In our previous TerraBlog post, How batteries can reduce CCAs GHG emissions, we shared the process of modeling the impact energy storage systems have on greenhouse gas emissions of a community choice agency (CCA). In this two-part post we will share the process and results for modeling the impacts to the Resource Adequacy (RA) costs for a CCA by pairing energy storage systems with existing NEM customers.
Background on Resource Adequacy
RA refers to the obligation of ensuring the grid will have sufficient resources at any given time to guarantee the grid can operate safely and reliably. It is a mechanism used to safeguard against potential brown outs or black outs. There are three types of RA costs that Load Serving Entities (LSE) including CCAs have to account for: system, local and flexible. Each type of RA has specific requirements. System RA costs are based on a CCA’s systemwide monthly peak forecast. Local RA costs are based on the past 10 years of load data for a region, this includes more than just the CCA’s load requirements. Flexible RA costs are based on the largest 3-hour ramp in a given month. By reducing the systemwide load, a CCA could lower their system and local RA costs, whereas flexible RA cost reduction could be accomplished with a Virtual Power Plant (VPPs). See our TerraBlog post on DER Rate Design in which the concept of VPPs and their benefit to CCAs are further explained.
For this study, we focused on assessing CCA customers with existing solar PV systems under the NEM tariff, and how pairing energy storage systems would impact the CCA’s system RA costs.
To determine the impact solar PV and energy storage systems have on RA we start by modeling the following system RA cost scenarios:
|System RA Cost Scenario #||Scenario Name|
|1||Annual system RA cost ex-solar PV|
|2||Annual system RA cost post-solar PV|
|3||Annual system RA cost post-solar PV and energy storage|
Here are the definitions for each scenario:
- Ex-solar: a building/customer/system load profile in absence of solar PV system (i.e. what would the load profile have been if there was no solar PV system installed during the study period).
- Post-solar PV: a building/customer/system load profile after solar PV system(s) are installed
- Post-solar PV and storage: a building/customer/system load profile after solar PV and energy storage system(s) are installed
Furthermore, the calculation methodology for each scenario is described below:
Scenario 1: To calculate the RA cost of a CCA under scenario 1, we would include the aggregate load profiles of all CCA customers including the calculated load profile of existing NEM customers under an ex-solar scenario.
Scenario 2: To calculate the RA cost of a CCA under scenario 2, we would include the aggregate load profiles of all CCA customers including the load profile of existing NEM customers under a post-solar scenario. This scenario should represent the current RA cost of a CCA.
Scenario 3: To calculate the RA cost of a CCA under scenario 3, we would include the aggregate load profiles of all CCA customers including the projected load profile of existing NEM customers under a post-energy storage scenario.
By modeling the first two system RA cost scenarios we are able to assess where system load peaks occur and which NEM customers have load peaks that are coincident with the CCAs systemwide load peaks. By adding energy storage systems to the NEM customers that contribute to the system peak, we can effectively reduce the system peak, and thus the RA costs for a CCA.
The following graph represents what these three scenarios could look like:
We then calculate the adjustment to RA costs due to the impact of solar PV and energy storage systems by comparing the following avoided cost values:
|Avoided Cost Scenario #||Scenario Name||Method|
|1||Annual avoided system RA cost due to solar PV||System RA Cost scenario 1 minus 2|
|2||Annual avoided system RA cost due to energy storage||System RA Cost scenario 2 minus 3|
Avoided cost scenario 1 represents the financial impact associated with a CCAs current NEM customers, presenting the effect these customers solar has had on the system RA costs. Avoided cost scenario 2 represents the financial impact associated with adding energy storage systems to the CCA NEM customers whose load peaks are coincident with the system load peaks. This represents the value add to a CCA of deploying energy storage systems to those specific customers.
Our next post will be part two of this study in which we will talk about the results of the RA modeling and how energy storage systems can impact the RA costs of a CCA.
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