How Big is the Market for Batteries on the Grid?

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Eric Selmon Hugh Wynne

Office: +1-646-843-7200 Office: +1-917-999-8556

Email: eselmon@ssrllc.com Email: hwynne@ssrllc.com

SEE LAST PAGE OF THIS REPORT FOR IMPORTANT DISCLOSURES

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April 18, 2017

How Big is the Market for Batteries on the Grid?

Recent statements by Elon Musk promoting the widespread deployment of batteries on the power grid have led to speculation that the grid may be the next big battery market. Is this view correct? In this note we quantify the addressable market for batteries on the grid, whether deployed by utilities, residences or businesses, and compare these potential markets to that for electric vehicle batteries.

  • We estimate the total addressable market for batteries on the U.S. power grid at 700 GWh, assuming full replacement of all peaking capacity. Given the high cost of storage, however, and the fact that small amounts of storage can suppress peak power prices, eroding the incentives for further deployment, we believe the economic market for grid storage will not exceed 115 GWh, and is likely far smaller.
  • By comparison, the total addressable market for electric vehicle (EV) batteries in the U.S. is staggeringly large. The U.S. vehicle fleet comprises 260 million cars, trucks and buses. Assuming each were equipped with a battery with a range of 300 miles per charge and an average fleet energy efficiency of 2.6 miles per kWh, the potential scale of the U.S. EV market for batteries can be estimated at 30,000 GWh – some 40x the total addressable market for grid storage.
  • Unless battery costs fall dramatically, regulated utilities and competitive generators will not deploy batteries as peaking capacity. Measured by the cost of energy supplied during peak hours, grid scale batteries cost 3 to 4x as much as new conventional gas fired peakers (Exhibit 2), discouraging their use by regulated utilities. And competitive generators cannot recover the cost of a battery from the arbitrage profit to be had by buying electricity off peak and selling it on peak in the wholesale power market (Exhibit 4).
  • Electric energy storage on the grid is attractive, by contrast, in markets where generation has been deregulated and where power is procured for consumers in competitive wholesale markets where prices are set by the marginal cost of supply. In these markets, power supply curves tend to be extremely steep at very high levels of demand (Exhibit 5), so that small increases in demand result in disproportionate increases in the marginal cost of supply and thus in the prevailing market price of power (Exhibit 6).
  • Even small amounts of electric energy storage on the grid can significantly reduce the marginal cost of supply on peak and thus the total cost of procuring power to serve load. We calculate that, had just 500 MW of storage been deployed on the ERCOT grid over the five years from 2011 through 2015, the savings to consumers would have averaged ~$1.3 billion annually.
  • We believe the substantial savings to consumers from even limited amounts of grid storage will motivate regulators to encourage its deployment by utilities and their customers. The California Public Utilities Commission has required the state’s investor-owned utilities to deploy 1,325 MW of storage by 2020. We expect regulators in other states that have deregulated generation to follow California’s example: Massachusetts is considering policies to encourage the deployment of 600 MW of storage by 2026 and Maryland has passed a tax credit for distributed storage.
  • However, in the five competitive wholesale markets that serve states where generation has been deregulated, the battery capacity required to close the average daily gap between maximum and minimum demand is only 29 GW. Assuming these batteries were capable of four hours of discharge, this would suggest an economic market for grid storage of only 115 GWh.
  • A market for smaller scale batteries may exist among commercial electricity consumers, whose bills include a demand charge based upon their highest draw of power from the grid. For businesses whose peak demand for power is relatively short (2 hours or less), the use of batteries to reduce peak demand is economic today in states like California where demand charges are high. If battery prices fall so as to render commercial storage economic in other states, the deployment of 2 hours of storage capacity to supply the very highest demand periods could cut peak U.S. commercial load by 5%, suggesting a potential commercial market for storage of 31 GWh (peak commercial load of 310 GW x 5% x 2 hours).
    • At businesses whose peak loads are of longer duration (4 hours or more), significant further declines in battery costs are required for additional storage to be attractive. These include most commercial consumers, with peak loads of 8 to 10 hours’ duration, and industrial consumers, whose demand profiles are generally flat across 16 to 24 hours of the day.
  • Similarly, unless their prices fall dramatically, batteries will not be economic for residential electricity consumers, whether for use as a back-up power supply, to arbitrage between peak and off-peak electricity rates, or to store excess solar generation at mid-day for use during the evening hours.
  • Critically, our estimate of the addressable market for batteries on the grid could be undermined by the feedback effects from the deployment of even small amounts of storage.
    • In the five competitive wholesale markets that serve states where generation has been deregulated, the bulk of the potential consumer savings could be achieved with a very small deployment of storage capacity. Assuming the batteries were dedicated solely to shaving demand during the highest priced 4 hours each day, only 5 GWh of capacity might be required to realize the bulk of the benefits available from storage – eroding the returns on further investment in storage.
    • Similarly, the market commercial storage is an artifact of utilities’ rate design, and specifically of demand charges calculated on the basis of peak load. The market could disappear, therefore, if utilities were forced to re-design electricity rates over time to mitigate the impact on revenues of deployments of storage and distributed solar by utility customers. Customer-sited batteries and distributed solar will reduce utilities’ revenues but not the fixed cost of the grid (at least for many years). Rather than see their cost recovery and earned ROEs eroded, utilities will seek a rate re-design to restore revenue to allowed levels, likely transitioning, like gas utilities, to fixed monthly connection charges. Such reforms are underway in several states.
  • For battery manufacturers, including TSLA, even a rapid roll out of grid storage is likely to have a limited market impact. Assuming that, after feedback loops, the U.S. market of grid storage is 50 GWh, and that this capacity is deployed over the next 10 years, it would add only 5 GWh to average annual sales. By comparison, Tesla’s Gigafactory alone will capable of producing 55 GWh of batteries annually when it comes online next year, roughly doubling existing global capacity.

