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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-AC04-94AL85000. SAND NO. 2011-XXXXP

Model Validation for Large Scale PV PlantsWECC REMTF Meeting, June 2014

Ryan Elliott, SNL

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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)

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Overview

Model validation for large scale PV plants using the 2nd 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 2nd gen PV models for large scale deployments Thorough testing has been done to develop confidence in the generic

models and identify implementation refinements

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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

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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)

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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)

𝑍 𝑠𝑢𝑏 𝑍 𝑐𝑜𝑙 𝑍 𝑔𝑠𝑢

𝑌2

𝑌2

𝑆𝑝𝑣𝑆𝑔𝑟𝑖𝑑

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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

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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

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PV Electrical Control Model Testing 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

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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?