Grid Integration of PV Battery Systems with Forecast-Based

Operation Strategies

Johannes Weniger, Tjarko Tjaden, Volker Quaschning

HTW Berlin - University of Applied Sciences, Germany

28th European PV Solar Energy Conference and Exhibition,

30th September 2013, Paris, France

The project “PVprog” (11410 UEP II/2) is funded by the

Environmental Relief Program (UEP II) that is co-financed

by the European Union through the European Regional

Development Fund (ERDF) and the state of Berlin.

2

0 2 4 6 8 10 12 14 16 18 20 22 24

0

20

40

60

80

100

120

140

Pow

er in

GW

Hour of the day

200 GWp

140 GWp

70 GWp

35 GWp

Load

Installed PV capacity

Impact of PV on the electricity supply in Germany

Data: ENTSO-E (load), EEX (PV generation for the PV capacity of 35 GWp)

Sunday, 21/7/2013

3

Combining PV systems with storage batteries

PV generator

PV inverter

Loads

Control

unit

=

Charge regulator

and inverter

== M

PP

TA

CD

C

=

== B

AT

AC

DC

Circuit breaker

Battery

888.888

kWh Energy meter

Grid

4

Operation strategies of PV battery systems

Optimal local PV use

Reduced grid load

Forecast-based

Balancing capability

Battery charge

Grid feed-in Feed-in limit

●

Fixed feed-in limitation

Increasing self-consumption

●

●

●

Dynamic feed-in limitation

●

●

●

●

Dynamic feed-in limitation

●

5

0.3 0.4 0.5 0.6 0.7

0.0

0.5

1.0

1.5

2.0

2.5

7.5%

1%

25%

20%

15%

10%

5%

2.5%

0%

Maximum feed-in power in kW/kWp

Usable

batt

ery

capacity in k

Wh/k

Wp

0%

5%

10%

15%

20%

25%

30%

35%Annual curtailment losses

Sizing of PV battery systems for fixed feed-in limitation

Assumptions: no direct use of PV power by the load, complete discharge of the battery at night meteorological data: BSRN/DWD Lindenberg, Germany

6

Annual duration curve of the feed-in power

0 500 1000 1500 2000 2500 3000 3500 4000

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

PV system

PV system with self-consumption

PV battery system to increase self-consumption

PV battery system with fixed feed-in limitation

PV battery system with dynamic feed-in limitation

Number of hours in the year

Feed-i

n p

ow

er

in k

W/k

Wp

PV system size 4 kWp, usable battery capacity 4 kWh, annual load demand 4 MWh load data: VDI 4655, meteorological data: BSRN/DWD Lindenberg, Germany

7

Ramp rates of the feed-in power

100

101

102

103

104

105

-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

PV system

PV system with self-consumption

PV battery system to increase self-consumption

PV battery system with fixed feed-in limitation

PV battery system with dynamic feed-in limitation

Fre

quency o

f occure

nce p

er

year

Ramp rate of the feed-in power in kW/(kWp min)

PV system size 4 kWp, usable battery capacity 4 kWh, annual load demand 4 MWh load data: VDI 4655, meteorological data: BSRN/DWD Lindenberg, Germany

8

Conclusion

• By implementing forecasts of the PV power and load into the operation of PV battery systems, the self-consumption can be increased and the feed-in power can be reduced.

• With forecast-based operation strategies not only the peaks but also the ramps of the feed-in power are reduced.

• A dynamic feed-in limitation is also able to balance the feed-in profiles of existing PV systems.

• Decentralised battery systems can increase the hosting capacity of the electricity grid for PV systems.

• The conjunction of PV systems with batteries is of decisive importance to tap the whole PV potential.

pvspeicher.htw-berlin.de