ECE ILLINOIS Hao Jan (Max) Liu Advisor: Prof. Hao Zhu
A Methodology of Conservation Voltage Reduction Performance Analysis Using Field Test Data
Presentation Outline
Background and Motivation CVR Factor Sparse Linear Regression Based CVR Analysis CVR Analysis with Synthetic Data and Field Test Data Conclusion and Future Work
What is Conservation Voltage Reduction (CVR)?
CVR is a reduction of power demand (energy) resulting from a reduction of feeder voltage.
• Residential ZIP model on IEEE-13 node system
• Voltage is directly proportional to real power demand
• Most effective on constant impedance load
CVR vs. Energy
Energy Consumption as a function of applied voltage Chen, M.-S.; Shoults, R.; Fitzer, Jack; Songster, H., "The Effects of Reduced Voltages on the Efficiency of Electric Loads," Power Apparatus and Systems, IEEE Transactions on , vol.PAS-101, no.7, pp.2158,2166, July 1982 doi: 10.1109/TPAS.1982.317486
CVR Allowed ANSI Service Voltage Range: 114-126 V
http://wiki.powerdistributionresearch.com/index.php?title=File:Voltage_profile_distribution.jpg
Benefits of CVR
• Improve Energy Efficiency & Decrease Carbon Emissions • Peak Load Shaving • Improve System Reliability
– Extend Transformer Lives – Avoid Overload on Critical Circuits
• Lower the Energy Bill
CVR Factor
CVR factor is the metric to evaluating the effectiveness of CVR and a way to estimate energy reduction in the system
CVR factor varies with overall load composition and network topology; therefore, the average factors are highly varied
VoltageEnergyCVRf
∆∆
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Determining the CVR Factor
EPRI Green Circuit Project: Oneida-Madison Electric Cooperative, Upstate NY November/December 2011: CVR OFF from 11/10-11/30
CVR ON
CVR OFF
http://ieeerepc.org/past-conferences/2012-repc/files/2012/09/PDF-PPT-B-2-Triplett2012FINAL.pdf
CVR Factor Studies
Year Location CVR Factor
1991 Snohomish City 0.5-1.5
2006 MicroPlanet 0.8
2007 NEEA 0.57-0.7
2010 EPRI 0.8
Substation Power Demand Model
Substation Power Demand Model
Least Absolute Shrinkage and Selection Operator (Lasso)
Synthetic Data from OpenDSS • 13.8 kV Feeder with 0% and 1% Voltage
Reduction • 1.58 – 8.23 kW Loading • Pick Load Range from 2680 W to 2700 W
715.0100242030
1.1732%%
=×=∆∆
=VoltageEnergyCVRf
69.010001.09.1800
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Synthetic Data from OpenDSS Power Demand Range (kW) CVR Factor 2600 - 2620 0.6688 2620 - 2640 0.6967 2640 - 2680 0.6916 2680 - 2700 0.696 3000 - 3020 0.676
3433323130272117721df
10-4
10-2
100
-20
0
20
40
60
80
100
120
140
Lambda
Trace Plot of coefficients fit by Lasso
0 5 10 15-0.2
0
0.2
0.4
0.6
0.8
Lag
Sam
ple
Aut
ocor
rela
tion
Sample Autocorrelation Function
Synesthetic Data: Input Variables Ranking
Ranking Coefficient V 132.47 Hour 9 16.79 Hour 4 21.33 Hour 8 21.98 Hour 0 -10.31 Wednesday 15.28 Hour 15 13.53
Field Test Data CVR Analysis • 13.8 kV Feeder in Central Illinois • 3.5 – 15.4 kW Loading • Yearly Data on 0%, 2%, and 4%
Voltage Reduction Rank Variable Coeff. Rank Variable Coeff. 1 'Pref' 140.22 8 'Hour21' 5.23 2 'Fall' -39.17 9 'Hour9' -3.41 3 'Summer' 8.73 10 'Hour19' 4.84 4 'Hour12' -0.02 11 'Sunday' 4.35 5 'Temp' 5.05 12 'Hour22' 4.4 6 'Hour8' 4.19 13 ‘V' 2.71 7 'Hour20' 5.26 14 'Hour18' 3.66
43.010001.0333.0
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VCVRf
Conclusion and Future Work
Develop a methodology which determines the stochastic nature of the power system load and its dependency on several different factors.
Obtain the voltage sensitivity information and find the system CVR factor
Extend this work to a more flexible power demand model accounting the dependency of each individual variable via. Group Lasso Analysis
Q & A