1. MIGRATING TOWARDS A SMART DISTRIBUTION GRID
Authors:
Prashanth DUVOOR
Ulrike SACHS
Satish NATTI
Siemens PTI

2. The needs in Network Planning will extremely change (1/2)
Past:
Only loads have been considered for distribution network planning
Information about maximum loads have based on measures in RMU and number of customers
Maximum loading of different equipment by diversity factors.
Today
Generation has to be considered.
Maximum utilization not definitely during peak load conditions
Voltage / power quality becomes a critical factor in future
Carsten Böse– Germany – Session 5 – Paper 0578

3. The needs in Network Planning will extremely change (2/2)
Future:
Data about consumption for each customer will be available (online/real-time)
Actual status of the network can be calculated based on measurements also in distribution networks.
Network operation and electronic components have to be taken into consideration
Distribution network become more and more active network.
New kind of loads are controllable (e.g. heat pumps, eCars, …)
 Power System Planning has to consider “copper” and IT
Carsten Böse– Germany – Session 5 – Paper 0578

4. Example: 314kWp PV Plant near Erlangen
Sunny day in April: 1,9 MWh
Cloudy day in April: 1,2 MWh
Carsten Böse– Germany – Session 5 – Paper 0578

5. Consideration of recorded loads and generation is the basis for future design
Meter Data Management Systems basis for load / generation model
meter data in 15 minutes intervals imported to PSS®SINCAL
Identification of critical situations by “dynamic” simulations
Carsten Böse– Germany – Session 5 – Paper 0578

6. Planning Tool considers DNA and DMS Energy Automation Portfolio
DSO IT
Renewables
Smart metering
Infrastructure and smart meters
System optimization measures based on meter data
Meter data management
Oil & Gas
Power Generation
Power Transmission
Storage
Distribution network
Management
Integration of DMS and OMS systems
Link-up of geo information (GIS) and workforce management (WFM)
Virtual power plant
Distribution
Industry
Distribution network automation
Smart feeder automation
Self-configuring substation automation
Energy Automation Portfolio
Carsten Böse– Germany – Session 5 – Paper 0578

7. Example Network
Feeder 1 has nearly 3 MW installed capacity of PV generation, and residential load.
Feeder 2 has a few PHEV charging stations, and residential load.
Feeder 3 has 1.8 MW installed capacity of wind generation, and commercial load.
Carsten Böse– Germany – Session 5 – Paper 0578

8. Advanced Distribution Network Analysis
Volt / var
Control
Whether
Forecast
Switching
Control
Load
Forecast
Power
Electronics
Controllable
Loads
Distributed
Generation
Demand
Response
Advanced Distribution Network Analysis including electrical
behavior and Distribution Management Systems algorithms
for pre- and post analysis
Carsten Böse– Germany – Session 5 – Paper 0578

9. Example: Loads
Carsten Böse– Germany – Session 5 – Paper 0578

10. Eample: Transformer Utilization
Carsten Böse– Germany – Session 5 – Paper 0578

11. Conclusions
Availability of online data import is crucial for precise evaluations of networks
Operational aspects have to be considered in future network planning
Power System analysis will identify new requirements for Distribution Network Automation (DNA) and Management (DMS)
Carsten Böse– Germany – Session 5 – Paper 0578