Siemens Energy, Inc.
Power Technology
Issue 110
Smart Grid Offering Within PSS®SINCAL
Ulrike Sachs
®
PSS SINCAL Project Manager
ulrike.sachs@siemens.com
A fast growing sector in energy systems is the so called “Smart Grid” area where a tremendous change in
the networks can be seen. The term smart grid has different meanings for different entities, but overall
most would agree that smart grid deals with at least these three components:
 Intelligence in the transmission and distribution networks, such as automation and remote control,
intelligent meters, blackout prevention or condition monitoring
 Smart generation like distributed generation, energy storage, virtual power plants, wind or
photovoltaic generation, and decentralized energy management
 Smart consumption such as meter reading and remote meter controlling, load management, and new
tariff models.
All this changes the expectation the engineers have for network planning systems such as PSS®SINCAL.
PSS®SINCAL offers a full range of analysis methods, from standard load flow to enhanced dynamic
simulation for balanced and unbalanced networks, and deals with voltage levels from extra high voltage
to low voltage.
There are several ways that PSS®SINCAL greatly benefits utilities in modeling analysis and in network
operations.
Modeling
PSS®SINCAL offers the full range of network modeling including the unbalanced network structures and
new smart grid network elements (such as wind generation, PV cells, e-cars, etc.) for this first step in
network analysis.
Figure 1 – Icons of Elements Available in PSS®SINCAL
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January 2012
PSS®SINCAL is versatile – offering a full range of network modeling, including modeling of substation
models and heavily meshed networks that can be presented in synchronized schematic and topologic
form. These may be based on internet maps in Bing Maps or Cloudmade formats.
Figure 2 – Example of PSS®SINCAL Maps
Figure 3 - PSS®SINCAL – Network Displayed in Google Earth
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Figure 4 - PSS®SINCAL Networks and Results can be displayed in Google Earth
PSS®SINCAL supports the user in modeling all details from transposed systems for long lines in high
voltage down to specialized single or two-phase transformer models with specific wye point connections
for distribution networks. There is no need to transfer data between different planning tools, as
PSS®SINCAL allows the simulation of all necessary tasks within the same model. Of course, the
complexity of the element description differs. For instance, for smart grid elements – e.g., PV, batteries, ecars, wind, micro turbines – PSS®SINCAL models new technologies accurately in all simulation methods,
such as load flow, short circuit, harmonics, dynamics and protection simulation.
Figure 5 - PSS®SINCAL Modules – Electricity Networks
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Generation and load profiles, and dynamic data, can be associated with each smart grid equipment
model for long- and short term dynamic calculations. This also includes single-phase dynamic models for
synchronous and asynchronous machines and DC equipment (converter/inverter).
Figure 6 - Example of Smart Grid Network Element DC-Equipment Input Data
and the Presentation in the Network Including Interactive Diagrams
Simulation Requirements
After the user has inserted and validated the data in PSS®SINCAL, the next requirement is the algorithms
to correctly simulate the networks which include smart grid elements.
Due to the smart generation, the distribution networks change from passive to active networks having all
the problems of transmission networks, with the even more critical problem of low short circuit power and
simply no detailed knowledge of what is going on in the networks. Therefore there is no reduction allowed
in technical presentation of the distribution networks. Micro Grids demand even more automation and
control, as the link to the grid is not constantly available and the power management has to include
load/generation shedding – according to power limits of the generators or the voltage limits in the network
based on load/generator priorities. Generation has to control the voltages in the network by regulating the
power factor. Islanding of networks has to be supported and capacity transfer between generators up to
the power limits has to be supported as well.
Analysis Methods
In addition to new smart grid models and simulation requirements the analysis methods have to be
enhanced as the conclusions from the existing ones are no longer sufficient.
During the last 40 years network planning was based on load flow simulation. However, due to the new
realities of smart generation and consumption it is no longer reasonable to study one particular load flow
for a network, but instead at least the complete day (if not periods of months or years) needs to be
evaluated creating a load profile. This load profile showing load for every quarter of an hour enhances the
traditional load flow simulation in large load flow simulations. PSS®SINCAL fully supports load profiles.
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Figure 7 - Network with Load Profiles and Voltage Plot for a Specific Time Step during the Day
Load trimming algorithms (also known as feeder load estimation algorithms) have to take into
consideration the generation in the distribution networks and the minimum and maximum load situation.
To operate the networks in an optimized way algorithms are needed for optimal branching that lead to
recommendations for the SCADA systems. Harmonic studies have to take into consideration the voltage
disturbances by the DC equipment and the protection simulation has to handle overcurrent and distance
protection in the same networks with directional elements and voltage-dependent tripping. PSS®SINCAL
meets all these needs.
Support of Network Operations
In addition to the network planning the network operation planning is a task of increasing importance. This
means that information from the grid (smart meter values from consumption and generation, generator
data, and distribution equipment status) has to be transferred to PSS®SINCAL to provide a realistic
simulation of the existing network. Here PSS®SINCAL offers different options to link to meter data
management systems. All of the data is stored in an SQL database, therefore it is possible to pass
load/generation profiles together with the switching state of network devices to PSS®SINCAL, for example
via SQL or XML or even with Excel. In this case the network model and the load data will be taken from
the database while simulating the network.
Figure 8 - Architecture of MDM Integration (eMeter) in PSS®SINCAL
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Due to the fact that the number of elements with profiles is high and profiles can have many
measurements, this can lead to very large memory demand. A solution for this is using the Smart Load
Flow of PSS®SINCAL. In this case only the static network model will be read from the database while the
profiles are linked by COM-servers from SCADA and/or MDM systems on the fly directly during the
simulation.
Figure 9 - Smart Loadflow Interface to Meter Management System
Figure 10 - Embedded Meter Reading in PSS®SINCAL and Results from Smart Load Flow
The most advanced level of simulation for smart grids is the real-time evaluation of the network (for
distribution networks in general, this means a latency of 15 minutes) offering recommendations to the
network operation. This is based on steady-state but also on new stability simulation in low voltage
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systems. PSS®SINCAL can request a meter data reading on demand. The results of the load flow are
stored in the database and can be used to support network operation. PSS®SINCAL can enhance the
SCADA system by determining the state of the distribution network as the SCADA system currently does
not have insight into these network components.
Even for the dynamic (short term) simulation – both transient stability and EMT studies are needed. The
challenge here is the large number of components that have to be modeled with dynamic behavior in
three-phase and single phase, and the unbalanced network structure that needs special simulation
algorithms. This was done with EMT studies in the past, but PSS®SINCAL can now offer a new transient
stability method that also works in unbalanced networks. Models can be built using the graphical model
builder, or using existing models (for example from Matlab Simulink), if special measures have been
taken during the development of the model.
Figure 11 - Micro Grid with three Diesel Generators, Unbalanced and Meshed Network
and Results from Long Term and Short Term Dynamic Simulation
With these advanced features PSS®SINCAL enables engineers to more accurately model new Smart Grid
technology and gives them better insight into the distribution system. With this improved understanding
they can operate the system in an optimized way.
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