Energy Storage System Requirements for Grid­Scale Solar Generation

  Argonne National Laboratory April 12, 2012    

             About Argonne National Laboratory Argonne is a U.S. Department of Energy laboratory managed by UChicago Argonne, LLC, under contract DE‐AC02‐06CH11357. The Laboratory’s main facility is outside Chicago at 9700 South Cass Avenue, Argonne, Illinois 60439. For information about Argonne and its pioneering science and technology programs, see www.anl.gov.   Point of Contact Inquiries about this report may be directed to: Mark C. Petri Technology Development Director Energy Engineering and Systems Analysis Directorate Argonne National Laboratory mcpetri@anl.gov           Disclaimer This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor UChicago Argonne, LLC, nor any of their employees or officers, makes any warranty express or implied, or assumes any legal liability or responsibility for the accuracy, completeness. or usefulness of any information, apparatus, product, or process disclosed. or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of document authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof, Argonne National Laboratory or UChicago Argonne, LLC. 

 

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Table of Contents  Abstract ..................................................................................................................................... 1  1 Introduction ......................................................................................................................... 2  2 Solar Photovoltaic Resource Variability and Power Grid Storage Applications ................ 3

2.1 Short- and Long-Term Photovoltaic Variability ........................................................ 3 2.2 Solar Photovoltaic Forecasting .................................................................................. 5 2.3 Potential Energy Storage Applications for Solar Photovoltaic Power ....................... 6

3 Electric Energy Storage Technology Options ..................................................................... 8 4 Energy Storage Metrics ....................................................................................................... 11

4.1 Technical Requirements ............................................................................................. 11

4.1.1 Energy Storage Capacity and Power .............................................................. 11 4.1.2 Round-Trip Efficiency ................................................................................... 12 4.1.3 Response Time ............................................................................................... 13 4.1.4 Lifetime and Cycling ..................................................................................... 13

4.2 Cost Requirements ..................................................................................................... 14 5 Advancing Li-Ion Batteries for Stationary Applications .................................................... 16

5.1 Prospects for Low-Cost Li-Ion Batteries ................................................................... 16 5.2 Priority Activities to Advance Li-Ion Batteries for Stationary Storage ..................... 20

6 References ........................................................................................................................... 22 7 Contributors ........................................................................................................................ 25

Figures  1 Output from a photovoltaic plant located in Nevada on a sunny day and

a partly cloudy day .............................................................................................................. 3 2 Cumulative distributions of one-minute plant output ramps for six photovoltaic

plants within a region of 200 km2 in Nevada compared to total output ............................. 4 3 One-minute irradiance to a single location and to 20 bundled locations in

Kansas/Oklahoma on a day with variable conditions ......................................................... 4

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Figures (Cont.)  4 Projected hourly load and photovoltaic generation for the Arizona Public Service

Company utility in Arizona for five summer days and five winter days in 2020 ............... 5 5 Projected average relative daily profiles of load and photovoltaic generation for

the APS utility in Arizona for 2020 .................................................................................... 5 6 Energy storage capacity and power ranges anticipated for solar applications, where

P/E represents the ratio of energy storage power to energy storage capacity in h–1 ........... 12 7 Suggested energy cost objectives for photovoltaic energy storage compared with

USABC goals for vehicle applications ............................................................................... 15 8 Dramatic decrease in consumer cell cost based on a graphite-LiCoO2

Li-ion cell chemistry ........................................................................................................... 17 9 Contribution of active materials to the cost of an electrochemical energy storage

system, considering cost ranges for lithium titanate spinel anode systems, graphite-based anode systems, and advanced Li-ion systems ............................................ 18

Tables  1 Potential applications of energy storage for photovoltaic owners, system operators,

and distribution companies ................................................................................................. 7 2 Commercial and demonstrated energy storage technologies for stationary

applications ......................................................................................................................... 10

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Energy Storage System Requirements for Grid­Scale Solar Generation 

Abstract  On behalf of the U.S. Department of Energy’s Solar Energy Technologies Program office, Argonne National Laboratory has defined and assessed the technical requirements for energy storage systems optimized to accommodate the variability of solar electricity generation for grid operations. To make solar photovoltaic generation not just cost-competitive but also essentially indistinguishable from other energy sources in its operational characteristics, ways are needed to smooth out solar production over transient time frames ranging from minutes (clouds) to hours (diurnal cycles). By identifying the technical requirements for energy storage systems optimized for these applications, this report helps to prioritize research and development opportunities that address energy storage in photovoltaic applications. Photovoltaic plant owners, system operators, and distribution companies have different needs for energy storage. For instance, a photovoltaic owner is mainly concerned with meeting desired financial targets for investing in a solar photovoltaic asset, whereas a power system operator needs to reliably balance supply and demand on the grid at the lowest cost. Several energy storage technologies are being deployed or being considered for grid-scale applications, such as peak shaving, load shifting, demand response, energy arbitrage, and outage protection. Examples include pumped-hydro storage and compressed-air energy storage. This report, however, focuses on the prospects for lithium-ion battery technologies to address the energy storage needs of solar photovoltaic power applications. Lithium-ion batteries are a compelling technology for grid-scale energy storage applications, because they basically already meet the most critical requirements in terms of energy storage capacity, power, round-trip efficiency, and response time. However, current lithium-ion batteries, which are being developed and optimized mostly for transportation purposes, cannot meet the much more stringent lifetime and cost requirements of grid storage applications. Nevertheless, there is hope that these requirements could be met by following a number of promising research paths that could be applied to a battery system developed specifically for grid photovoltaic use. Research needs to target materials discovery and performance optimization and battery design and life. If such battery research were successful, solar photovoltaic generation would become much more attractive for large-scale grid deployment, since system operators would no longer have to contend with the problems and ancillary costs that arise from the minute-by-minute and hour-by-hour variability that currently typifies solar power.