Exhibit 1: Heat Map: Preferences Among Utilities, IPP and Clean Technology

Source: SSR analysis

Table of Contents

Estimating the Addressable Market for Batteries on the Bulk Power System 3

Feedback Loops from Battery Deployment that Could Limit the Market for Storage on the Grid 7

The Market for Batteries Among Residential Consumers of Electricity 11

Battery Demand Among Large Commercial and Industrial Electricity Consumers 13

The Growth of Grid Storage and the Global Market for Large Format Batteries 15

Details

1. Estimating the Addressable Market for Batteries on the Bulk Power System

The maximum addressable market for electric energy storage on the U.S. power grid can be estimated in variety of ways. The simplest is to assume that all the peaking capacity on the U.S. power grid is replaced over time with batteries.

If we define peaking units as those with a capacity factor of 15% or less, then there are ~175 GW (175,000 MW) of peaking capacity on the U.S. power grid.[1] If these units were to be replaced with batteries capable of four hours of continuous discharge, the total capacity of these batteries would be ~700 GWh (175 GW x 4 hours) or 700,000 MWh.

Unless battery costs decline dramatically, however, regulated utilities and competitive generators will not deploy batteries as peaking capacity, suggesting that the economic market for batteries on the power grid is far smaller. At current prices, batteries remain a far more expensive source of peak hour electricity than new conventional gas turbine peaking plants, let along existing peaking plants. Regulated utilities are thus unlikely to deploy batteries as a substitute for conventional gas turbine peakers. This is illustrated in Exhibit 2, which compares the all-in cost of electricity from lithium ion batteries and a conventional gas turbine peaker at capacity factors of 5%, 10% and 15%. (See our note of February 16, 2017, Electric Energy Storage and the Bulk Power System: An Introduction to the Applications and Impact of Storage).

Exhibit 2: Cost Comparison of Lithium Ion Batteries and Gas Turbine Generators Deployed as Peaking Capacity (Levelized Cost of Energy in $/MWh)

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Source: Energy Information Administration, Capital Cost Estimates for Utility Scale Electricity Generating Plants, November, 2016; Lazard and Enovation Partners, Lazard’s Levelized Cost of Storage – Version 2.0, December 2016; SNL and SSR analysis

The above comparison, however, understates the economic attractiveness of batteries, which can be operated in ways that conventional peakers cannot. Critically, gas turbine peakers have a far higher variable cost of operation than do batteries, limiting their hours of operation to the highest priced hours of the year. At a gas price of $3.00/MMBtu, a gas turbine peaker with a heat rate of 10 MMBtu/MWh incurs a fuel cost of $30.00/MWh; with the addition of non-fuel variable operation and maintenance expense, including start-up costs, a gas turbine is unlikely to be dispatched unless the power price rises above $35.00/MWh. By comparison, the average on-peak power prices in CAISO, ERCOT, SPP, MISO, PJM, and the New York ISO ranged between $24.00 and $32.00/MWh in 2016 (Exhibit 3); only in ISO New England did on-peak power prices average $35.00/MWh. It is not surprising, therefore that the average capacity factor of gas turbine peakers in the U.S. is only 7%. During many of the hours that they do run, moreover, gas turbines are the marginal, price-setting units on the system, limiting the gross margin they can earn.

Exhibit 3: Average Peak and Off-Peak Power Prices by Region in 2016 ($/MWh)

Source: SNL Energy and SSR analysis

By contrast, the variable operating of a battery is the cost of purchasing power during the lowest priced hours of the day, adjusted for electricity losses across the charge/discharge cycle (less than 10% for a lithium ion battery). As illustrated in Exhibit 3, off-peak power prices across the seven principal U.S. RTOs averaged $24.00/MWh or less in 2016, and averaged as little as $13.00 to $19.00/MWh is markets with abundant wind resources, such as SPP and ERCOT. The variable operating cost of lithium ion batteries in these markets thus ranges, on average, from $14.50 to $26.50/MWh. As a result, it is profitable to charge and discharge batteries during every day of the year, the only exception being days when the difference between the lowest and highest priced hours of the day is less than 10%. A lithium ion battery that cycled on a daily basis, buying power during the four lowest priced hours of the day and selling it during the four highest priced hours of the day, would have an expected capacity factor of 16.7% (4/24), or more than twice that of the average gas turbine. During these hours, moreover, the batteries could expect to be consistently profitable on a cash basis; we estimate that their arbitrage margins would average over $7.00/MWh over the course of the year, even allowing for cycling losses.

Despite these advantages, our analysis suggests that the profits available from daily energy arbitrage are nowhere near sufficient to recover the cost of a grid scale battery. In Exhibit 4 below, we compare the annual revenue required to recover the cost of a new grid scale battery, including capital costs and fixed operation and maintenance expense, (expressed in $/kW-year; see the left hand column of the table) with the net annual revenue that a battery could earn by charging during the four lowest priced hours of each day and discharging during four highest priced hours, 365 days a year. As Exhibit 4 illustrates, in 2016 the net revenues of the battery from energy arbitrage would have covered only 5% to 13% of the annual revenue required to recover the cost of the battery.

