ISO-NE Model Verification EE Team 2011 / CSE Team 10 EE: Cynthia - - PowerPoint PPT Presentation

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May 06, 2023 109 likes •426 views

ISO-NE Model Verification EE Team 2011 / CSE Team 10 EE: Cynthia Bissereth, Jonathan Davis, Ethan McRae CSE: Andrew Collins, Eric Flower, Sam Markelon Background Power system dynamic models to accurately represent BPS Current System:

SLIDE 1

ISO-NE Model Verification

EE Team 2011 / CSE Team 10

EE: Cynthia Bissereth, Jonathan Davis, Ethan McRae CSE: Andrew Collins, Eric Flower, Sam Markelon

SLIDE 2

Background

Power system dynamic models to accurately represent BPS
Current System: Automatic Power Plant Model Verification (APPMV) tool

○ Runs 24/7 ○ Gets event trigger, verifies event, runs PPMV, sends out results in email ○ Results are qualitative

Courtesy of ISO-NE

SLIDE 3

The Problem

Data not easily read
Comparisons are only quantitative

○ Engineers receive only graphs ○ Cannot do chronological comparison for a single plant ○ Data is not well-organized

No way to rank models

Courtesy of ISO-NE

SLIDE 4

Requirements

Augment current metrics

○ Make more readable representations

Manage, analyze, and quantify results automatically
Score and rank models

○ Highlight bad models ○ Provide automated ranking from quantitative comparison ○ Discuss alternative scoring methods ■ Current scoring metric ■ Root mean square error (RMSE) ■ Normalized root mean square error (NRMSE)

SLIDE 5

Solution

Approach

○ ECE Team designs scoring engine ○ CSE Team develops UI, DB, and implements engine

Webex meetings weekly

○ Whole team meeting ○ Present current work

SLIDE 6

Solution

Approach

○ ECE Team designs and implements scoring engine ○ CSE Team develops DB and web GUI ECE Team CSE Team

SLIDE 7

Solution/experiments/simulations

Scoring metric
RMSE
NRMSE

SLIDE 8

Scoring Algorithm

Weighted average of multiple signal metrics

○ Correlation coefficient ○ Similarity of phase magnitude ○ Similarity of phase angle

Implemented as a set of functions in MATLAB
Proposed by Dr. Rezaei and Dr. Venkatasubramanian in Quantitative Indicators

for Quality of Fit Assessment in Power System Model Validation Problems

SLIDE 9

Metrics Magnitude Correlation Angle

SLIDE 10

Magnitude Distance Semimetric

𝛽: sensitivity

SLIDE 11

Magnitude Distance Semimetric

SLIDE 12

Angle Distance Semimetric

𝛾: sensitivity

SLIDE 13

Angle Distance Semimetric

SLIDE 14

Semimetric Surface

SLIDE 15

Semimetric Tuning

Sensitivity parameter β

○Determines shape of semimetric

Formula relating β to angle cutoff
Allows for precise score

SLIDE 16

Semimetric Tuning

Cutoff percentage:5% Cutoff angle: 180 deg

SLIDE 17

Score

SLIDE 18

Score

SLIDE 19

Future Work

Further testing of MATLAB tfest() function

○ How accurate is the estimate? ○ Test with 2, 3, 4 poles on models and data

Frequency range

○ Range for integrating ○ Paper outlines 0 Hz to 1 Hz

SLIDE 20

MATLAB Results

SLIDE 21

Root Mean Square Error

SLIDE 22

Normalized Root Mean Square Error

SLIDE 23

Preliminary Results

SLIDE 24

Constraints

Unable to work in person, online/teleconference meetings only

SLIDE 25

Project management

No budget necessary

○ Everything online

Previous issue with file types resolved
Updated Gantt Chart on following slides

SLIDE 26

Gantt Chart: Phase 1: Project Introduction

SLIDE 27

Gantt Chart: Phase 2: Project Design

SLIDE 28

Gantt Chart: Phase 3: Project Implementation

SLIDE 29

Gantt Chart: Phase 4: Project Verification

SLIDE 30

Demo Day

Project needs

○ Laptop/computer to show working formula

Go through the solutions and simulations