© Fraunhofer IWES

12. Symposium Energieinnovation, 16.02.2012, Graz, Austria

Dr.-Ing. Jan Ringelstein

Division Engineering and Grid Integration

Fraunhofer IWES, Königstor 59, D-34119 Kassel

jan.ringelstein@iwes.fraunhofer.de

Impact of incentive-based demand response on urban low-voltage grid operation

© Fraunhofer IWES

Agenda

� Introduction and Project SHSG

� Considered grid area and software simulation

� Simulation Results

� Conclusions and further work

© Fraunhofer IWES

Public Power Corporation (PPC) S.A.

Industry

Fraunhofer Institute for Wind energy and energy

system technology

Institute of Com-munication and

Computer Systems

Research

Source: http://www.smarthouse-smartgrid.eu/index.php?id=147

SHSG Project Partners

© Fraunhofer IWES

Amalgamated smart grid architecture

Source: the SH/SG team, 2010

© Fraunhofer IWES

BEMI Coordination Algorithm Concept

Device Types

ISET-BEMI+® Functions~

=~

=

~=

~=

~

����

����

Gateway

Low-VoltageNetwork

CommunicationNetwork

Bidirectional Energy Management Interface

� Concept of decentralized decision

� based on central and decentralized information

© Fraunhofer IWES

Practical relevance of Simulations

� The final structure of the future smart grid is yet unknown

� Grid assets must be procured today for lifetimes of > 30 years

� The beginning energy system transition influences daily grid operation

Smart Grid simulations should…

� Allow for developing Smart Grid processes

� Assess applications of Energy Management Systems (EMS) in grid operation

� Quantify influence on grid operation parameters,

i.e. line loadings, voltages and line losses

� Provide a tool for grid operation and future grid design

� Allow for consideration of grid deconstruction scenarios

� Complement field tests and measurements

© Fraunhofer IWES

Simulation studies in SHSG WP4

A: ECN/TNO

�Study I: PowerMatcher improving integration of wind power generation

in a cluster of 3.000 Smart Houses.

�Study II: PowerMatcher impact on grid losses within a single LV feeder

B: IWES/MVV

�Impact of 300 Smart Houses equipped with BEMI

on grid operation parameters for three realistic LV grid topologies (MA-Wallstadt)

�MVV studied impact of DG within real LV networks in Mannheim, Offenbach, Kiel (voltages, line loadings)

C: ICCS/PPC

�Considering MAGIC application for island system operation (Crete)

�Study I: steady-state simulation considering load controller impact

on grid operation parameters (peak load, losses, CO2 emissions, cost)

�Study II: transient simulation in grid disturbance scenario (frequency stabilization)

© Fraunhofer IWES

Considered LV grid area, Mannheim - Wallstadt

Source: http://www.maps.google.de, 2011

© Fraunhofer IWES

Network for SH/SG Simulations

LV busbar with MV connection

LV busbar

1

5

2 3

6

A

C

B

7

100m/11PCC 150m/6 PCC 250m/2 PCC150m

4 PCC

210m

3 PCC

240m

3 PCC

260m

12 PCC

40m/1 PCC250m/18 PCC520m/41 PCC

240-460m

43 PCC

370m/17 PCC

4

100m

2 PCC

� 162 PCCs, 309 Households

� neighbour LV cell interconnections near nodes 1, 4 and 6

� Node 4 is subject to maximum voltage deviations

© Fraunhofer IWES

Network for SH/SG SimulationsConsidered topologies

LV busbar with MV connection

LV busbar

1

5

2 3

6

A

C

B

7

100m/11PCC 150m/6 PCC 250m/2 PCC150m

4 PCC

210m

3 PCC

240m

3 PCC

260m

12 PCC

40m/1 PCC250m/18 PCC520m/41 PCC

240-460m

43 PCC

370m/17 PCC

4

100m

2 PCC

Topology Nr. LV-LV connections LV-MV connection

1 All open All closed

2 All open B&C closed

3 All open A&C closed

© Fraunhofer IWES

IWES Simulation system as used for SH/SG

Module „BEMIVis“

Module „BEMISim“

Module „BEMI_DSIF“ Network simulation software DIgSILENT PowerFactory

Simulation Master

cSimMaster

Haushalte

cHousehold

HaushalteHouseholds

BEMIEnergy managemt.device switching

Customerrandom device

influencing

cBEMI cCustomer

DevicesFridges, Freezers,

Washing Machines,

unmanaged Loads,PV, CHP, ...

cSOC_Device, …

Sim

. data

netw

ork

Clie

nt S

erv

er

User interfaceParameters

Simulation controlData display during

simulation

Pool-BEMI

C/C++

C#

Sim

. data

netw

ork

Clie

nt S

erv

er

C++ DigSilent Programming Language (DPL)

LV network model3phased

Load-flowcalculation

DPLScript

Data exchangeActive/Reactive Power at

grid connection pointsNode voltages,

line loads, ...

Sim. data network

Client Server

ASCIIFiles

TCP/IPModule „BEMIVis“

Module „BEMISim“

Module „BEMI_DSIF“ Network simulation software DIgSILENT PowerFactory

Simulation Master

cSimMaster

Haushalte

cHousehold

HaushalteHouseholds

BEMIEnergy managemt.device switching

Customerrandom device

influencing

cBEMI cCustomer

DevicesFridges, Freezers,

Washing Machines,

unmanaged Loads,PV, CHP, ...

cSOC_Device, …

Sim

. data

netw

ork

Clie

nt S

erv

er

User interfaceParameters

Simulation controlData display during

simulation

Pool-BEMI

C/C++

C#

Sim

. data

netw

ork

Clie

nt S

erv

er

C++ DigSilent Programming Language (DPL)

LV network model3phased

Load-flowcalculation

DPLScript

Data exchangeActive/Reactive Power at

grid connection pointsNode voltages,

line loads, ...

