

2524 9

4 3

6 5

20

Control Area 1 Control Area 2

Equivalent Generator Types

~

~

C(TG): Conventional Gas

~

C(H): ConventionalHydro

~

C(TC):Conventional Fuel or Coal

N: Conventional Nuclear W: Wind

Simplified Portuguese Transmission Network

Winter valley period (6 a.M.)

Secondary ReserveResults – Interconnection active Power Flow

0 100 200 300 400 500 600 700 800 900-3500

-3000

-2500

-2000

-1500

-1000

-500

0

500

1000

Time (s)

P inte

rcon

nect

ion

(MW

)

With participation of EVWithout participation of EV

Reserve (MW)Used Reserve (MW)

t=2min t=15min

Hydro 461 461 461

Thermal 590 211 256

EV 0 0 0

Total 1049 672 717

Reserve (MW)Used Reserve (MW)

t=2min t=15min

Hydro 461 192 316

Thermal 590 31 74

EV 581 581 581

Total 1630 804 971

Reserve Used Without EV Participating in Secondary Control

Reserve Used With EV Participating in Secondary Control

Secondary ReserveResults – Used Reserve Levels

-10 -5 0 5 10 15 20 25 30

49.7

49.8

49.9

50

50.1

50.2

Time (s)

Freq

uenc

y (H

z)

With participation of EVWithout participation EV

Secondary ReserveResults – Frequency Evolution

0 20 40 60 80 100 120

0.35

0.4

0.45

0.5

0.55

0.6

0.65

0.7

0.75

Time (s)

I 16-1

8 (p.u

.)

With participation of EVWithout participation of EV

Secondary ReserveResults – Electrical Current in the Line 16-18

0 20 40 60 80 100 120

0.65

0.7

0.75

0.8

0.85

0.9

0.95

1

Time (s)

I 20-2

1 (p.u

.)

With participation of EVWithout participation of EV

Secondary ReserveResults – Electrical Current in the Line 20-21

Secondary ReserveResults – Area Control Error for Portugal

0 100 200 300 400 500 600 700 800 900-3000

-2000

-1000

0

1000

2000

3000

Time (s)

AC

E (M

W)

With participation of EVWithout participation of EV

• Three main conclusions that can be drawn from these studies:

1. Improvement of the system robustness of operation

2. Increase of the system reserve levels that can be effectively mobilized for secondary control use

3. Increase safe integration of renewable power sources in the system

• Fast reaction of EV + communication + control architecture = fast and effective AGC operation

• When EV are participating in secondary frequency control, further integration of IRES in interconnected grids is possible

• Additional economical and environmental benefits are expected from the adoption of EV smart control strategies, mainly due to avoided start-up of expensive and highly pollutant generation units that compose the tertiary control

• As a counterpart EV owners must be properly remunerated when participating in the provision of this type of ancillary services in order to make this concept efficient and with sufficient adherence

Secondary ReserveConclusions

Final Conclusions

• A specific EV grid interface needs to be adopted in order to allow EV to participate in the provision of ancillary reserve services;

• This on board device can be integrated with the EV battery management system

• The adoption of such control approach allows increased dynamic robustness of operation to the system

• Large penetration levels of renewable variable power generation are feasible, specially in isolated grids..