Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze...

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Distribution Distribution Transformer Size Transformer Size Optimization by Optimization by Forecasting Customer Forecasting Customer Electricity Load Electricity Load Jarrod Luze Jarrod Luze Black Hills Power Black Hills Power Rapid City, South Dakota Rapid City, South Dakota

Transcript of Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze...

Page 1: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

Distribution Transformer Distribution Transformer Size Optimization by Size Optimization by

Forecasting Customer Forecasting Customer Electricity LoadElectricity Load

Jarrod LuzeJarrod Luze

Black Hills PowerBlack Hills Power

Rapid City, South DakotaRapid City, South Dakota

Page 2: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

IntroductionIntroduction

Electric utilities face common challenges Electric utilities face common challenges determining transformer sizes.determining transformer sizes.

Study consists of 960 three phase pad-Study consists of 960 three phase pad-mounted transformers.mounted transformers.• Research and categorization of existing Research and categorization of existing

transformerstransformers• Ideal vs. actual benefit/cost analysisIdeal vs. actual benefit/cost analysis• Forecasting future customer power demandForecasting future customer power demand

Page 3: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

Study of Existing Transformers in ServiceStudy of Existing Transformers in Service

Compared kVA name-plate rating to peak Compared kVA name-plate rating to peak demand of customerdemand of customer

‘‘R+_’ signifies that a transformer is R+_’ signifies that a transformer is undersized and would ideally require a undersized and would ideally require a larger transformer for the load.larger transformer for the load.

‘‘R-_’ signifies the transformer is under-R-_’ signifies the transformer is under-loaded, and a smaller transformer would loaded, and a smaller transformer would suffice. suffice.

Page 4: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

Study of Existing Transformers in ServiceStudy of Existing Transformers in Service

Out of 960, 605 were oversized-63%Out of 960, 605 were oversized-63%

Over 10% at least 3 sizes too bigOver 10% at least 3 sizes too big

150 kVA, 300 kVA and 500 kVA are the least 150 kVA, 300 kVA and 500 kVA are the least accurately sizedaccurately sized

Very few transformers over-loadedVery few transformers over-loaded

Overall results of study show an overly Overall results of study show an overly conservative sizing methodconservative sizing method

Page 5: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

Existing Transformers in Existing Transformers in ServiceService

E xis ting T rans formers in S ervic eT rans former C las s ific ation

0%

20%

40%

60%

80%

100%

kV A kV A kV A kV A kV A kV A kV A kV A kV A kV A kV A

75 112 150 225 300 500 750 1000 1500 2000 2500T ra nsformer S iz e (kVA)

3-P

has

e P

adm

ou

nts

R -5

R -4

R -3

R -2

R -1

R

R +1

Page 6: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

Study of Existing Transformers in ServiceStudy of Existing Transformers in Service

Page 7: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

Financial AnalysisFinancial Analysis

Capital expense of the equipmentCapital expense of the equipment

Operating cost = No-load power lossOperating cost = No-load power loss

Wholesale electricity rate of $0.04/kWH Wholesale electricity rate of $0.04/kWH was usedwas used

Page 8: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

Financial Analysis – Capital Financial Analysis – Capital

Estimated by using the price of the most Estimated by using the price of the most recently purchased transformer of that recently purchased transformer of that sizesize

Sums entire purchase price* of the 960 Sums entire purchase price* of the 960 transformers (total capital expense)transformers (total capital expense)*Purchase price includes installation costs*Purchase price includes installation costs

Theoretical estimated purchase cost vs. Theoretical estimated purchase cost vs. actual estimated purchase costactual estimated purchase cost

Page 9: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

Financial AnalysisFinancial Analysis

Page 10: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

Financial Analysis – Operating Financial Analysis – Operating

No-load power loss (Watts)No-load power loss (Watts)

Not considered:Not considered:• Full-load loss, repairs and maintenance Full-load loss, repairs and maintenance • Conservative estimateConservative estimate

PF of 0.95 used, if unable to gather PF of 0.95 used, if unable to gather from databasefrom database

Page 11: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

Financial AnalysisFinancial Analysis

No-Load Power Loss (O&M)No-Load Power Loss (O&M)

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Financial Analysis - OverallFinancial Analysis - Overall

Assuming sizing methods and results are Assuming sizing methods and results are consistent for all BHP transformersconsistent for all BHP transformers

• Three-phase, pad-mount share of the transformerThree-phase, pad-mount share of the transformer

purchase cost is roughly 26% of the $2.5 million annual purchase cost is roughly 26% of the $2.5 million annual

transformer purchase cost budgettransformer purchase cost budget

• At 17%, At 17%, $425,000 $425,000 annual benefitannual benefit

Page 13: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

Research ApplicationResearch Application

Increase efficiency from the sizing Increase efficiency from the sizing statisticsstatistics

PossibilitiesPossibilities• Review current transformer placement, Review current transformer placement,

and change-out existing units based on and change-out existing units based on economic feasibility. economic feasibility.