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1  Introduction  The U.S. Department of Energy’s Solar Energy Technologies Program (SETP) office commissioned Argonne National Laboratory to assess and define the technical requirements for energy storage systems optimized to accommodate the variability of solar electricity generation for grid operations. The ideal goal is to make solar photovoltaic generation not just cost competitive but also essentially indistinguishable from other energy sources in its operational characteristics. Primarily, this means eliminating the burden that today’s grid operators face when dealing with variable and largely unpredictable solar photovoltaic power. Coupling energy storage to solar production offers a way to smooth out solar production over transient time frames ranging from minutes (clouds) to hours (diurnal cycles). By identifying the technical requirements for energy storage systems optimized for these applications, this report helps to prioritize research and development opportunities that address energy storage in photovoltaic applications. Several energy storage technologies are being deployed or considered for grid-scale applications, and they have been examined in several review papers [1]–[9]. This report does not attempt to repeat that effort, although it does summarize the advantages and disadvantages of various energy storage options. Instead, it concentrates on lithium-ion batteries. Argonne was asked specifically to assess whether lithium-ion battery systems (which, through significant DOE investments, have made great advances in transportation applications) could address the needs of an electric power grid that includes wide-scale adoption of solar power. Lithium-ion batteries, with their high energy density and wide range of power and energy capabilities, are an attractive option for solar power applications. This report, then, focuses on the application of lithium-ion battery technologies to solar photovoltaic power applications. Section 2 briefly describes why and how energy storage could be beneficially deployed in photovoltaic applications to manage the long- and short-term variability in power output. Section 3 provides a summary of the costs and operational characteristics of commercial and emerging energy storage technologies. Pulling from this information, Section 4 posits technical and cost metrics for solar energy storage. Section 5 then outlines the advances needed in order for lithium-ion battery technologies to meet the requirements that would make solar photovoltaic generation attractive for large-scale grid deployment.

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2  Solar Photovoltaic Resource Variability and Power Grid Storage Applications 

2.1  Short­ and Long­Term Photovoltaic Variability  Solar photovoltaic resources vary on different time scales. The very short-term variability from a single photovoltaic plant/installation depends on local weather conditions (Figure 1). The photovoltaic output tends to be almost entirely smooth on days with clear skies, and the variability in output can be very high on days with variable cloud cover.

Figure 1 Output from a photovoltaic plant located in Nevada on a sunny day (left) and a partly cloudy (right) day (sampling time: 10 seconds) [10]

Geographical aggregation effects are also important when considering photovoltaic variability. Figure 2 shows that short-term variability, measured in terms of the likelihood for one-minute ramps, is much lower for the total output from six photovoltaic plants than for the output from an individual plant. A look at the 99% percentile in the figure shows that most of the individual plants experience ramp events of more than 20% of their installed capacity for as much as 1% of the time. In contrast, the corresponding ramp event is less than 10% of installed capacity for the total photovoltaic generation from the six plants. Furthermore, the aggregate generation never experiences one-minute ramps that are more than 25% of installed capacity. The same geographic aggregation effect is illustrated in Figure 3, which shows that the variability in solar irradiance is much smaller for 20 bundled locations than for an individual site. From a power system perspective, it is mainly the net variability from all sources in the power grid that needs to be balanced, and this balance could be achieved by having large-scale aggregate storage facilities in the grid. Still, the individual photovoltaic owner might also have an incentive to install local energy storage to smooth out the variability from the specific photovoltaic facility, as further discussed below.

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Figure 2 Cumulative distributions of one-minute plant output ramps for six photovoltaic plants within a region of 200 km2 in Nevada compared to total output [11]

Figure 3 One-minute irradiance to a single location and to 20 bundled locations in Kansas/Oklahoma on a day with variable conditions [12]

The daily variability of solar photovoltaic generation is illustrated in Figures 4 and 5. They show that the solar photovoltaic output correlates relatively well with the daily variations in load. However, the peak output from solar photovoltaic generation does not fully coincide with the peak occurrence of loads in either of the two seasons. Furthermore, there is, of course, no output from solar photovoltaics during hours without daylight. The regional aggregation effect will be less prominent for daily variability, as different photovoltaic plants within a region will, more or less, follow the same daily pattern.

