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BEO software by TerraVerde Energy

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How can CCAs use software to identify and promote DERs that are economically beneficial and reduce GHGs?

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BEO software by TerraVerde Energy

  1. 1. BEO Software for CCA Program Managers
  2. 2. The BEO software CEC funded grant to develop a software to enable CCAs Program Managers to identify DER programs. ‣ DER programs: ‣ Replicable & scalable ‣ Reduce GHG emissions ‣ Provide economic benefits
  3. 3. The omni question approach The BEO software is designed to approach problems that can be modeled using the following omni question format: "What is the Benefit or Cost to deploy a Quantity of DERs to a Customer Segment in a CCA'sTerritory/Location over aTime Frame?"
  4. 4. We picked batteries for our first analysis What is the benefit to deploy behind-the-meter battery storage systems to NEM net generator customers in MCE over the 2018 annual billing cycle?
  5. 5. Step 1 Identify the right customers
  6. 6. Class Count Aggregate Load (kWh) E1 2306 (2,679,128) ETOUA 2203 (2,364,570) E6 780 (1,101,666) A6 90 (1,091,933) A1 22 (468,151) ETOUB 361 (439,355) A1X 42 (238,438) EVA 215 (228,081) E1L 227 (210,699) ETOUAL 129 (106,575) ETOUC 27 (23,739) ETOUBL 15 (18,529) E6L 17 (13,040) Other 659 (1,472,492) Let’s understand the customers
  7. 7. Class Aggregate Load (kWh) % of Total E1 (2,679,128) 24.9% ETOUA (2,364,570) 22.0% E6 (1,101,666) 10.3% A6 (1,091,933) 10.2% A1 (468,151) 4.4% Use Pareto’s rule for scalability/replicability
  8. 8. Apply K-means Clustering A6 commercial customers ‣ Cluster on total kW per month-hour ‣ 43 customers with similar usage patterns chosen
  9. 9. Step 2 Apply DER Scenario
  10. 10. Use a standard battery specification ‣ Each battery modeled separately per meter ‣ Battery sized at 120 kW @ 2 hours ‣ 200 kWh available for daily cycling ‣ 40 kWh reserved for resiliency ‣ Charge only on solar exports to the grid ‣ Discharge between 4 p.m. and 9 p.m. ‣ Do not export from battery to the grid
  11. 11. We see load flattening ‣ Impact to Aggregate kWh by month-hour ‣ 12 black lines represent kWh each month before batteries ‣ 12 blue lines represent kWh each month after batteries
  12. 12. Monthly demand reduction
  13. 13. Monthly load shifting
  14. 14. Step 3 Calculate Cost/Benefits
  15. 15. Month Before After 1 24.80 27.86 2 -14.83 -12.48 3 -19.84 -17.91 4 -57.54 -56.40 5 -70.76 -69.64 6 -82.98 -81.74 7 -74.42 -73.11 8 -40.33 -38.90 9 -23.60 -21.88 10 8.17 9.61 11 26.70 27.59 12 35.88 38.23 Total -288.75 -268.77 GHG impact: method 1 ‣ Using grid GHG content average ‣ 0.000435 tCO2/kWh constant ‣ total kWh increases due to battery losses ‣ calculated GHG emissions increase
  16. 16. Year Before After 2018 -240.03 -228.33 2022 48.30 -9.74 2026 1.38 -38.37 2030 250.53 133.48 GHG impact: method 2 ‣ Using Clean Net Short ‣ Variable tCO2/kWh on a month-hour basis
  17. 17. Customer bill/CCA revenue impact Before: -$202,692.53 | After: -$191,349.09 Exports during peak hours ($0.340/kWh) are used to offset load during part-peak hours ($0.102/kWh)
  18. 18. Future considerations ‣ Assess other top customer segments ‣ Apply other battery models: ‣ size ‣ charge/discharge schedule for wholesale procurement profitability ‣ charge from grid, export to grid (pending regulation) ‣ Assess potential resource adequacy opportunities ‣ Model real-time and day ahead benefits underVPP
  19. 19. Thank you

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