Exhibit 4: Percentage of Batteries’ Annual Revenue Requirement Recoverable from Energy Arbitrage in Various Regional Energy Markets, 2016

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Source: SNL, SSR analysis

In summary, batteries are unlikely to be deployed by regulated utilities as a substitute for gas turbine peakers, nor by independent generators, operating in regions of the country where generation has been deregulated, seeking to profit from energy arbitrage. Absent a dramatic decline in battery prices, therefore, the economic market for grid scale batteries is unlikely to approach our 175 GW estimate of the maximum addressable market for utility scale batteries on the bulk power systems.

There may be other ways, however, for batteries to be rolled out on the grid. For example, we see a compelling case for utility regulators to encourage the deployment of grid storage in states where power generation has been deregulated, and consumers pay electricity rates that reflect the wholesale price of power. In competitive power markets, the price of electricity reflects the variable cost of operation of the last unit dispatched to meet demand. Power supply curves tend to be extremely steep at very high levels of demand, or put another way, supply is highly inelastic relative to price during peak demand hours (Exhibit 5). As a result, small increases in demand result in disproportionate increases in the marginal cost of supply and thus in the prevailing market price of power. The impact of very high on-peak prices on the cost of procuring energy for load, and thus on customers’ bills, is aggravated by the fact that these prices prevail during precisely those hours when the demand for power is greatest.

Under extreme weather conditions, the combination of steep supply curves and very high levels of demand can result in a tiny number of high priced hours being responsible for a large percentage of the total annual cost of supplying load. One such example occurred in 2011 in Texas, when the state suffered 100 days when the temperature broke 100 degrees Fahrenheit. In ERCOT in 2011, during the highest priced 24 hours of the year, the real-time price of electricity averaged ~$2,600/MWh (Exhibit 6). These 24 hours, just 0.3% of the hours of the year, accounted for 24% of the total cost of serving load in ERCOT in that year[2]

Exhibit 5: ERCOT Power Supply Curve, Summer of 2011

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Source: Energy Information Administration

Exhibit 6: Wholesale Electricity Prices in ERCOT During the Top 2% of Hours

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Source: ERCOT 2015 State of the Market Report

In markets such as ERCOT, therefore, the deployment of storage on the distribution grid, whether by regulated transmission and distribution companies or their customers, could materially reduce the marginal cost of power supply during peak demand hours and thus the total cost procuring power to serve load. We

calculate that the savings to consumers of deploying just 500 MW of storage on the ERCOT grid would have totaled $3.1 billion in 2011. On average over the five years from 2011 through 2015, we estimate that 500 MW of storage deployed on the ERCOT grid would have saved consumers ~$1.3 billion annually. (See our note of March 22, 2017, 20% Price Declines for Wholesale Power? The Compelling Social Case for Electric Energy Storage and Why Regulated Utilities Are Likely to Roll It Out First.)

We believe the substantial savings to electricity consumers from the deployment of even limited amounts of storage will motivate state utility regulators to encourage investment in storage by regulated utilities. The California Public Utilities Commission, for example, has required the state’s investor-owned utilities to deploy 1,325 MW of storage by 2020. We expect regulators in New England, New York and the Mid-Atlantic to follow California’s example. Massachusetts is currently considering policies to encourage the deployment of 600 MW of storage by 2026 and Maryland just passed a tax credit for distributed electric storage.

A second approach for estimating the demand for storage on the grid, therefore, is to exclude states where generation remains regulated, and utilities are unlikely to deploy high cost batteries on the grid, and focus on those where generation has been deregulated, and where regulators may encourage the deployment of batteries by utilities and their customers. In these states, bulk power is procured for consumers, either by their distribution utilities or by competitive electricity retailers, in competitive wholesale markets operated by regional transmission organizations (RTOs) and independent system operators (ISOs). The question thus becomes: How much storage capacity might be deployed in the RTOs and ISOs that supply electricity to consumers in deregulated states?

The combined peaking capacity of the five competitive wholesale power markets that serve states that have deregulated generation is ~84 GW (Exhibit 7).[3] Were regulated utilities in these states, or their customers, to deploy batteries on the grid with a power capacity equivalent to that of these peakers, and assuming these batteries were capable of four hours of continuous discharge, the maximum battery capacity deployed in these markets would total ~335 GWh or 335,000 MWh. This slightly less than half our prior estimate of 700 GWh of battery storage required to replace all U.S. peaking plants.

Exhibit 7: Potential Market for Grid Storage in the Five Competitive Wholesale Power Markets That Serve States That Have Deregulated Power Generation


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Source: Energy Information Administration, SNL, SSR analysis

Feedback Loops from Battery Deployment that Could Limit the Market for Storage on the Grid

Critically, the estimates we have provided above of the addressable market for batteries on the grid could be undermined by the feedback effects from the deployment of even small amounts of storage. The bulk of the economic benefit to consumers of electric energy storage on the grid, as measured at least by the reduction in the cost of procuring power in the wholesale markets to serve peak load, could be achieved with a far smaller deployment of storage capacity than our addressable market estimates imply. The economic market for storage, in other words, could be much smaller than the total addressable market.

For example, if the storage capacity deployed on the grid were sufficient to bring peak load down, and off-peak load up, to the point where the two are equal, on average, across all the days of the year, there would be very little difference between average peak and off-peak power prices on most days. The deployment of further storage capacity would thus be superfluous. In Exhibit 8 we present the average daily difference in load between the highest and lowest demand hour of each day for each of the competitive wholesale power markets serving states that have deregulated generation. Across these five power markets, the sum of these average gaps is 57 GW or 57,000 MW, equivalent to only two thirds of the ~84 GW of peaking capacity installed in these markets.

