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Photos placed in horizontal position with even amount of white space between photos and header Sandia National Laboratories is a multi-program laboratory.

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Presentation on theme: "Photos placed in horizontal position with even amount of white space between photos and header Sandia National Laboratories is a multi-program laboratory."— Presentation transcript:

1 Photos placed in horizontal position with even amount of white space between photos and header Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL SAND NO XXXXP Model Validation for Large Scale PV Plants WECC REMTF Meeting, June 2014 Ryan Elliott, SNL

2 Context  Model validation is required  As part of new equipment model development/adoption  To comply with reliability standards  To increase accuracy and transparency in generator interconnection process  Treatment of PV and Wind in WECC Generating Facility Data, Testing and Model Validation Requirements  Wind & PV plant models must be validated against Reference Data (it can be field measurements, type test, manufacturer reference data)  Validation must address active/reactive power capability, active/reactive power controls, protection for different output conditions (e.g, partial output and full output) 2

3 Overview  Model validation for large scale PV plants using the 2 nd generation generic models developed by the REMTF  NERC MOD standards dictate that validated models must be submitted for all generators 75 MVA and greater  WECC policy is more strict and states that models must be submitted for generators 10 MVA and greater  Must be revalidated every 5 years  Developing MATLAB-based tools to help plant owners comply  The status of 2 nd gen PV models for large scale deployments  Thorough testing has been done to develop confidence in the generic models and identify implementation refinements 3

4 PV Model Structure  The value of the modular approach becomes apparent  The plant controller (REPC_A) and converter model (REGC_A) are employed for both wind and PV plants  The electrical control model (REEC_B) is different and slightly simpler for PV 4

5 One-line Diagram  PMU measurements are made at the substation level  The plant controller model takes measurements made at the plant level as inputs  The electrical control model requires local measurements made at the terminal bus (must infer from PMU data) 5

6 Components of a Validation Tool 1)Dynamic models that correspond well to commercial tools 2)Simple equivalent impedance model to reflect PMU measurements to the terminal bus 3)Parameter fitting algorithm using norm minimization as an objective (must be balanced with engineering judgment) 6

7 Inverter Level Validation Example  Bench test peformed on a 3-phase, 50kW PV inverter in a laboratory environment  Response to a symmetrical 75% voltage deviation  Simulated parameter fit reflects a manually tuned response because development of the validation tool is ongoing 7

8 Large PV Plant Example  PMU data collected from a transmission-connected PV plant  This fault is not ideal for model validation because of its long duration (greater than 0.5 seconds or 30+ cycles)  While not a perfect fit, it demonstrates the value of using PMU data for model validation 8

9 PV Electrical Control Model Testing 9  Designed a set of simulations which tested every possible control configuration for REEC_B (32 modes of operation)  Ran the simulations in both PSLF and MATLAB and compared the results (750+ simulations)  Helped develop confidence in MATLAB-based dynamic model implementation needed for model validation tool  Identified a couple of implementation improvements and worked with commercial software vendors to resolve them

10 Summary  Developing MATLAB-based software tools to enable semi- automated parameter fitting to measured response data  Tools are intended to provide guidance, but results must be verified in the commercial tool of your choice  A “good” parameter set should result in a close match under different disturbance conditions  Provided that the control mode and settings are fixed  Plant-level model validation using PMU measurements is constrained by the quality of the data  Disturbances must be large enough to be clearly discernible from measurement noise and unrelated perturbations  Thank you, questions and/or comments? 10


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