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Figure 4 Projected hourly load and photovoltaic generation for the Arizona Public Service Company (APS) utility in Arizona for five summer days and five winter days in 2020 [13]

Figure 5 Projected average relative daily profiles of load and photovoltaic generation for the APS utility in Arizona for 2020 [13]

2.2  Solar Photovoltaic Forecasting  The forecasting of solar photovoltaic production will play an important role in managing the power generation from photovoltaic resources, from the perspectives of both the photovoltaic owner and the power system operator. The daily profile for potential photovoltaic generation is entirely predictable, since it follows the movement of the sun. However, the impact of clouds on photovoltaic output is currently very difficult to predict. Still, the use of sky imagers and satellite observations may contribute to better short-term forecasts, and enhanced numerical weather prediction models will help improve longer-term forecasts [11]. Solar photovoltaic forecasting is an active area of research that is receiving an increasing amount of attention from DOE [14].  

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2.3  Potential Energy Storage Applications for Solar Photovoltaic Power  Energy storage could potentially be used to mitigate the impacts of both the variability in and the uncertainty of solar photovoltaic resources over both the very short (subhourly) and longer time horizons. A number of potential applications of energy storage in the context of solar photovoltaic, renewable energy, and power systems in general have been identified in the literature [1]–[6]. An overview of relevant applications is provided in Table 1. This report differentiates the potential storage needs of photovoltaic owners from those of power and distribution system operators. The photovoltaic owner is mainly concerned with meeting desired financial targets for investing in a solar photovoltaic asset (or minimizing the cost of meeting his load). The power system operator, on the other hand, is primarily responsible for operating the transmission system and balancing supply and demand in the entire grid at the lowest cost. The distribution company is in charge of planning and reliably operating the distribution grid. Photovoltaic plant owners, system operators, and distribution companies have different energy storage needs, as described in Table 1. Furthermore, the incentives for investing in energy storage depend, to a large extent, on the rules and regulations governing the electricity market and operation of the power grid. These different needs and rules give rise to several analytical challenges in terms of evaluating the optimal design and operation of energy storage systems for specific photovoltaic and grid applications. For energy storage technologies to succeed, the benefits they provide must be larger than their cost. It is clearly advantageous if an energy storage technology can provide multiple benefits (e.g., provide energy arbitrage, ancillary services, and capacity). Combining energy storage use in the grid with other applications (such as all-electric or plug-in hybrid electric vehicles in transportation) might also help address the cost-benefit challenge. When one considers the outlook for energy storage for the grid, it is important to remember that other technologies and solutions (demand response, more flexible generation, improved forecasting, better market operation and dispatch procedures, etc.) can address the same needs. For energy storage technologies to be a viable alternative, they have to be competitive with other solutions.

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Table 1 Potential applications of energy storage for photovoltaic owners, system operators, and distribution companies

Photovoltaic Scale Photovoltaic Owner Power System

Utility

(>20 MW)

Arbitrage energy prices Sell ancillary services (regulation,

spinning, non-spinning reserves) Participate in capacity markets Make photovoltaics more

predictable and thereby reduce deviation penalties

Avoid energy curtailment Meet interconnection requirements

System Operator Enable load shifting and peak shaving Provide ancillary services Improve resource adequacy Allow for more efficient dispatching Improve power quality and reliability (voltage,

reactive power, frequency, etc.) Enhance transmission system stability Defer transmission investments Provide black start capability (i.e., start without

relying on network)

Commercial

(0.1–5 MW)

Arbitrage energy prices Reduce peak load charges by

photovoltaic-demand management Sell ancillary services (regulation,

spinning and non-spinning reserves) Protect against outages Expand the use of microgrid and

enable islanding

Distribution Company Enable load shifting and peak shaving Defer distribution investments Provide ancillary services Improve power quality and reliability

Residential

(5–25 kW)

Arbitrage energy prices Reduce peak load charges by

demand management Protect against outages Expand the use of microgrid and

enable islanding

Distribution Company Enable load shifting and peak shaving Defer distribution investments Improve power quality and reliability