Moreover, to close this 57 GW average gap between the highest and lowest demand hour of each day, it would not be necessary to deploy 57 GW of storage; half this amount (~29 GW) would suffice. Charging at night when demand is lowest, these 29 GW of storage capacity would raise off-peak demand by a similar amount; discharging during the day when demand is highest, the same batteries would reduce peak demand by a similar amount. The average daily gap between peak and off-peak demand would thus be reduced to zero.

Were we then to limit the roll out of storage on the five competitive wholesale markets to only 29 GW of power capacity, and were we to assume once again that these batteries were capable of four hours of continuous discharge, the total battery capacity required would be 115 GWh or 115,000 MWh (see Exhibit 8). This is roughly a third of our prior estimate of 335 GWh, based on the assumed replacement of all the peaking capacity in these markets, and a sixth of our initial estimate of 700 GWh, which was based upon the replacement of all U.S. peaking capacity.

Exhibit 8: Potential Market for Grid Storage in the Five Competitive Wholesale Power Markets That Serve States That Have Deregulated Power Generation, Based on the Average Gap Between Highest and Lowest Load


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Source: Energy Information Administration, SNL, SSR analysis

More detailed modeling of loads and prices in the principal U.S. power markets suggests that an even smaller amount of battery capacity might suffice. We have modeled the impact on generator revenues of deploying batteries dedicated solely to the arbitrage of peak/off-peak energy pricing in each of the principal U.S. RTOs. Allowing for 10% electricity losses through the charge/discharge cycle, we assumed these batteries would charge for 4.4 hours each night during the hours when power prices are lowest, and discharge during the 4.0 hours each day when power prices were highest. To estimate how the daily charging and discharging of each 100 of MW battery capacity would affect peak and off-peak prices, we assumed that power prices would fall during the hours that batteries were being discharged to the average level prevailing when power demand was 100 MW lower, and that power prices would rise during the hours that the batteries were being charged to the average level prevailing when demand was 100 MW higher. (Given that power prices reflect numerous market factors in addition to demand, including the prevailing prices of coal and gas, seasonal swings in the availability of hydroelectric and other renewable resources, and the seasonal maintenance schedule of large thermal power stations, we estimated the price impact of 100 MW of storage on a month by month basis.)

As noted above, power supply curves are extremely steep at very high levels of demand. As a result, small increases in demand result in disproportionate increases in the marginal cost of supply and thus in the prevailing market price of power. The deployment of relatively small amounts of storage, discharged during on-peak hours, reverses this dynamic, achieving a small reduction in peak hour demand but a large decrease in marginal cost and thus in the market price.

Conversely, during off-peak hours, when demand is low and low cost generation resources are abundant, power supply curves tend to be quite flat. As a result, it is possible to charge batteries during these hours with little upward pressure on off-peak power prices.

Simulating the impact of deploying battery storage in the ERCOT power market over the last five years, for example we found that 500 MW of storage, in a market where average daily peak demand is ~44,000 MW, would reduce the average daily peak hour price of electricity by 37%. Increasing the amount of storage above 500 MW had very limited incremental impact on peak hour prices; deploying 1000 MW of storage, for example, would have reduced the average daily peak hour price by just 39%.

Our analysis of the impact of storage on peak power prices in PJM produced a similar result. Over the last five years in PJM, by our estimate, the deployment of 500 MW of storage would have reduced the average daily peak hour price of electricity over the last five years by 8%; with 1000 MW of storage, the reduction in the average daily peak hour price increases to just 10%.

In the smaller ISOs, such as ISO New England and the New York ISO Zone J (New York City), are analysis suggests that even 500 MW of storage is more than is required to achieve the bulk of the potential reduction in on-peak prices in these markets; rather, the deployment of as little as 100 MW of storage may be most cost effective.

When we examine the impact of storage on generator revenues, we find that the depressing effect of storage on peak power prices, and its far more limited upward pressure on off-peak prices, is accentuated by the fact that the volume electricity sold during the highest demand hours of the day is on average some 40% greater than the volume sold during the lowest demand hours. Storage thus exerts significant downward pressure on generators’ peak hour revenues, depressing prices significantly during those hours when the highest volume of electricity is sold, while putting far less upward pressure on off-peak prices, when sales volumes are materially lower.

In Exhibit 9, we quantify what these reductions in peak hour prices, and increases in off-peak prices, imply for generators’ annual revenues: the red columns illustrate the reduction in generator revenues from the discharge of storage during the four highest demand hours of the year and the blue columns show the increase in generator revenues caused by the charging of storage during the four lowest demand hours of the year. Our analysis suggests that the roll out of very modest amounts of storage – only 1,300 MW in total — could achieve significant reductions in generator revenues, and commensurately large consumer savings, in all five RTOs. The biggest impact would be felt in ERCOT and PJM: over the five years 2011-2015, we calculate that the savings to consumers in ERCOT of deploying only 500 MW of energy storage would have been ~$1.3 billion annually, while consumers in PJM would have saved $0.6 billion annually.[4]

Exhibit 9: Change in Cost of Procuring Peak and Off-Peak Power to Serve System Load Following Deployment of Battery Storage, per RTO ($ millions)

Source: SNL, SSR analysis

In summary, our analysis suggests that the deployment of 1,300 MW of dedicated storage capacity across the five RTOs could achieve the bulk of the potential reduction in generator revenues in these markets. Assuming these batteries would be capable of four hours of continuous discharge and were dedicated to the purpose of shaving demand during the highest priced 4 hours each day, only 5 GWh of battery capacity might be required to realize the bulk of the benefits available from storage.

