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

1. BEO
Software for CCA Program Managers

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. 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. 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. Step 1
Identify the right customers

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. 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. Apply K-means Clustering
A6 commercial customers
‣ Cluster on total kW per
month-hour
‣ 43 customers with similar
usage patterns chosen

9. Step 2
Apply DER Scenario

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. 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. Monthly demand reduction

13. Monthly load shifting

14. Step 3
Calculate Cost/Benefits

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. 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. 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. 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. Thank you