• Develop more accurate transformer Develop more accurate transformer sizing methodsizing method

Page 14: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

Forecasting Customer Forecasting Customer Electricity LoadsElectricity Loads

Many factorsMany factors• Size of structure to be poweredSize of structure to be powered• General purpose of structureGeneral purpose of structure• Structural componentsStructural components• Machines and Appliances to be installedMachines and Appliances to be installed• LocationLocation• Personnel capacity of building or Personnel capacity of building or

structurestructure

Page 15: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

Customer CategoriesCustomer Categories

This study includesThis study includes• Retail Stores Retail Stores • Business officesBusiness offices• Apartments (gas heated, electric heat)Apartments (gas heated, electric heat)• Many others to be considered, time-Many others to be considered, time-

constraints limit this studyconstraints limit this study

Page 16: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

Data Collection and CalculationData Collection and Calculation

Cooperation of CustomersCooperation of Customers Tax Equalization office supplied square Tax Equalization office supplied square

footage informationfootage information Averages based on Peak kVA demandsAverages based on Peak kVA demands Power factor assumed 0.95 if Unavailable Power factor assumed 0.95 if Unavailable

in databasein database Calculations of W/sf, mA/sfCalculations of W/sf, mA/sf

• Consistent values, low standard of deviation in Consistent values, low standard of deviation in datadata

Page 17: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

Results – Business OfficesResults – Business Offices

Averaged Averaged 5.765.76 watts per square foot watts per square foot Highest: Highest: 7.097.09 Lowest: Lowest: 4.524.52 W/sqft W/sqft

Averaged 34% of Main Switch Averaged 34% of Main Switch AmpacityAmpacity

Mainly fluorescent lightingMainly fluorescent lighting Gas heatedGas heated

Page 18: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

Business OfficesBusiness Offices

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Results - Retail StoresResults - Retail Stores

Averaged 4.98 W/sqft Averaged 4.98 W/sqft High: 8.13 / Low: 2.86High: 8.13 / Low: 2.86 Averaged 46% of Main Switch Averaged 46% of Main Switch

AmpacityAmpacity Mostly Fluorescent Lighting, some Mostly Fluorescent Lighting, some

spot lightingspot lighting

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Retail StoresRetail Stores

Page 21: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

Results - ApartmentsResults - Apartments

Gas Heated, summer peaking, 94.7% occ.Gas Heated, summer peaking, 94.7% occ.• Averaged 1.42 W/sqft, 1.5 W/sqft @ 100%Averaged 1.42 W/sqft, 1.5 W/sqft @ 100%• High: 2.09 / Low: 0.82High: 2.09 / Low: 0.82

Electric Heat, winter peaking, 81.5% occ.Electric Heat, winter peaking, 81.5% occ.• Averaged 3.53 W/sqft, 4.3 W/sqft @ 100%Averaged 3.53 W/sqft, 4.3 W/sqft @ 100%• High: 4.14 / Low: 2.71High: 4.14 / Low: 2.71

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Apartment BuildingsApartment Buildings

Page 23: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

ApplicationsApplications

Gives utility representatives statistics Gives utility representatives statistics when discussing options with customers & when discussing options with customers & contractors.contractors.

Presents evidence & factual history to help Presents evidence & factual history to help decide on transformer size.decide on transformer size.

Provides foundation and structure for Provides foundation and structure for further research of future demand and further research of future demand and transformer sizing.transformer sizing.

Page 24: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

SummarySummary

Sizing analysis shows significant cost Sizing analysis shows significant cost avoidance capabilities:avoidance capabilities:• 17% $425,00017% $425,000• O&M savings (NLL only) of 31%O&M savings (NLL only) of 31%

Customer demand indicators may Customer demand indicators may help utility reps with transformer help utility reps with transformer sizing, and provide a basis to sizing, and provide a basis to advance researchadvance research

Page 25: Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota.

Questions?Questions?