In conclusion, we expect the rollout of relatively small amounts of storage on the grid to erode the incentives for further battery deployment. As we have seen, replacing the 175 GW of peaking capacity on the U.S. power grid with batteries capable of four hour discharge implies a maximum total addressable market for grid storage of up to 700 GWh. Unless battery costs decline dramatically, however, regulated utilities and competitive generators will not deploy batteries as peaking capacity. Measured by the cost of energy supplied during peak hours, grid scale batteries cost 3 to 4x as much as new conventional gas fired peakers (Exhibit 2), discouraging their use by regulated utilities. And competitive generators cannot recover the cost of a battery from the arbitrage profit to be had by buying electricity off peak and selling it on peak in the wholesale power market (Exhibit 4).

Rather, the rollout of batteries may occur primarily under the aegis of state regulators in states that have deregulated generation, and where utilities procure electricity for their customers in wholesale markets where prices reflect the marginal cost of supply. In this context, the deployment of batteries by transmission and distribution utilities and their customers can reduce the marginal cost of supply during peak hours, decreasing wholesale prices and thus consumers’ electricity bills. If so, this implies a much smaller market for storage on the grid. In the five wholesale power markets serving states that have deregulated generation, the deployment of just 29 GW of storage would be sufficient to close the gap between peak and off peak power demand, tending to equalize peak and off peak power prices and thus eliminating the incentive for further storage. An addressable market of only 115 GWh (29 GW x 4 hours) may therefore be more realistic (Exhibit 8). And even this more most modest estimate may materially overstate the potential for batteries to be deployed economically on the grid; a detailed analysis of power demand and prices in these five wholesale markets suggests that only 5 GWh of battery capacity may be sufficient to the realize most of the economic benefit from the deployment of storage on the grid (Exhibit 9).

2. The Market for Batteries Among Residential Consumers of Electricity

A second potential market for electric energy storage on the grid is among residential electricity consumers. In October of last year, Tesla, in collaboration with solar rooftop installer SolarCity (which it subsequently acquired), introduced its PowerWall 2 residential battery, which can store 14 kWh of energy. The battery is capable of delivering 5 kW of continuous power, with a peak discharge of 7 kW – rendering it capable of meeting the peak power demand of an average U.S. residence.

We believe the market for such a battery to be inherently limited, however. The average U.S. residence consumes ~11,000 kWh of electricity per year, or the equivalent of 1.25 kW per hour on average across the

year.[5] A 14 kWh PowerWall battery would thus provide ~11 hours of back-up power to an average U.S. home; two batteries would provide back-up electricity for nearly a day. As a back-up power supply in the event of prolonged power outage following a natural disaster, even a two battery system would be of little use. When Hurricane Sandy hit the East Coast in 2013, 2.2 million electricity consumers were without power for a week or more; the 2012 derecho storm across the Ohio River Valley left a million people without power for four days or longer; and Hurricane Irene in 2011 left 650,000 people without power for three days or more. Residential or small commercial consumers concerned about maintaining power supply in similar circumstances would more likely be drawn to a back-up diesel or gas fired generator, which can provide continuous power indefinitely as long as fuel is available. The capital cost of such back-up generators is materially lower than that of PowerWall batteries: despite providing power for less than a day, a back-up energy system comprising two PowerWall batteries costs 3.5x as much to procure and install as an 8 kW Generac home generator.

Back-up power is not the only potential application of a residential storage system, however. Certain states, including California, have introduced time of use (TOU) electricity rates for residential consumers. These rates vary across the hours of the day, and across the seasons of the year, to reflect daily and seasonal swings in wholesale power prices. The highest priced hours tend to occur during the afternoons and early evenings of the working week, while the lowest priced hours occur at night and on weekends. Faced with TOU rates, residential consumers may be tempted to deploy home battery systems to arbitrage the difference between peak and off-peak power prices. As explained below, however, our analysis suggests that, at current battery and power prices, the arbitrage of TOU rates would not be economic.

In a February 2017 report[6], the National Renewable Energy Laboratory (NREL) estimated the installed cost of a 5 kW, 20 kWh lithium ion residential battery to be ~$25,500, or the equivalent of $1,275/kWh. Lazard and Enovation Partners, in a December 2016 analysis,[7] estimated the cost of a residential lithium ion battery system to be in the range of $890 to $1,475/kWh, the midpoint of which ($1,183/kWh) is similar to NREL’s estimate. To calculate the homeowner’s annual capital cost of installing such a battery, we have amortized the $25,500 installed cost over an assumed 10 year useful life at a weighted average pre-tax cost of capital of 10%. (Our cost of capital estimate may be generous; it is equivalent to the pre-tax cost of capital to a regulated electric utility, and is likely lower than the cost of capital available to a solar rooftop installer or residential electricity consumer.) Based on these assumptions, the annual capital charge borne by residential customer for the 5 kW battery would be ~$4,150.

To estimate the cost of charging the battery, we have used the average off-peak TOU rate charged by Southern California Edison to its residential customers, $0.134/kWh. If the 5 kW battery is discharged for four hours each day, its annual output would be 7,300 kWh. Allowing for 8% electricity losses across the charge/discharge cycle, this implies the need to purchase 7,935 kWh at a total annual cost of $1,060.