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3  Electric Energy Storage Technology Options  A broad range of energy storage technologies have been evaluated for power systems and photovoltaic grid integration applications. Table 2 provides a summary of energy storage technologies capable of storing and delivering energy at a scale necessary for peak shaving, load shifting, demand response, energy arbitrage, and outage protection. Not included in this table are storage technologies (e.g., flywheels [15], [16], capacitors, and ultracapacitors) that are more suitable for power-dominated applications (e.g., voltage and frequency regulation) [1]. Pumped-hydro is the only energy storage technology that is now being implemented at a large scale. With existing installations totaling 127,000 MW, it makes up 99% of all storage capacity on the grid. Because of the economy of scale and uncertainties in siting associated with this technology, it is a less attractive option for energy storage when it is coupled to individual residential, commercial, or utility-scale photovoltaic systems. Furthermore, the water resources needed for pumped-hydro storage are geographically restricted and may not be available, especially in the regions that are most suitable for solar power generation. Two commercial-scale compressed-air energy storage (CAES) systems have been reliably operating for several years [1], [17], [18]. The wider-spread deployment of CAES has been limited by cost. Existing CAES technologies are also plagued by their low efficiencies and reliance on being coupled to fossil fuel combustion. However, resources are being directed to develop next-generation CAES technologies that employ advanced compressor and turbine designs. Electrochemical systems make up the remaining storage technologies summarized in Table 2. These systems are generally very efficient, with Li-ion and lead-acid systems operating at round-trip efficiencies of greater than 85%. Flow batteries are attractive because they can be designed separately for power and energy requirements, unlike conventional enclosed batteries. In theory, independent designs for power and energy should lead to the lowest possible system cost. The development of novel flow chemistries is an ongoing process that may one day lead to a more cost-effective system. The lower energy density of flow batteries, however, leads to higher-than-desired costs. Lead-acid and sodium-sulfur technologies are commercially available, and both can be considered mature. The success of these systems for grid storage has been hampered by the poor lifetimes of the lead-acid systems and the high costs of the high-temperature sodium-sulfur systems. Although advances continue to be made, particularly with regard to lead-acid batteries, the maturity of these technologies makes it unlikely that significant reductions in cost or dramatic advances in their lifetimes could be achieved. Li-ion batteries, commonly used in portable electronics and now in transportation applications as well, are still considered too costly for large deployments of load shifting. Currently, however, their use is being demonstrated to meet the technical challenges of managing grid reliability and integrating renewable technologies. The potential for future Li-ion batteries to meet the stringent cost and lifetime objectives associated with grid-scale energy storage is discussed in detail in Section 5.1.

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Other storage technologies that are in various stages of research and development include superconducting magnetic energy storage [19], thermal energy storage, fuel cells, and hybrid energy systems. Electrochemical storage technologies under development for grid applications include these:

Enclosed battery chemistries (e.g., Na/NiCl, Fe/air [20], and liquid metal [21]),

Flow battery chemistries (e.g., Zn/air, H/Br [20], ZnMnO, Fe/Cr, and flowable Li-ion), and

Capacitors (e.g., lead-carbon asymmetric [3]).

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Table 2 Commercial and demonstrated energy storage technologies for stationary applications

Energy Storage Technology Maturity*

Efficiency*in %

Lifetime*in Cycles

Installed Capacity* in MWh (Power in MW)

Cost* in $/kWh ($/kW)

Advantages and Current Limitations

Pumped hydro Commercial 76–85 >13,000 (50 years)

1,680–14,000 (280–1,400)

250–430 (1,500–4,300)

Maturity of technology, long life, large capacity, fast response time High upfront capital costs, siting constraints, environmental impacts

Compressed air – underground

Commercial (+ demonstration of second- generation technology)

40–54 >13,000 1,080–3,600 (135–180)

60–125 (960–1,250)

Fast response time, potentially large capacity Low efficiency, need for fuel combustion, siting constraints, need for long lifetimes to reduce costs

Vanadium redox flow battery

Demonstration 65–75 >10,000 250 (50)

620–740 (3,100–3,700)

Independent design of power and energy, low maintenance Low energy density, need for expensive vanadium

Zinc-bromine flow battery

Demonstration 65–70 >10,000 250 (50 MW)

290–350 (1,450–1,750)

Independent design of power and energy, low maintenance Low energy density, need for a stripping cycle, need for hazardous bromine

Sodium-sulfur battery

Commercial 80 4500 300 (50 MW)

520–550 (3,100-3,300)

Abundant, nontoxic materials; established technology Need for high temperatures, need for highly corrosive materials

Lead-acid battery

Commercial 85–90 2200–4500 200–400 (20–100)

425–980 (1700–4900)

Maturity of technology; abundant, low-cost materials Low energy density, short life

Lithium-ion battery

Demonstration 90–94 (4500) 4–24 (1–10)

900–1700 (1800–4100)

High energy density, high efficiency, broad power and energy ranges High cost

* Data source: [1]

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4  Energy Storage Metrics  In this section, key energy storage metrics for solar applications are identified, and quantifications are posited. The optimal values for these metrics depend on the solar application, photovoltaic installation, design of the energy storage system, and available opportunities for revenue generation. This report evaluates the metrics for a broad generalization of three sizes of solar photovoltaic installations:

Utility-scale photovoltaic (20–200 MW of capacity), Commercial-scale photovoltaic (100 kW–5 MW of capacity), and Residential-scale photovoltaic (5–25 kW of capacity).

This evaluation adopts the perspective of the photovoltaic owner. Owners of utility-scale photovoltaic installations are driven to maximize profits and mitigate risks. A consequent objective with regard to energy storage is to make photovoltaic power as predictable, dispatchable, and marketable as electricity delivered from conventional power plants is. To achieve this objective, the energy storage system needs to provide both load shifting (for price arbitrage) and variability damping functionalities. Commercial and residential photovoltaic owners are less likely to be concerned about variability in power output, since they can draw on grid electricity as needed. Instead, they are likely to be interested in maximizing the value of their photovoltaic output. They may also be interested in emergency protection in the event of electricity outages or, in some cases, capabilities for off-grid operations. Energy storage with load shifting functionality would be most useful in meeting these objectives, especially given the revenue possibilities from available net-metering and ancillary service opportunities. Energy storage at the grid (transmission or distribution) or micro-grid level can fulfill other revenue-generating functions that could potentially be more useful and cost effective [2]. However, these applications (such as reducing line-loss rates during high-demand periods and providing black-start capability) are outside the scope of this evaluation. 4.1  Technical Requirements  4.1.1  Energy Storage Capacity and Power  The energy capacity and power requirements of a specific installation are interrelated and depend highly on the photovoltaic and energy storage technologies, locations, operating and cycling schedules, and desired revenue-generating functions. A cost-benefit optimization is critical in making these specifications for the energy storage system design. Broadly speaking, load shifting aims to improve the matches between the photovoltaic output, the periods of highest electricity pricing, and the energy demand or load profile. To perfectly