Sim. data network

Client Server

ASCIIFiles

TCP/IP

© Fraunhofer IWES

Refrigerator

MaxOnTm 4800 sec +- 20 %

MaxOffTm 7200 sec +- 20 %

Freezer

MaxOnTm 3430 sec +- 40 %

MaxOffTm 8100 sec +- 30 %

SOC Model: Parameters used for SH/SG

© Fraunhofer IWES

SOC Model: Example

-20

0

20

40

60

80

100

120

Con

tent(g

rün) [%

], S

tor

(bla

u) [%

]

0 6 12 18 24 6 12 18 24 6 12 18 24

Stunden seit jew. Tagesbeginn

© Fraunhofer IWES

Load and Generation within the network

Distributed Generation

� peak generation of ~350 kWp

from PV installed at every PCC (evenly distributed)

� used PV irradiation measurements from Kassel (5 min resolution)

Load

� Peak consumption ~200 kW in grid area

� 3.300 kWh / a consumption per household

ApplicationRelativeconsumption

Absolute Consumption [kWh/a]

Fridges 11% 363

Freezers 11% 363

Washing Machines 7% 231

Dish Cleaners 7% 231

Tumble Dryers 10% 330

Non-controllable 54% 1.782

Sum 100% 3.300

© Fraunhofer IWES

� 6 days in June were simulated in each run

� 5 min simulation stepwidth

� Each run is done for a flat tariff and a PV tariff

� PV tariff designed for incentivizing load switch-on

during high PV infeed:

� three price groups à 103 households

� Price group 1: 15 ct/kWh 11:00-12:59, else 20 ct/kWh

� Price group 2: 15 ct/kWh 11:00-13:59, else 20 ct/kWh

� Price group 3: 15 ct/kWh 11:00-13:59, else 20 ct/kWh

� Repetition for each topology � 3 x 2 simulation runs

Simulation Runs

© Fraunhofer IWES

0 200 400 600 800 1000 1200 1400 1600 18000

50

100

150

200

250

300

350

Time [x5 min]

PV

(re

d);

Tota

l (b

lack),

SO

C (

blu

e)

and F

PS

load (

gre

en)

[kW

]

Example result topology 3: load and generation (flat tariff)

© Fraunhofer IWES

0 200 400 600 800 1000 1200 1400 1600 18000

50

100

150

200

250

300

350

Time [x5 min]

PV

(re

d);

Tota

l (b

lack),

SO

C (

blu

e)

and F

PS

load (

gre

en)

[kW

]

Example result topology 3: load and generation (PV tariff)

© Fraunhofer IWES

Example result topology 3: active power line losses (red: flat tariff, black: PV tariff)

© Fraunhofer IWES

103% Un

100% Un

Example result topology 3: voltage at node 4 (red: flat tariff, black: PV tariff)

© Fraunhofer IWES

Characteristic value Change

Imported energy avg. -3,7 %

Locally used PV energy avg. +3,7 %

Line losses -8 .. -9 %

Transformer losses appr. -1 %

Avg. Voltage node 4

during 11:00-14:00 -1 .. -1.8 V

else +0.1 .. +0.3 V

Avg. Line loading

during 11:00-14:00 -3.2 .. -6.2 %

else +0.1* .. +0.4 %

Avg. Transformer loading

during 11:00-14:00 -7.1 .. -9.7 %

else appr. +0.6 %

marginal effect due to restriced load

shifting potential and short low-price period

lower than ECN/TNO due to different loads

Note: tr. loss ~ lne. loss x 8 .. 2 (top. 1 .. 3)

Peaks reduced by 0.8 .. 1.4 V

Caused by load switch-off at HI-price times*

* Attribution to tariff effect uncertain

Causing increase of peaks by up to 1.2 %

Note: peaks are not occuring in this time

Causing increase of peaks by up to 2 %

Note: peaks are not occuring in this time

Result summary

© Fraunhofer IWES

Conclusions and further work

� Loadings and voltages are uncritical in any case

� PV tariff changing char. values as expected, but in some cases

merely marginal. Reasons: low LM potential, tariff design

� Significant reduction of line losses due to PV tariff design� Tariff design needs to be goal oriented

� Significant reduction of voltages, line & transformer loading

during LO-price times only

� Weaker grids benefit more from tariff effects

� Further Research: Model improvements, study other tariffdesigns, MV studies and practical applicability considerations

� The work continues in project „Modellstadt Mannheim“

© Fraunhofer IWES

SHSG project website

All publications and public final report at:

http://www.smarthouse-smartgrid.eu

© Fraunhofer IWES

Thank you for your attention!

Dr.-Ing. Jan RingelsteinFraunhofer IWES, Königstor 59, D-34119 Kassel,

Tel.: +49 561 7294 – 208, Email: jan.ringelstein@iwes.fraunhofer.de

This report is based on a research project partly funded by the EU FP7 project SmartHouse/SmartGrid (Grant no.: FP7-ICT-2007-224628).

The authors are responsible for the content of this publication.