ARPA-E micro-Synchrophasor Project: Modeling and Validation

Emma Stewart, Chuck McParland & Sila Kiliccote

Grid Integration Group, LBNL February 21th 2014

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Acknowledgment: The information, data, or work presented herein was funded in part by the Advanced Research Projects Agency-Energy (ARPA-E), U.S. Department of Energy, under Award Number DE-AR0000340. Disclaimer: The information, data, or work presented herein was funded in part by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

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SCE: SONGS

•  Imbalance of supply and demand anticipated in southern California due to SONGS shutdown.

•  Focus on South of Lugo area served by SCE

•  Issues: SONGS off is N-1 –  System needs rebalanced

such that SONGS off is now N and the area can cope with N-1, N-2 and N-1-1

–  Currently SONGS + high load + outages could result in N-3 (very bad)

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PG&E Operations in Concord, California

Why is distribution “invisible”? •  It worked •  No major incidents to spur

change – most major outages have been caused by transmission

•  What could happen? –  Two way power flow –  Its becoming an active

resource –  No real insight into the impact

of changing power flows on transmission and distribution

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Review of Distribution Simulation Tools •  Review of distribution tools in general

–  Steady state, dynamic, transient packages •  Review of what are positive features for future software

development in distribution planning •  Comparison of available tools for application development such as

state estimation and dynamic device characterization •  Important other features

–  Interfaces with real time data –  Data input/output capabilities –  GUI’s

!

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Planning Tool Selection to Address Utility Concerns Issue   Timeframe   So.ware  op1ons   Opera1ons  Op1ons  FIDVR   Milliseconds,  sub-­‐cycle   None   Data  input  to  

opera:ons  

Dynamic  Load  Behavior   Similar  to  FIDVR   CymDist,  PSCAD,  DEW,  DigSilent    

Data  input  to  opera:ons  

Dynamic  Inverter  Behavior  

Milliseconds,  Seconds   CymDist,  PSCAD,  DEW,  DigSilent  

Network  model  representa:on    

Controllable  inverter  behavior  (Volt/Var)  

Seconds,  Minutes,  Hours  

CymDist,  DEW,  DigSilent  

Data  input  to  opera:ons  

Transient  switching  impacts  (microgrids  

Subcycle   PSCAD,  PSS/Sincal,  DigSilent  

Not  opera:on  issue  –  preventa:ve  in  planning  and  protec:on  analysis  

Load  flow  –  reverse  power,  voltage  profiles  etc  

Hours,  minutes,  steady  state  

CymDist,  DEW,  SynerGEE  Electric  

Data  input  to  opera:ons  

Protec:on  in  high  penetra:on  scenarios  

Milliseconds   DEW,  CymDist,  SyenrGEE  Electric  

Not  opera:onal  issue    

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Preliminary Modeling Tools Review Conclusions •  Preliminary observations from analysis of T&D modeling tools:

–  The existing models are not designed to simulate the operation of large numbers of distributed resources.

–  Model data standardization and validation is essential –  Highly variable PV systems must be analyzed in a detailed

dynamic and steady state simulation. –  As more detailed inverter control schemes become widely

available to customers, the impact must be justifiable and proven through simulation.

–  Availability of measured data is essential for validation and lacking in many cases.

–  No single software package can achieve all analysis objectives. •  Dynamic and steady state packages are advantageous together •  Transient can be separate

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µPMU Pilot Site Development at LBNL

•  Pilot site at LBNL for µPMU devices

•  Installing µPMU devices in 4 locations at LBNL – from substation to Building 90

•  Will measure high fidelity phase angle data, voltage and current to validate the LBNL CymDist Model

•  Challenges: communications, calibration, and commissioning

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LBNL Model Development & Analysis Plan •  Translated schematic from SKM and one-lines to CymDist

–  Converges with estimated load •  Enhancing substation model for feeder to bldg 90 •  Aggregate isolated unmeasured portions of lab distribution system •  Analysis plan

–  Validation and verification process against standard and uPMU angle data –  Baseline studies incluing load flow, fault current and long time step dynamics –  Advanced studies of potential application inc high renewable penetration,

transient impacts

BLDG 90

SW STA A6 FEED FROM GP

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Model Validation with Improved Data

•  We often model and assume distribution lines flow (top graph) and voltage is represented by the blue line

•  In reality it looks like the red line

•  Distribution model may have been constructed assuming traditional flow (all one direction)

•  Present and future needs more fidelity at line and phase level

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Distribution versus Transmission Validation •  Need for a proactive approach to distribution model validation

–  Transmission task force was in response to incidents –  Need to build a distribution system model validation process from

lessons learned in transmission •  Challenges:

–  Unbalanced non-symmetrical systems, harder to solve –  transmission assumption (R/X ratio not true) –  More components –  Dispersed load, many dynamic types –  Less measured data, time synchronization, more time series

changes •  Operations models in early stages of implementation

–  Create a process to validate planning and operations models concurrently

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Data Standardization •  CIM: Common Information

Model –  Defines the structure of data in a

logical model •  Originally for the exchange of

data between EMS and GIS –  Enabling the integration of

network models at both transmission and distribution levels

–  Expanded to include distribution extensions

•  Does not include all data required for increasingly complex analyses on distribution systems, but can be extended for use cases and further development

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Model Validation Process

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Analysis Plan for 20+ Feeders

•  Get models (SynerGEE, utility format) •  Determine issues of concern with utilities, obtain any

existing measured data – select tools to use for each utility •  Transfer model data to selected tools •  Validate models in measured condition •  Determine baseline conditions to perform for all models for

comparison •  Perform baseline analysis – load flow in varied load/gen

conditions •  Run key diagnostic issues on validated planned models •  Report on usefulness of data in planning models and

validation

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Summary •  Challenges In Modeling and Analysis

•  Data format from utilities •  Model, measured, other •  Transmission representation

•  Current issues in the distribution system •  Volume of unknowns •  Lack of control and visibility •  Inaccurate and un-validated modeling

•  There are big challenges in distribution systems simulation and analysis

•  Observability – if we cannot see a resource how can we get the most benefit from it?

•  Appropriate accurate analysis – validated models and using the correct tools and applications

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Thank You!

Sila Kiliccote Skiliccote@LBL.gov