Solar+Storage/Impact of Load Profile
Impact of Load Profile on Solar+Storage Economics
Key Questions
- Which building types have the most peaks in electricity use?
- Do buildings with variable loads get more savings from solar+storage?
- Can a building with a flat electricity load see savings from a solar+storage system?
Results
- Secondary schools, office buildings and retail stores have the most variation in electrical loads.
- The potential for savings from combining solar with storage is independent of building load variability, likely due to the significant energy cost ($/kWh) reductions from the solar generation.
- Combining solar with storage may increase the number of cases in which storage is economical.
- As technology prices decline, solar+storage systems may yield savings for most commercial building types, despite the amount of variation in load profile.
- No relationship was found between load variability and the battery configuration. Optimization modeling resulted in vastly different battery durations for buildings of the same type and of similar load variability. Other variables, such as technology cost and rate structure, were more influential on the cost-optimal battery sizing and duration.
Load Factors of the Buildings Modeled
Load factor indicates the degree of fluctuation in the building load. It is calculated by dividing the mean demand by the peak demand over the course of a year. A low percentage indicates higher variability in the load. The chart below shows the load factors of the buildings modeled.
Impact of Load Variability on Expected Savings
A common assumption is that load profiles with peaks are the most likely candidates for savings from storage due to the opportunity for demand charge reduction. Our results indicate that by combining solar with storage, buildings with less variability may also achieve savings. This is likely due to the energy cost reductions resulting from the solar generation.
Impact of Load Variability on Expected Savings from Solar Combined with Storage
Breaking out energy charge and demand charge savings by building load factor shows the extent to which variability in the load impacts savings. Demand charge savings are higher in cases with more variability in load profile, however total savings from combined solar and storage projects is not related to load variability.
Impact of Load Variability on Battery Configuration
No relationship was found between load variability and the battery configuration. Optimization modeling resulted in vastly different battery durations for buildings of the same type and of similar load variability. Other variables, such as technology cost and rate structure, were more influential on the cost-optimal battery sizing and duration.
Cost Point Definitions
| Cost Point | PV System Installed Cost ($/w) | PV O&M Cost ($/kW) | Battery Storage System Installed Cost for Power Rating* ($/kW) | Battery Storage System Installed Cost for Energy Rating ($/kWh) | Battery Storage Replacement Cost ($/kW) | Battery Storage Replacement Cost ($/kWh) |
|---|---|---|---|---|---|---|
| High Cost Point | $1.37 | $8 | $1,332 | $290 | $441 | $256 |
| Mid Cost Point | $1.11 | $8 | $1,062 | $256 | $407 | $238 |
| Low Cost Point | $0.97 | $8 | $1,193 | $151 | $326 | $106 |
| Stretch Cost Point | $0.90 | $8 | $787 | $106 | $276 | $97 |
* Battery storage projects costs vary depending on the power to energy ratio (also referred to as "duration"). The REopt model requires storage project costs to be input as two separate numbers, one for the power rating and another for the energy rating. These two cost variables are considered together in determining the optimal battery system configuration and, hence, the final project cost.