# Residential Battery Storage

The 2022 ATB represents cost and performance for battery storage with a representative system: a 5-kW/12.5-kWh (2.5-hour) system. It represents only lithium-ion batteries (LIBs)—with nickel manganese cobalt (NMC) and lithium iron phosphate (LFP) chemistries—at this time, with LFP becoming the primary chemistry for stationary storage starting in 2021. There are a variety of other commercial and emerging energy storage technologies; as costs are well characterized, they will be added to future editions of the ATB.

The National Renewable Energy Laboratory's (NREL's) Storage Futures Study examined energy storage costs broadly and specifically the cost and performance of LIBs (Augustine and Blair, 2021). This report is the basis of the costs presented here (and for distributed commercial storage and utility-scale storage) . This work incorporates base year battery costs and breakdown from the report (Ramasamy et al., 2021) that works from a bottom-up cost model. The bottom-up battery energy storage systems (BESS) model accounts for major components, including the LIB pack, inverter, and the balance of system (BOS) needed for the installation. We would note though that, during the elapsed time between the calculations for the Storage Futures Study and the ATB release, updated values have been calculated as more underlying data have been collected. While these changes are small, we recommend using the data presented here in the ATB rather than what was previously published with the Storage Futures Study.

2021 costs for residential BESS are based on NREL’s bottom-up BESS cost model using the data and methodology of (Ramasamy et al., 2021), who estimated costs for both AC- and DC-coupled systems. We use the same model and methodology but do not restrict the power or energy capacity of the BESS to two options. Key modeling assumptions and inputs are shown in Table 1. We assume 2021 battery pack costs of $252/kWh_{DC} 2020 USD (Ramasamy et al., 2021)

Model Component | Modeled Value | Description |

System size | 5 kW power capacity 2.5 E/P ratio | Battery capacity is in kW E/P is battery energy to power ratio and is synonymous with storage duration in hours. |

Battery pack cost | $252/kWh | Battery pack only (BNEF, 2019) |

Battery-based inverter cost | $167/kWh | Assumes a bidirectional inverter (BNEF, 2019), converted from $/kWh for 5 kW/12.5 kWh system |

Supply-chain costs | 5% (U.S. average) | U.S. average sales tax on equipment |

Installation labor cost | Electrician: $27.36/hour Laborer: $18.22/hour | Assumes U.S. average pricing |

Engineering fee | $98 | Engineering design and professional engineer-stamped calculations and drawings |

Permitting, inspection, and interconnection | $295 permit fee $1,133–$1639 in labor | 20/32 hours (DC-coupled/AC-coupled) of commissioning and interconnection labor, and permit fee |

Sales and marketing (customer acquisition) | $0.54/WDC | 20 hours more for DC system and 32 hours more for AC system, per closed sale, associated with selling a storage system versus selling a PV system |

Overhead (general and administrative) | $0.25/WDC | Rent, building, equipment, staff expenses not directly tied to permitting, inspection, and interconnection; customer acquisition; or direct installation labor |

Profit (%) | 17% | Fixed percentage margin applied to all direct costs including hardware, installation labor, direct sales and marketing, design, installation, and permitting fees. |

As with utility-scale BESS, the cost of a residential BESS is a function of both the power capacity and the energy storage capacity of the system, and both must be considered when estimating system cost. Furthermore, the Distributed Generation Market Demand (dGen) model does not assume specific BESS system sizes and it needs an algorithm to estimate residential BESS system cost based on the attributes of the residences (agents) it generates.

We develop an algorithm for stand-alone residential BESS cost as a function of power and energy storage capacity using the NREL bottom-up residential BESS cost model (Ramasamy et al., 2021) with some modifications.