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follow the target load, the amount (energy) and rate (power) of photovoltaic output charged or discharged would need to constantly change throughout the day. For the purposes of defining generalizing metrics, the charge and discharge rates are assumed to be the same and constant. For grid energy storage applications, durations of 2 to 4 hours for residential users (load following and backup), 3 to 6 hours for commercial consumers (energy arbitrage), and 15 minutes to 4 hours (voltage regulation and energy arbitrage) for utility photovoltaics have been proposed [1]. An independent evaluation of load-shift strategies that used photovoltaic output and power generation data projected for Arizona in 2020 [13] arrived at similar duration estimates. On the basis of these durations, estimates of energy capacity and power ranges for the reference energy storage applications were made and are shown in Figure 6.

Figure 6 Energy storage capacity and power ranges anticipated for solar applications, where P/E represents the ratio of energy storage power to energy storage capacity in h–1. Energy storage

capacity and power cost-optimized for specific applications may fall outside the general ranges shown in this figure.

4.1.2  Round­Trip Efficiency  Round-trip efficiency takes into consideration energy losses from power conversions and parasitic loads (e.g., electronics, heating/cooling, and pumping) associated with operating the energy storage system. This metric is a key determinant of the cost-effectiveness of energy storage technologies. Among energy storage options, compressed-air energy storage (CAES) has the lowest reported efficiency (40–55%), and Li-ion batteries have the highest (87–94%) [1]. For energy storage coupled with photovoltaics, efficiencies of less than 75% are unlikely to be cost effective.

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4.1.3  Response Time  The need for fast response times is expected to be more important for variability-damping than for load-shifting applications and hence more relevant to utility-scale photovoltaic generation in this evaluation. Passing clouds are the primary source of rapid changes in photovoltaic power output. The solar insolation at a single point can change by more than 60% in seconds [11]. Changes of this magnitude in power output from utility-scale photovoltaic systems are expected to occur on the order of minutes. Photovoltaic power output ramp rates were measured at a photovoltaic system in Hawaii that operated at 50% capacity over the course of a year [22]. In that study, only 0.07% of the one-minute ramps were greater than 60% of the operating capacity, and only 5% were greater than 10% of that capacity. System operator experience suggests that a response time of seconds would be adequate to dampen the majority of short-term variability events of significant magnitude. 4.1.4  Lifetime and Cycling  As is the case for efficiency, the cost-effectiveness of energy storage is directly related to its operational lifetime. For designs of energy storage in coupled systems, knowing the lifetimes of the major system components is helpful. To derive the SunShot initiative goals, a photovoltaic lifetime of 30 years and an inverter lifetime of 20 years were assumed [23]. These values set the objective range for an energy storage system lifetime to be 20 to 30 years. The lifetime of an energy storage system depends on many factors, including charge/discharge cycling, the depth of discharge, and environmental conditions. For any application, maximizing the depth of discharge minimizes the required energy storage capacity. The cycling schedule thus offers the greatest degree of freedom in design. For the residential and commercial applications considered in this analysis, one to two cycles per day — or 7,300 to 22,000 lifetime cycles — would be adequate to allow for photovoltaic power shifting and nighttime storage of cheap grid electricity. The design of cycling schedules to dampen photovoltaic output variability introduces additional degrees of freedom, the most important being the number of power spikes that a single discharge/charge cycle is designed to handle, when cycling frequency is traded off with energy storage capacity. The lifetime cycling requirement can also be reduced by increasing the magnitude or percentage of power spikes that is tolerated without intervention. An energy storage system that is designed to respond to power spikes that are more than 10% of the photovoltaic nameplate power in a single discharge/charge cycle might experience many more than 100,000 cycles over its lifetime, especially in cloudier locations.  