To recover the annual capital cost $4,150 plus the annual charging cost of $1,060, the homeowner must realize an annual savings of $5,210 on his electricity bill by using the output of his battery rather than purchasing electricity from the utility at peak hour TOU rates. This works out to $0.71/kWh (equivalent to the sum of $4,150 and $1,060 divided by the 7,300 kWh discharged by the battery each year). But the annual average on-peak rate charged by Southern California Edison is only $0.345/kWh, implying that, at current prices for residential batteries, arbitraging peak and off-peak TOU rates is far from economic. For TOU arbitrage to become economic in southern California, the installed cost of batteries for homeowners would have to fall below $450/kWh.

A final possibility is that residential storage systems could be marketed to homeowners who have already installed rooftop solar systems, but have subsequently been denied the ability to sell the excess generation of the system back to the grid. Under these circumstances, storing the excess output of the solar array for use during the evening hours would allow the homeowner to reduce his purchases of electricity and thus his utility bill.

Installing a battery to store excess solar generation might also be of interest to rooftop solar owners that are allowed to sell their excess power output to the grid but are required to do so at TOU rates – a requirement imposed by the state of California on any homeowner planning to install a new rooftop solar system. As noted above, currently, daytime TOU rates in southern California average $0.345/kWh, so this requirement is not an onerous one. In the future, however, it may be. The rising supply of utility and rooftop solar generation in California is increasingly being reflected in extremely low power prices during the middle hours of the day when solar generation is highest. [8] If in future these low daytime wholesale prices are reflected in similarly low daytime TOU rates, rooftop solar owners may find it attractive to store their excess generation during the day for sale in the evening, when wholesale prices are much higher.

To analyze the economics of residential electricity storage under these circumstances, we have modified slightly the assumptions set out above. The owner of a typical 6 kW rooftop solar system might install only a 3 kW, 12 kWh battery to store just that portion of his solar generation that exceeds the requirements of his home during the hours from 10 AM to 2 PM, when the sun is at its highest. Assuming a capital cost of $1,275/kWh, the installed cost of the 12 kWh battery would be $15,300; amortized over ten years at a discount rate of 10%, the annual capital cost of the system would be $2,484. Assuming the battery is charged and discharged daily, the annual output of such a battery would be 4,380 kWh. As the battery is to be charged from the excess generation of the rooftop solar system, and this excess output cannot be sold back to grid or must sold at extremely low TOU rates, the charging cost of the battery may be assumed to be zero. Dividing the annual capital cost of $2,484 by the battery’s annual output of 4,380 kWh implies that the homeowner would need to realize savings of at least $0.567/kWh to recover his costs. Unfortunately, this breakeven price is approximately two thirds higher than Southern California Edison’s average on-peak price for electricity ($0.345/kWh) at which the homeowner could otherwise purchase power for his home in the evening.

In the above case of a homeowner unable to sell his excess solar generation to the grid, the installed cost of storage would only need to fall below $750/kWh for batteries to be economic, suggesting that residential storage could become attractive, under these limited circumstances, over the next five years. However, we expect this to be a very limited market: the vast majority of rooftop solar is installed precisely because net metering renders it economic to do; without net energy metering, homeowners have no economic incentive to install these systems. Also, the economics in our example benefit from California’s high peak hour rates for residential customers; not all states have residential TOU pricing and those that do tend to have lower rates.

In summary, given current battery prices and capabilities, we see little demand for batteries among residential electricity consumers, whether for use as a back-up power supply, to arbitrage between peak and off-peak TOU rates, or to store excess solar generation at mid-day for use during the evening hours.

On the other hand, we believe residential batteries can be a high-end consumer product, carving out a small niche in the residential backup power market, driven by design, marketing and advertising. After all, the Tesla PowerWall does look cool hanging on the side of your house.

3. Battery Demand Among Large Commercial and Industrial Electricity Consumers

Yet another potential market for batteries on the grid is among commercial and industrial consumers of electricity, whose peak demand for power is materially higher than that of residential consumers. The larger scale of their power purchases allows commercial and industrial consumers to install substantially larger batteries at a much lower per kWh cost.

To illustrate the relative scale of residential and commercial loads, the peak power demand of an average U.S. residence is ~6 kW. By contrast, California’s largest electrical utility, Pacific Gas & Electric, classifies commercial customers that draw 20 kW to 200 kW of power from the grid at peak as “small,” those drawing 200 kW to 500 kW as “medium”, and those drawing over 500 kW as “large.”[9] The utility’s very largest industrial customers would draw more than 1000 kW of power from the grid at peak.

Given the scale of these customers’ peak demand for power, utilities commonly bill their commercial and industrial customers not only for the kWh of electricity they consume but also for their peak demand for power from the grid. This “demand charge” is expressed in $/kW of peak demand. Peak demand is measured monthly, and is usually based on the customer’s maximum draw of power from the grid over any 15 minute interval during the month.[10]

The appeal of batteries to commercial and industrial customers with demand-based utility rates thus lies in the potential to shave their peak draw of power from the grid by relying on the battery during their highest demand hours. By reducing their power draw from the grid during the highest 15 minute interval, customers with batteries can cut their demand charges accordingly.

Batteries will be particularly attractive to establishments whose demand charge is high due to a short-lived spike in demand which can be eliminated with a short burst of power from a battery, allowing a smaller capacity battery (measured in kWh) to be purchased. By way of example, let’s say a tanning salon generates a surge in power demand as customers tumble in for an hour or two after work; as they clear out, the establishment’s power demand drops sharply. To reduce its peak demand for power by 25 kW, the salon might invest in a 50 kWh battery (a 25 kW battery capable of 2 hours of continuous discharge). By contrast, the owner of the office building next door to the tanning salon must light and cool the building throughout the working day, resulting in a prolonged peak in power demand. To reduce the peak demand of his building by 25 kW, the landlord would have to invest in a much larger battery, one capable of discharging 25 kW of power for eight hours, or a 200 kWh battery. To achieve the same reduction in demand charge, in other words, the landlord must invest in a battery 4x the size of the salon’s.