## Scenario Descriptions

Available cost data and projections are very limited for distributed battery storage. Therefore, the battery cost and performance projections in the 2022 ATB are based on the same literature review as for utility-scale and commercial battery cost projections. The projections are based on a literature review of 19 sources published in 2018 or 2019, as described by Cole and Frazier (Cole and Frazier, 2020). Three projections from 2020 to 2050 are developed for scenario modeling based on this literature.

In all three scenarios of the scenarios described below, costs of battery storage are anticipated to continue to decline. The Storage Futures Study (Augustine and Blair, 2021) describes that the majority of this cost reduction comes from the battery pack cost component with minimal cost reductions in BOS, installation, and other components of the cost. The report indicates that NREL, BloombergNEF (BNEF), and others anticipate that the growth of the overall battery industry - across the consumer electronics sector, the transportation sector, and the electric utility sector - will lead to cost reductions. Additionally, BNEF and others indicate that changes in lithium-ion chemistry (such as switching away from cobalt) will also reduce cost. A third key factor is ongoing innovation with significant corporate and public research on batteries. Finally, the growth in the market (effective learning-by-doing) and more diversity of chemistries will expand and change the dynamics of the supply chain for batteries resulting in cheaper inputs to the battery pack (Mann et al., 2022).

**Conservative Technology Innovation Scenario****(Conservative Scenario):**The conservative projection is comprised of the maximum projection in 2020, 2025, and 2030 among the 19 projections reviewed. Defining the 2050 points is more challenging because only four data sets extend to 2050; they show cost reductions of 19%, 25%, 27%, and 39% from 2030 to 2050. The 25% is used for the Moderate and Conservative scenarios. In other words, the Conservative Scenario is assumed to decline by 25% from 2030 to 2050.**Moderate Technology Innovation Scenario (Moderate Scenario):**The moderate projections are taken as the median point in 2020, 2025, and 2030 of the 19 projections reviewed. Defining the 2050 points is more challenging because only four data sets extend to 2050; they show cost reductions of 19%, 25%, 27%, and 39% from 2030 to 2050. The 25% is used for the Moderate and Conservative scenarios. In other words, the Moderate Scenario is assumed to decline by 25% from 2030 to 2050.**Advanced Technology Innovation Scenario (Advanced Scenario):**The advanced projections are taken as the lowest cost point in 2020, 2025, and 2030 of the 19 projections reviewed. Defining the 2050 points is more challenging because only four data sets extend to 2050; they show cost reductions of 19%, 25%, 27%, and 39% cost reduction from 2030 to 2050. The 39% is used for the Advanced Scenario. In other words, the Advanced Scenario is assumed to decline by 39% from 2030 to 2050.

## Methodology

NREL does not maintain future cost projections for residential BESS for the ATB as it does for utility-scale systems. Instead, we base residential BESS cost projections on the NREL bottom-up cost model for residential systems combined with component cost projections from BNEF. BNEF has published cost projections for a 5-kW/14-kWh BESS system through 2030 (Frith, 2020), with the projections being based on learning rates and future capacity projections.

Data Source: (BNEF, 2019)

The methodology involves the following the steps to generate the Moderate Scenario future cost projections in detail:

- Estimate base year costs for a range of BESS power and energy capacity combinations using the NREL bottom-up residential BESS cost model.
- Total and component cost results are recorded.
- Component costs are assigned to categories according to Table 4.

- Moderate Scenario: For each future year, apply cost reductions.
- Apply cost reductions from the BNEF projections (Frith, 2020) to the corresponding component cost category for each BESS considered.
- BNEF projections only go to 2030. We assume residential BESS component costs decline by an additional 25% from 2030 to 2050, similar to the assumption used in the ATB utility-scale BESS cost projections (Cole and Frazier, 2020).

- Advanced and Conservative Scenarios: Apply cost projections from the corresponding ATB utility-scale BESS scenario to all component costs.
- Sum the component costs to get the total BESS cost in future years. For each future year, develop a linear correlation relating BESS costs to power and energy capacity:
- BESS cost (total $) = c
_{1}* P_{B}+ c_{2}* E_{B}+ c_{3} - Where P
_{B}= battery power capacity (kW) and E_{B}= battery energy storage capacity ($/kWh), and c_{i}= constants specific to each future year.