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4.2  Cost Requirements  The high cost of energy storage technologies is the primary reason for their very limited deployment in power generation, transmission, and distribution applications. Storage dedicated for solar applications may require even less costly alternatives, with a capital cost of significantly less than $1/W. The SunShot Initiative cost targets for photovoltaic installations (excluding energy storage) can act as points of comparison; these targets are $1/W for utility-scale photovoltaic systems, $1.25/W for commercial rooftop photovoltaics, and $1.50/W for residential rooftop photovoltaics [23]. To illuminate the energy storage cost gap for solar applications, a reference case was developed from a projection of electric demand and photovoltaic power generation in Arizona in 2020 [13]. On the basis of that projection, a 100-MW photovoltaic system would generate a maximum 750 MWh of electrical energy each day (with an average of 580 MWh). The amount of energy to be stored can be estimated by comparing the power output and grid load on a scale relative to the total daily demand and by assuming that any relative power produced beyond the grid demand (minimum storage need) or any excess demand beyond the base-load power production (maximum storage need) should be stored. The results of this comparison indicate that 50%, plus or minus 10% (i.e., 40–60%) of the photovoltaic output would be stored for later distribution. Comparing energy storage costs on the basis of the added cost to a $1/W photovoltaic solar installation can be instructive. Figure 7 illustrates this relationship for a reference case with 40% and 60% of the photovoltaic output stored. For example, to meet an energy storage cost objective of no more than $0.25/W of nameplate photovoltaic capacity, the energy storage technology would need to cost between $55 and $85/kWh, depending on the desired storage capacity. As a point of reference, Figure 7 also compares the goals of the U.S. Advanced Battery Consortium (USABC) for vehicle applications to the projected cost targets for storing electrical energy produced from solar energy. The near-term USABC goal for plug-in hybrid electric vehicles (PHEVs) with a power-to-energy (P/E) ratio of 4 h–1 and a 40-mile electric range is $300/kWh, based on usable energy (the amount accessible by the end user). The long-term USABC goal for an electric vehicle (EV) with a P/E ratio of 2 h–1 and a 150-mile electric range is $125/kWh. One can see that the cost objectives for solar power applications are much more stringent than those for vehicle applications. U.S. activities aimed at meeting the needs for electric-drive transportation are thus unlikely to lead to commercially viable energy storage options that would enable the widespread adoption of solar power as a competitor to traditional power sources.

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Figure 7 Suggested energy cost objectives for photovoltaic energy storage ($55–$85/kWh) compared with USABC goals for vehicle applications

 

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5  Advancing Li­Ion Batteries for Stationary Applications  The lithium-ion family of chemistries can readily meet the technical requirements for making solar electrical generation (residential scale to many-megawatt scale) indistinguishable from other established generation sources. Meeting both response-time and deep-discharge requirements is within the capability of an existing Li-ion battery, if the battery is sized for peak-shifting applications. However, dramatic advances are needed to significantly reduce the costs and increase the lifetimes of these technologies.

The long-term cost target for existing DOE-funded battery programs (USABC) is $125/kWh for electric vehicles, whereas the estimated cost target for long-duration storage for solar technologies is $55–$85/kWh.

The USABC program’s battery lifetime goal is 15 years for current vehicles that have an

8-year warranty, whereas photovoltaic lifetime expectations are 20 to 30 years. 5.1  Prospects for Low­Cost Li­Ion Batteries  Costs for the Li-ion family of chemistries are still coming down a rather steep curve, as shown in Figure 8. Meanwhile, the demonstrated performance of commercial Li-ion systems is reshaping the Ragone plot of energy density versus power density and the performance that this technology was previously thought to be capable of. Li-ion technology is poised to be the prime power source in a growing vehicle market based on hybrid electric, plug-in hybrid electric, and fully electric vehicles. Companies that want to expand their market presence have launched efforts to develop stationary energy storage units that are capable of stabilizing the grid in developing countries or of regulating the sharp ramp rates inherent when integrating renewable generation. The diversity of the Li-ion family enables it to be the optimal chemistry for both extreme power applications and high-energy uses. Selecting the right combination of materials, morphology, and battery design is all that is needed to meet these disparate technical needs, including those for solar applications. Nevertheless, dramatic advances are necessary to significantly reduce the costs and increase the lifetimes of these technologies. As Figure 7 indicates, current efforts to reach automotive cost targets will not result in batteries that are cost effective for photovoltaic applications. Current projections of cost curves for Li-ion technology should reach near-term vehicle application goals [24]. However, the long-term USABC goal of $125/kWh will require dramatic breakthroughs in materials chemistry and battery design. If meeting long-term transportation goals requires transformational breakthroughs, how, then, can stationary storage for the grid possibly reach $55 to $85/kWh?

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Figure 8 Dramatic decrease in consumer cell cost based on a graphite-LiCoO2 Li-ion cell chemistry. Almost all advances are in manufacturing and engineering. Changing to fundamentally less expensive materials with a novel cell design and a different ratio of inactive to active material

is the key to creating a new cost curve with an even steeper slope. Stationary and transportation applications have very different requirements. The most significant difference in performance requirements is the relative quantity of storage needed, which is best described by the power-to-energy (P/E) ratio. Batteries developed for electric vehicles target a P/E of 2, or the equivalent of 30 minutes of storage. Storage systems for solar applications are best optimized for 3 to 6 hours of storage at the rated power. Developing electrochemical energy storage that is optimized for longer storage times will dramatically reduce the burden of inactive materials and allow a system for solar storage applications to be developed at the least cost possible. In practice, an electric vehicle transportation battery will charge and discharge over longer time periods by using average power values lower than the rated maximum. However, the design values for maximum rated power set the designed P/E ratio. The contribution of Li-ion active materials (anode, cathode, and electrolyte) to the total cost of energy storage is examined in Figure 9 in an attempt to understand the lowest possible cost feasible for Li-ion systems. As already mentioned, currently produced Li-ion transportation batteries cost $650/kWh, with near- and long-term targets of $300/kWh and $125/kWh, respectively. Thus, the active materials currently constitute a small fraction (~$70–$80/kWh of the total battery price. Battery cost projections predict that active materials will contribute about 40% of the total system cost once high volumes and a competitive market drive down costs toward the USABC targets [24].