To assess the attractiveness of batteries to commercial electricity consumers with different load profiles, we have modeled the case of a hotel seeking to reduce its peak demand for power by 100 kW for two hours in the evening. We have assumed a capital cost for the battery of $600/MWh, reflecting the lower end of the cost range for commercial scale batteries estimated by Lazard and Enovation Partners in their December

2016 analysis.[11] Given the need for a 200 kWh battery (100 kW of power for two hours), this implies a capital outlay of $120,000. Amortized over the 10 year life of the battery at an assumed pre-tax weighted average cost of capital of 10%, the corresponding annual capital charge is ~$19,500. In addition, the battery owner would bear the cost of the electricity losses incurred by charging and discharging the battery on a daily basis; we assume an 8% electricity loss for the lithium ion battery across the cycle. Assuming the battery is charged and discharged daily, producing some 73,000 kWh annually (100 kW x 2 hours per day x 365 days) these losses would amount to ~6,350 kWh per year.

Once again, we have used for purposes of our analysis the rate structure of Southern California Edison, which charges its small commercial customers an average demand charge of $21.50/kW and an average energy rate of $0.075/kWh. By reducing its peak demand by 100 kW, the owner of the commercial establishment saves $2,150 per month or ~$25,770 per year. This is more than sufficient to offset the ~$20,000 total annual cost of the battery, comprising (i) the annual capital cost of $19,500 and (ii) the $480 annual cost of the electricity losses incurred in charging and discharging it (equivalent to 6,350 kWh of electricity losses at an average energy rate of $0.075/kWh).

As pointed out earlier, however, the economic attractiveness of investing in battery storage deteriorates as a function of the duration of the consumer’s peak demand for power. Let’s compare the case of a hotel with a two hour peak in power demand in the evening to that of an office building whose peak demand lasts for the eight hours of the working day. For the office building, the same target reduction in peak demand of 100 kW would require the purchase of an 800 kWh battery, four times the size of our previous example. The annual capital cost of the battery thus quadruples to $78,000, as does the cost of the energy losses incurred in charging and discharging it on a daily basis, rising now to $1,920 annually. The total annual cost of the battery thus rises to ~$80,000. Yet the office building still saves the same amount of money as did the hotel; by reducing its peak demand by 100 kW, it saves only $21.50 per month ($0.215/kW x 100 kW) or ~$25,770 per year. In this case, installing the battery is a clearly a money losing proposition.

Finally, we note that customers of most other utilities, with lower demand charges, would likely need battery prices to fall further for even a two hour deployment of storage to be economic.

In summary, batteries are far more likely to prove economic investments to commercial electricity consumers than to residential ones, reflecting the utility practice of charging such customers based on their peak demand. At the current cost of lithium ion batteries, we have seen that commercial consumers whose peak power demand is of short duration (2 hours or less) could recover the cost of a battery through the reduction in their demand charge, at least in states where these charges are high, such as California. For commercial consumers whose peak demand is of longer duration, however, batteries quickly become uneconomic. Industrial consumers, whose demand tends to be flat across two or three production shifts a day (16 to 24 hours daily) will find it very difficult to realize an economic benefit from deploying batteries. The expansion of the battery market to include these customers will require a material reduction in battery costs (approximately two thirds in our example of an office building seeking to shave eight hours of peak demand).

How large might the addressable market for storage be among commercial consumers of electricity in the United States? Over the last five years, the commercial sector has contributed ~36% of total U.S. electricity demand. Peak power demand in the U.S. is approaching 860 GW; assuming that the commercial sector accounts for a similar share of peak load, we can estimate peak commercial demand for power at ~310 GW. While the typical duration of peak demand among commercial consumers is 8 to 10 hours, we have seen that deploying storage to reduce peaks of this duration is uneconomic. Having examined data on the load profile of large commercial electricity consumers, however, we estimate that deploying just 2 hours of storage capacity, to supply only the very highest demand periods of this 8 to 10 hour extended peak, could result in a 5% reduction in the peak demand of the sector. A 5% reduction in the peak demand of the commercial sector for 2 hours a day results in a potential market size of 31 GWh (310 GW of peak demand x 5% reduction in peak demand x 2 hours). At current battery prices, however, the deployment of storage by commercial electricity consumers will likely be limited to the states like California with higher electric utility rates.

In our analysis of storage on the bulk power grid, we saw that the deployment of relatively limited battery capacity has the potential to close the gap between peak and off peak demand, tending to equalize peak and off peak power prices and thus eliminating the incentive for additional storage. A similar feedback loop may limit the market for storage among commercial electricity consumers.

In the short run, the growing deployment of battery storage by commercial electricity consumers seeking to reduce their demand charges will erode the revenues of the utilities that supply them. Because the fixed costs of the grid (i.e., fixed operation and maintenance expense, depreciation expense, interest expense and return on equity) are not reduced in the short term by customers’ deployment of storage, this erosion of revenues will tend to drive utilities’ earned ROEs below their allowed levels. In the medium term, the affected utilities will seek to recover these lost revenues, and restore their ROEs to allowed levels, through changes in their rate design, for example by introducing a fixed monthly charge for grid access to replace demand charges levied in proportion to peak load. This type of rate design is common among gas utilities. The rollout of batteries to commercial electricity consumers, in other words, could become a victim of its own success, with utilities’ revenue losses forcing a rate re-design that eliminates the incentive to install batteries to shave peak demand.

