a methodology of conservation voltage reduction ... · 0.57-0.7 . 2010 ; epri . 0.8 ; the northwest...

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ECE ILLINOIS Hao Jan (Max) Liu Advisor: Prof. Hao Zhu

A Methodology of Conservation Voltage Reduction Performance Analysis Using Field Test Data

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ECE Main Slide

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

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90% of the home receive too much voltage. Typical Urban “Feeder” operates in upper half (120-126 V). This range ensure that all electric devices operate properly. PNNL: 4) When extrapolated to a national level, it can be seen that a complete deployment of CVR, 100% of distribution feeders, provides a 3.04% reduction in annual energy consumption. 5) If deployed only on high value distribution feeders, 40% of distribution feeders, the annual energy consumption is still reduced by 2.4%.

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

∆∆

=%%

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

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The load composition in the system is continuously varying and a complex function of customer behavior, temperature, time of day, time of week…etc. It is a major challenge for the utilities today to accurately determine the dependency of the system load on voltage. Pilot Demonstration projects controlled the voltage for 24 hours (On days) and then the normal utility voltage (uncontrolled) was applied for the next 24 hours (Off days), alternating back and forth for the duration of the project.

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

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The Northwest Energy Efficiency Alliance (NEEA) is an alliance of more than 100 Northwest utilities and energy efficiency organizations working on behalf of more than 12 million energy consumers.

Substation Power Demand Model

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emphasizing test/reference feeder each CVR test feeder has a corresponding reference feeder with similar load characteristics. The reference feeder has undergone no CVR testing, and hence its real power consumption could also be used to infer the test feeder power consumption as well.

Substation Power Demand Model

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What is known and what is unknown!

Least Absolute Shrinkage and Selection Operator (Lasso)

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0 controls the level of sparsity in the estimated solution. The OLS solution in (2) corresponds to the estimate in (3) when = 0, while the Lasso solution is all-zero for every parameter when ! 1. By varying the value from 1 down to 0, a Lasso solution path can be obtained with an increasing number of non-zero entries [11]. Hence, one additional benefit of the proposed framework is to rank the input variables in determining the output power demand. Take about using Lasso to select the variable and re-fitted to OLS

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%%

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=VoltageEnergyCVRf

69.010001.09.1800

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1 =×××

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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

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Lambda

Trace Plot of coefficients fit by Lasso

0 5 10 15-0.2

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Sample Autocorrelation Function

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The largest Lambda such that MSE is within one standard error of the minimum, a scalar The Lambda value with minimum MSE, a scalar

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

1

1 =×××

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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

a methodology of conservation voltage reduction ... · 0.57-0.7 . 2010 ; epri . 0.8 ; the northwest...

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