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Figure 9 Contribution of active materials (anode, cathode, and electrolyte) to the cost of an electrochemical energy storage system, considering cost ranges for lithium titanate spinel anode

systems (LTO-based Li ion), graphite-based anode systems (Gr-based Li ion), and advanced Li-ion systems. Active materials are assumed to be 50%–60% of the total system cost. Materials cost must

drop to the $5–$10/kg range for high-energy-density Li-ion chemistries to reach solar electricity storage targets. Near-term material costs should be $10–$25/kg. Systems with intrinsically higher

energy density typically result in a lower cost of energy ($/kWh). Figure 9 was adapted from a version created by Yet-Ming Chiang of MIT in a private communication.

The prices of the anode, cathode, and electrolyte materials are similar to each other on a $/kg scale within a factor of two. Costs are predicted to fall to $10–$25/kg in the near term [25], [26]. Raw materials, processing costs, and energy usage all drive the cost of these materials. Current intercalation materials used for anodes and cathodes are made through energy-intensive processes, which alone may contribute $5/kg to the material cost. The use of elements such as cobalt and nickel result in higher-than-desired prices. Finally, electrochemical systems are known to require very high purity levels to ensure long life; such a requirement adds to the cost. To meet an energy storage cost objective of $55–85/kWh, the active materials would need to cost $5–$10/kg, assuming they would make up 50%–60% of the installed system and future maintenance cost. The implicit assumption is that new battery designs that decouple power from energy will drive active materials to a higher overall fraction of installed cost, when compared to the cost of Li-ion batteries developed for transportation applications. The combined pathway of lower active-materials cost with lower inactive-materials burden creates the prospect that Li-ion technology can meet future solar storage needs. Lower-energy-density intercalation systems, such as those based on the lithium-titanate spinel anode (LTO-based Li-ion), are often cited as favorable energy storage systems for stationary storage applications, since they are typically based on earth-abundant materials (e.g., Ti, Fe, and Mn) and have demonstrated low capacity-fade and power-fade during usage. Figure 9, however, clearly shows the disadvantage of systems based on these lower-energy couples. The slopes of the cost ranges are directly related to the energy density of the couples. Whereas a system’s

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volume and weight are less important for stationary storage applications than for transportation applications, higher energy density often translates to lower total costs. Traditional approaches based on a graphite anode (Gr-based Li-ion) and anticipated advanced Li-ion systems hold the best promise to meet the stringent targets for the Li-ion family of chemistries. The high energy densities afforded by these systems reduce the quantity of material needed and thus the overall cost burden. The advanced chemistries that focus on earth-abundant materials, such as manganese and silicon, have the greatest chance of success. Continued investments in doing research on Li-ion based technologies may lead to batteries that are able to reach the storage targets for transportation applications. However, new paradigms in battery design are needed to drive down costs even further to meet the needs of solar energy applications. Traditional Li-ion batteries are restricted to a modest range of P/E ratios. Therefore, the use of this standard design in applications outside the intended P/E range results in an increased cost due to the large quantity of inactive material that supports the operation of the battery (separator, current collectors, packaging, etc.). Moving to designs that make the reactants and/or the electrolyte flow can dramatically lower the ratio of inactive materials to active materials in the final design. Both the current and past generations of flow batteries have used this approach. The final products, however, have not been able to show a cost curve that demonstrates the potential to meet the aggressive cost targets required for grid applications. The general trends shown in Figure 9 suggest this is a result of the low inherent energy density of commercial flow-battery systems, such as vanadium redox. Novel approaches to using Li-ion materials in designs that decouple power and energy may allow for the development of dramatically cheaper stationary energy storage. The designed power of the battery is set by the maximum power output of the photovoltaic system as well as a need to handle the dramatic swings in photovoltaic output from passing clouds. Analysis may show that coupling a lower-power, but high-energy, system with more traditional Li-ion systems or electrochemical double-layer capacitors is the optimal configuration. The extreme fluctuations in solar output must always be considered. These fluctuations are easier to overcome when a large storage system is utilized. Power electronics are necessary to integrate photovoltaic units with stationary energy storage. Proper design should allow for a single DC-to-AC inverter shared during both electricity generation and discharge of the energy storage device. The cost target above implicitly assumed that the photovoltaic installation cost includes the inverter. However, DC-to-DC converters and other power conditioning devices will be needed, and their costs are not negligible. The development of simplified systems that have a minimal cost yet a long life is necessary to meet the $55–$85/kWh storage targets.  

