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Distribution Transformer Size Optimization by Forecasting Customer Electricity Load

Distribution Transformer Size Optimization by Forecasting Customer Electricity Load. Jarrod Luze Black Hills Power Rapid City, South Dakota. Introduction. Electric utilities face common challenges determining transformer sizes. Study consists of 960 three phase pad-mounted transformers.

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Distribution Transformer Size Optimization by Forecasting Customer Electricity Load

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

  2. Introduction • Electric utilities face common challenges determining transformer sizes. • Study consists of 960 three phase pad-mounted transformers. • Research and categorization of existing transformers • Ideal vs. actual benefit/cost analysis • Forecasting future customer power demand

  3. Study of Existing Transformers in Service • Compared kVA name-plate rating to peak demand of customer • ‘R+_’ signifies that a transformer is undersized and would ideally require a larger transformer for the load. • ‘R-_’ signifies the transformer is under-loaded, and a smaller transformer would suffice.

  4. Study of Existing Transformers in Service • Out of 960, 605 were oversized-63% • Over 10% at least 3 sizes too big • 150 kVA, 300 kVA and 500 kVA are the least accurately sized • Very few transformers over-loaded • Overall results of study show an overly conservative sizing method

  5. Existing Transformers in Service

  6. Study of Existing Transformers in Service

  7. Financial Analysis • Capital expense of the equipment • Operating cost = No-load power loss • Wholesale electricity rate of $0.04/kWH was used

  8. Financial Analysis – Capital • Estimated by using the price of the most recently purchased transformer of that size • Sums entire purchase price* of the 960 transformers (total capital expense) *Purchase price includes installation costs • Theoretical estimated purchase cost vs. actual estimated purchase cost

  9. Financial Analysis

  10. Financial Analysis – Operating • No-load power loss (Watts) • Not considered: • Full-load loss, repairs and maintenance • Conservative estimate • PF of 0.95 used, if unable to gather from database

  11. Financial Analysis No-Load Power Loss (O&M)

  12. Financial Analysis - Overall Assuming sizing methods and results are consistent for all BHP transformers • Three-phase, pad-mount share of the transformer purchase cost is roughly 26% of the $2.5 million annual transformer purchase cost budget • At 17%, $425,000 annual benefit

  13. Research Application • Increase efficiency from the sizing statistics • Possibilities • Review current transformer placement, and change-out existing units based on economic feasibility. • Develop more accurate transformer sizing method

  14. Forecasting Customer Electricity Loads • Many factors • Size of structure to be powered • General purpose of structure • Structural components • Machines and Appliances to be installed • Location • Personnel capacity of building or structure

  15. Customer Categories • This study includes • Retail Stores • Business offices • Apartments (gas heated, electric heat) • Many others to be considered, time-constraints limit this study

  16. Data Collection and Calculation • Cooperation of Customers • Tax Equalization office supplied square footage information • Averages based on Peak kVA demands • Power factor assumed 0.95 if Unavailable in database • Calculations of W/sf, mA/sf • Consistent values, low standard of deviation in data

  17. Results – Business Offices • Averaged 5.76 watts per square foot • Highest: 7.09 Lowest: 4.52 W/sqft • Averaged 34% of Main Switch Ampacity • Mainly fluorescent lighting • Gas heated

  18. Business Offices

  19. Results - Retail Stores • Averaged 4.98 W/sqft • High: 8.13 / Low: 2.86 • Averaged 46% of Main Switch Ampacity • Mostly Fluorescent Lighting, some spot lighting

  20. Retail Stores

  21. Results - Apartments • Gas Heated, summer peaking, 94.7% occ. • Averaged 1.42 W/sqft, 1.5 W/sqft @ 100% • High: 2.09 / Low: 0.82 • Electric Heat, winter peaking, 81.5% occ. • Averaged 3.53 W/sqft, 4.3 W/sqft @ 100% • High: 4.14 / Low: 2.71

  22. Apartment Buildings

  23. Applications • Gives utility representatives statistics when discussing options with customers & contractors. • Presents evidence & factual history to help decide on transformer size. • Provides foundation and structure for further research of future demand and transformer sizing.

  24. Summary • Sizing analysis shows significant cost avoidance capabilities: • 17% $425,000 • O&M savings (NLL only) of 31% • Customer demand indicators may help utility reps with transformer sizing, and provide a basis to advance research

  25. Questions?

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