Grid Integration of PV

1. © Fraunhofer ISE
GRID INTEGRATION OF PV
Dr.-Ing. Bernhard Wille-Haussmann
Fraunhofer Institute for Solar
Energy Systems ISE
6th PV Performance Modeling and
Monitoring Workshop
24th October 2016

2. © Fraunhofer ISE
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AGENDA
The Challenge
Solutions for grid integration
Grid planning with renewables
Conclusion

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What is the challenge for grid integration?
And its classical solution
 decreasing of line impedance ZL
voltage band violations thermal limitations
U1 ΔU
I I U2
ZL
U2 = U1 – ZLI  voltage decrease
U2 = U1 + ZLI  voltage increase
~
voltage
 Current lead to heating of cable
 Increase cross section of cable

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By pass
lines
Trafo
change
Additional
lines
OLTC
DSM
Q-
Control
Line
change
Existing
grid
Cost data
Cost optimal grid
Optimal grid expansion
Avoid grid reinforcement
Feed-in
restricti
on

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PV-Battery Systems
 Local self consumption of
electricity from PV
 Grid oriented operation
electricity
Operation of Local Systems
Electric thermal systems
 Thermal storages offer the
possibility to decouple thermal
and electric processes
CHP HP
electricity
What are services for the Smart Grid?

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Grid-friendly operation of PV battery systems
Feed-in peak
max. 60% PPV
Self consumption optimized
Grid friendly
 Self consumption optimization
does not avoid grid peaks
 Grid friendly operation: up to 66%
surplus PV can be installed.

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External Feed-in Reduction requests
Electricity grids are increasingly stressed
 Increasing feed-in of
fluctuating renewables
affects grids operation
 Feed-in management
becomes more important
 Decentralized feed-in of
renewables influences
dimensioning of electricity
grids.
This energy can be used better instead of shutting off.
source: EWE NETZ GmbH
Eisman-Einsätze
requests from outside
requests inside EWE NETZ

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Integration: reactive power control
 Voltage will be
stabilized by changing
the phase between
voltage and current.
 Increasing of inverter
nominal power
 Increasing of losses
 Reactive power control
is defined in grid
connection guidelines.

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Integration: voltage control with tap changer
 Usage of variable tap-changer at transformer
 Dynamic adaptation of voltage a point of connection
 Usage of the full voltage range
 No reduction of PV necessary.
source: Maschinenfabrik
Reinhausen

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The planning process of a local DSO
 Calculating grid
load
 Testing measures
 Economical
evaluation
Grid planningGIS System
 Data Export
 Import
changes
2
3
1

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Expected Development
 Decentralized production
Photovoltaic: 180 kWp
Combined heat: 0 kW
 Heat
Needed heat: 50 MWh
Heatpump 50 %
Storage per HP 3 h
 Electrical Storages
EV: 0
PV-batteries: 0 kWh
NEMO Use Case – Reference Ringkøbing
Step 1: Problem
PV Distribution
HP Distribution
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NEMO Use Case – Reference Ringkøbing
Step 2: Identifikation
Voltage Transformer load
 Heatpumps dominate
 Low voltages
 Winter: high trafo load by HP
 Summer: Inversed power flow
because of PV
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NEMO Use Case – Reference Ringkøbing
Step 3: Definition of possible solutions
Solution possibilities
 Grid reinforcement
 conventional
 OLTC
 Q-Control
 Intelligent Control
 Demand Side Management
 Local energy management
 grid friendly PV
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NEMO Use Case– Reference Ringkøbing
Step 4: Solution with convention reinforcement
Starting point Expansion
Conventional reinforcement
 Replace cables : 1,1 km NAYY 4x240
 Change transformer: 400 kVA
* 1km NAYY240 57.000€ (inkl. Verlegung)
Transformator 400 kVA: 9.000 €
2

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NEMO Use Case– Reference Ringkøbing
Step 5: Solution with Demand Side Management
Ausbau
Demand Side Management
 Reducing peak load : 220 kW  170 kW
 Replace cables: 0,3 km NAYY 4x240
 Change transformer: not necessary
Haushalt
Wärmepumpe
Photovoltaik
Haushalt
Wärmepumpe
Photovoltaik
Status Quo Demand Side Management
* 1km NAYY240 57.000€ (inkl. Verlegung)
Transformator 400 kVA: 9.000 €
2

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Conclusion
 Decentralized generation can lead to
 Violations of voltage bands
 Violation of thermal restriction
 Beside conventional reinforcement
 Energy Management
 Low voltage on load tap changers
 Reactive power control
Gird planning has become a multi
criteria optimization problem.

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Thank You!
Fraunhofer Institute for Solar Energy Systems ISE
Dr.-Ing. Bernhard Wille-Haussmann
www.ise.fraunhofer.de
bernhard.wille-haussmann@ise.fraunhofer.de