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5.2  Priority Activities to Advance Li­Ion Batteries for Stationary Storage  Targeted research and development could result in new designs of Li-ion batteries that would help advance solar energy storage. An increased understanding of current Li-ion batteries and their suitability for solar storage could encourage the optimization and subsequent adoption of these technologies. In addition, Li-ion battery systems that incorporate new materials (e.g., the cost-effective, optimized materials used for electrodes and other components) could help overcome the current gaps and limitations of Li-ion batteries, creating Li-ion systems more suited to solar storage applications. For Li-ion batteries, activities and initiatives can accelerate progress in the following areas:

Materials discovery and performance optimization. In the long term, achieving significant cost reductions would likely require the use of cost-effective alternative materials or the development of new Li-ion chemistries. The development of new intercalation compounds with low cycling strain and fatigue crack propagation for Li-ion batteries could also have a major impact. New compounds should have a goal of 10,000 cycles at 80% depth of discharge. Some long-lived Li-ion chemistries, such as lithium iron phosphate, have already been explored. Such work should continue and be expanded in pursuit of the cycle and depth-of-discharge goals. It will be necessary to develop low-energy methods for synthesis or to use abundant minerals that require minimal processing in order to reach the material cost targets. Earth-abundant materials are absolutely essential. The focus should be the following elements: C, N, O, S, F, Fe, Al, Mn, P, Si, and Ti. The cost of the electrolyte must also be addressed, particularly if a flow-battery design is used. The salt of choice for the Li-ion — LiPF6 — is currently the most expensive component of the electrolyte solution. LiPF6 shows excellent transport properties under different conditions, and, perhaps more important, it passivates the aluminum current collector and thus has proved hard to replace. Novel attempts to minimize or replace this salt, by leveraging the large amount of work on electrolyte additives now being done, should be undertaken. Work in this area could also lead to a synergistic improvement in lifetime, since it has been suggested that LiPF6 produces acidic side products that might degrade active material capacity while passivating the aluminum. Long-term basic and applied research should also focus on developing new battery chemistries (e.g., sodium ion [Na-ion] or anion-based nonaqueous batteries). Very little is known about these chemistries, and their future capabilities may prove competitive or revolutionary compared to those of Li-ion systems. Unknown advances in these other systems might result in a more capable technology. Other common commercialized battery technologies are based on the anion as the charge carrier from the anode to the cathode. Li-ion batteries rely on the cation, Li+. Cations tend to have slower diffusion rates than anions, owing to the strong interaction of the positive charge with the solvent. The development of nonaqueous batteries that use anion charge carriers would open up new classes of structure types to serve as the host materials.

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Battery design. New architectures optimized to lower P/E ratios must combine the high energy density of Li-ion systems with novel ways to minimize active (costly) materials. Flowing the reactants or the electrolyte is one way to reduce the transport limitations that come with thick electrodes (high loadings). Changes (e.g., packaging electrodes into larger cell formats or flowing active materials from storage tanks) that are perhaps not feasible for transportation applications could reduce the number of steps in the manufacturing process and therefore the end cost. The cost effectiveness of energy storage could be further improved by optimizing the design (especially power and energy requirements) for specific residential, commercial, and utility applications.

Life. Achieving the 20- to-30-year lifetime demanded for storage for solar applications will require both a materials and systems development approach. Stable and robust 100-year-lifetime materials should be designed and used; they would allow the battery to be refurbished after it aged. In addition to the materials discovery and engineering detailed above, completely new approaches to design and operations will be necessary. Researchers must develop electrodes that consider alternate ways to combat aging. For example, the creation of a method that allows parts to be washed and refreshed in place or recycled by using a minimal amount of energy at a minimal cost would shift the paradigm. Designs that separate power and energy should be more amenable to such concepts.

 

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[12] Hoff, T., R. Perez, J.P. Ross, and M. Taylor, 2008, Photovoltaic Capacity Valuation Methods, SEPA Report 02-08, Solar Electric Power Association, May.

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7  Contributors  Ira Bloom Manager, Electrochemical Analysis and Diagnostics Laboratory, Chemical Sciences and Engineering Division Audun Botterud Energy Systems Engineer, Decision and Information Sciences Division Anthony Burrell Interim Department Head, Electrochemical Energy Storage, Chemical Sciences and Engineering Division Jeffrey P. Chamberlain Major Initiative Leader, Energy Storage, Chemical Sciences and Engineering Division Guenter Conzelmann Director, Center for Energy, Environmental, and Economic Systems Analysis, Decision and Information Sciences Division Kevin G. Gallagher Chemical Engineer, Chemical Sciences and Engineering Division Diane J. Graziano Sustainable Energy Analyst, Decision and Information Sciences Division Vladimir Koritarov Deputy Director, Center for Energy, Environmental, and Economic Systems Analysis, Decision and Information Sciences Division Mark C. Petri Technology Development Director, Energy Engineering and Systems Analysis Directorate Michael Thackeray Argonne Distinguished Fellow, Senior Scientist, Chemical Sciences and Engineering Division Jianhui Wang Computational Engineer, Center for Energy, Environmental, and Economic Systems Analysis, Decision and Information Sciences Division Zhi Zhou Computational Engineer, Center for Energy, Environmental, and Economic Systems Analysis, Decision and Information Sciences Division