4. The Growth of Grid Storage and the Global Market for Large Format Batteries

What then are the implications of the growth of grid storage for the global market for large format batteries? In the long run, given the scale of the potential market for electric vehicle batteries, we expect the rollout of batteries on the grid to be of limited consequence.

The addressable market for electric vehicle batteries in the United States is staggeringly large relative to the scale of the electric energy storage that could be deployed on the U.S. power grid. The U.S. vehicle fleet comprises 260 million cars, trucks and buses. Assuming each were equipped with a battery with a range of 300 miles per charge and an average fleet energy efficiency of 2.6 miles per kWh, the potential scale of the U.S. market for electric vehicle batteries can be estimated at 30,000 million kWh (260 million vehicles x 300 miles per charge divided by 2.6 miles/kWh) or 30,000 GWh. By contrast, our estimate of the total addressable market for storage on the grid – assuming the nation’s entire 175 GW of peaking capacity were replaced with batteries capable of four hour discharge – is only 700 GW, or 2.3% of the addressable market for EV batteries. Recognizing the fact that batteries are still far too expensive to be attractive to either regulated utilities or competitive generators as sources of peaking capacity (see Exhibits 2 and 4), we believe the economic market for grid storage will not exceed 115 GWh, or just ~0.4% of the potential market for EV batteries in the U.S. And given the fact that small amounts of storage can suppress peak power prices, eroding the incentives for further deployment, the actual deployment of storage on the grid is likely to be far smaller.

For battery manufacturers, including TSLA, even a rapid roll out of grid storage is likely to have a limited market impact. Assuming that, after feedback loops, the U.S. market for grid storage is 50 GWh, and that this capacity is deployed over the next 10 years, it would add only 5 GWh to average annual sales. By comparison, Tesla’s Gigafactory alone will capable of producing 55 GWh of batteries annually when it comes online next year, roughly doubling existing global capacity.

©2017, SSR LLC, 225 High Ridge Road, Stamford, CT 06905. All rights reserved. The information contained in this report has been obtained from sources believed to be reliable, and its accuracy and completeness is not guaranteed. No representation or warranty, express or implied, is made as to the fairness, accuracy, completeness or correctness of the information and opinions contained herein.  The views and other information provided are subject to change without notice.  This report is issued without regard to the specific investment objectives, financial situation or particular needs of any specific recipient and is not construed as a solicitation or an offer to buy or sell any securities or related financial instruments. Past performance is not necessarily a guide to future results.

  1. We have measured the capacity factor of these plants over the last two years in order to avoid categorizing as peakers plants that have experienced long maintenance outages that have materially reduced their hours of operation.
  2. Calculated as the product of the electricity sold in each hour and the real time price during that hour. Utilities and power retailers may have hedged their cost of procuring electricity by entering into bilateral power purchase agreements with generators at fixed prices or by entering into contracts for differences, which would reduce the short-term impact. The spike in real time prices would nonetheless have a material long term impact by driving prices higher in the forward market, as the expectations of price spikes are incorporated into forward pricing.
  3. These markets are operated by the California Independent System Operator or CAISO, the Electric Reliability Council of Texas or ERCOT, ISO New England, the New York ISO and the PJM Interconnection.
  4. Although CAISO is similar in size to ERCOT, the benefits of storage on power pricing fall off very quickly in this market. We believe this is likely a result of large and increasing penetration of solar generation throughout the day combined with a flat supply curve for the conventional generation fleet. It is possible that as solar penetration increases in other markets over time this could reduce the impact of storage. In ERCOT in 2011, 80% of the 25 highest priced hours were during summer months between 1-4pm when solar production would be high.
  5. The large difference between average and peak residential power demand reflects the periodic surges in the power demand of a home due to the operation of large electro-mechanical devices such as air conditioners, water heaters and pool pumps.
  6. . National Renewable Energy Laboratory, “Installed Cost Benchmarks and Deployment Barriers for Residential Solar Photovoltaics with Energy Storage: Q1 2016,” February 2017.
  7. . Lazard and Enovation Partners, “Lazard’s Levelized Cost of Storage – Version 2.0,” December 2016.
  8. . On March 11th of this year, for example, utility-scale solar accounted for 40% of the power produced in California; adding the output of residential and commercial rooftop generation, the EIA estimates that “the total solar share of gross demand probably exceeded 50% during the mid-day hours.” Reflecting the abundance of zero variable cost solar energy, wholesale electric prices on the California ISO dipped to zero during these hours. See David Morris, “Solar Briefly Topped 50% of California Electricity in March, Driving Rates Below Zero,” Fortune, April 8, 2017.

  9. One method of estimating the peak power demand of a 21st century commercial building is to apply a ratio of 1.5 Watts per square foot. Thus a three story, 200 foot by 200 foot office building with 120,000 square feet of floor would have an estimated peak demand of 180 kW.
  10. The level of the demand charge may vary based on the timing of a customer’s peak demand, with a higher rate applied when a customer’s peak draw of power is coincident with the peak demand for power on the grid and a lower rate applying when it is not.
  11. . Lazard and Enovation Partners, “Lazard’s Levelized Cost of Storage – Version 2.0,” December 2016. See page 39 of the report, which estimates the cost of a lithium ion battery for use by a commercial electricity consumer at $588/kWh to $1,307/kWh.
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