In our previous TerraBlog post, How CCAs can partner with their NEM customers to reduce their Resource Adequacy costs with energy storage systems, we shared the process we use to model the impact of pairing energy storage systems with existing customer solar PV systems on CCA Resource Adequacy (RA) costs. This post is part two of the study and presents the economic results of that study.

Utilizing the BEO software, the primary focus of the study is to reduce a CCA’s system RA costs. Other RA costs, i.e., local and flex, are not included in the study. The software was used to identify ideal NEM customers that match the following features in their electricity usage profiles:

  • Sufficient electricity export from solar for daily charging of commercially available batteries
  • Coincident usage peaks with the CCA’s system peaks
  • Sufficient electricity imports at other hours to absorb the electricity discharge from batteries

The software identified approximately 1,038 customers whose profiles matched these features, from a population of 5,021 potential customers. These 1,038 customers are on PG&E E-1 and E-6 rate schedules with electricity load profiles suitable to deploy 10 and 20 kWh battery energy storage systems.

The software then applied the following battery cycling algorithm to the load profile for each customer:

  • Charge the batteries from solar exports
  • Block charging the batteries from the grid
  • Discharge the batteries to optimally flatten the primary and secondary system peaks for each month for the CCA

A note on primary and secondary system peaks: As an example, if the system load’s primary peak occurs at 6pm and the secondary peak occurs at 7pm, then the battery will focus on discharging at 6pm and continue to discharge during 7pm to reduce both peaks simultaneously, as capacity remains available. The following tables represent the monthly system maximum loads in a 288h format before and after the addition of these batteries.

The net impact of the energy storage systems on the monthly maximum loads can be seen in the following table.

The impact of load reduction varies in each month with the highest reduction occurring in the month of June. Over the course of a year, the monthly maximum loads are reduced by a total of 23.5 MW-months. This monthly reduction is achieved by deploying approximately 15.7 MWh of storage capacity distributed between 1,038 customers. Using an average value of $6/kW-month for system RA costs, this reduction corresponds to approximately $140,676 of annual RA cost savings for the CCA.

For our next TerraBlog post, we will share the process and economic impacts from electrification measures (ex. gas to electric water and space heaters) for CCAs and their customers.

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