- BESS cost (total $) = c

### Capital Expenditures (CAPEX)

**Definition: **The bottom-up cost model documented by (Ramasamy et al., 2021) contains detailed cost bins for both solar only, battery only, and combined systems. Though the battery pack is a significant cost portion, it is a fraction of the cost of the battery system. This cost breakdown is different if the battery is part of a hybrid system with solar PV or a stand-alone system. The total costs by component for residential-scale stand-alone battery are demonstrated in Figure 2 for two different example systems.

**Current Year (2021)**: The Current Year (2021) cost estimate is taken from (Ramasamy et al., 2021) and is currently in 2020 USD.

Within the ATB Data spreadsheet, costs are separated into energy and power cost estimates, which allows capital costs to be constructed for durations other than 4 hours according to the following equation:

Total System Cost ($/kW) = (Battery Pack Cost ($/kWh) × Storage Duration (kWh) + Battery Power Capacity (kW) × BOS Cost ($/kW) + Battery Power Constant ($)) / Battery Power Capacity (kW)

For more information on the power versus energy cost breakdown, see (Cole and Frazier, 2020). For items included in CAPEX, see the table below.

**Future Projections**: Future projections are based on the same literature review data that inform Cole and Frazier (Cole and Frazier, 2020), which generally used the median of published cost estimates to develop a Mid Technology Cost Scenario and the minimum values to develop a Low Technology Cost Scenario. However, as the battery pack cost is anticipated to fall more quickly than the other cost components (which is similar to the recent history of PV system costs), the battery pack cost reduction is taken from BNEF (Frith, 2020) and is reduced more quickly. This tends to make the longer-duration batteries (e.g., 10 hours) decrease more quickly while shorter-duration batteries (e.g., 2 hours) decrease less quickly into the future. All durations trend toward a common trajectory as battery pack costs decrease into the future.

### Operation and Maintenance (O&M) Costs

**Base Year**: (Cole et al., 2021) assume no variable O&M (VOM) cost. All operating costs are instead represented using fixed O&M (FOM) costs. The fixed O&M costs include battery replacement costs, based on assumed battery degradation rates that drive the need for 20% capacity augmentations after 10 and 20 years to return the system to its nameplate capacity (Ramasamy et al., 2021). The augmentations assume that 20% of the cells are replaced in each augmentation, with costs for battery cells and bidirectional inverters dropping 40% in the next 20 years. In the 2022 ATB, FOM is defined as the value needed to compensate for degradation to enable the battery system to have a constant capacity throughout its life. According to the literature review in (Cole et al., 2021), FOM costs are estimated at 2.5% of the capital costs in dollars per kilowatt. Items included in O&M are shown in the table below.

**Future Years**: In the 2022 ATB, the FOM costs and VOM costs remain constant at the values listed above for all scenarios.

### Capacity Factor

The cost and performance of the battery systems are based on an assumption of approximately one cycle per day. Therefore, a 4-hour device has an expected capacity factor of 16.7% (4/24 = 0.167), and a 2-hour device has an expected capacity factor of 8.3% (2/24 = 0.083). Degradation is a function of this usage rate of the model and systems might need to be replaced at some point during the analysis period. We use the capacity factor for a 4-hour device as the default value for ATB due to anticipation that 4-hour durations are more typical in the utility-scale market.

### Round-Trip Efficiency

Round-trip efficiency is the ratio of useful energy output to useful energy input. (Mongird et al., 2020) identified 86% as a representative round-trip efficiency, and the 2022 ATB adopts this value. In the same report, testing showed 83-87%, literature range of 77-98%, and a projected increase to 88% in 2030.

## References

The following references are specific to this page; for all references in this ATB, see References.