TODAY’S STUDY: How Energy Storage Makes Deep Emissions Cuts Easier
The role of energy storage in deep decarbonization of electricity production
Maryam Arbabzadeh, Ramteen Sioshansi, Jeremiah X. Johnson and Gregory A. Keoleian, 30 July 2019 (Nature Communications)
Deep decarbonization of electricity production is a societal challenge that can be achieved with high penetrations of variable renewable energy. We investigate the potential of energy storage technologies to reduce renewable curtailment and CO2 emissions in California and Texas under varying emissions taxes. We show that without energy storage, adding 60 GW of renewables to California achieves 72% CO2reductions (relative to a zero-renewables case) with close to one third of renewables being curtailed. Some energy storage technologies, on the other hand, allow 90% CO2 reductions from the same renewable penetrations with as little as 9% renewable curtailment. In Texas, the same renewable-deployment level leads to 54% emissions reductions with close to 3% renewable curtailment. Energy storage can allow 57% emissions reductions with as little as 0.3% renewable curtailment. We also find that generator flexibility can reduce curtailment and the amount of energy storage that is needed for renewable integration.
Due to cost decreases1,2, renewable energy is experiencing greater use (https://www.eia.gov/outlooks/steo/pdf/steo_full.pdf). Many jurisdictions have policies in place to incentivize renewable use (http://www.dsireusa.org/). These policies are often intended to decrease the carbon-intensity of electricity production. The role of energy storage in aiding the integration of renewable energy into electricity systems is highly sensitive to the renewable-penetration level3. California, for instance, is experiencing days during which demand is too low to accommodate all of the solar energy that is available midday4. This overgeneration-related renewable curtailment can be exacerbated by thermal generators having limited flexibility in how quickly they can adjust their production or how low their production levels can go5.
The development and deployment of grid-scale energy storage is advancing due to technology development and policy actions, such as California’s energy storage mandate6,7. Energy storage can provide a variety of services and its economic rationale is highly application-dependent8. Numerous studies optimize the size and operation of energy storage within a specific power system to achieve the best economic or environmental outcome. However, there are no studies in the extant literature that investigate systematically the economic viability of using energy storage to alleviate renewable curtailment for the purposes of decarbonizing electricity production. Moreover, the existing literature does not examine the impacts of emissions policy, such as a carbon tax, on the economics of energy storage for mitigating renewable curtailment. Detailed analysis is required to estimate the value of energy storage that is used for different applications, including renewable integration9. This study addresses this gap by optimizing the investment in and operation of nine currently available energy storage technologies to minimize cost of the California and Texas power systems. We assume varying renewable penetrations and different CO2-tax policies.
Energy storage technologies have different characteristics and potential applications10,11,12,13. As such, no single technology excels on all characteristics. Integrating energy storage into the grid can have different environmental and economic impacts, which depend on performance requirements, location, and characteristics of the energy storage system14,15,16. The cost of energy storage systems and regulatory challenges are major obstacles to their adoption13,17,18,19. Braff et al.20examine the value of using energy storage to increase the price at which wind and solar energy can be sold in wholesale markets. They find that many energy storage technologies are currently too costly for this application and determine the cost reductions that are needed to make this application economically viable. Other works21,22,23,24,25examine the environmental impacts of energy storage, showing that it depends upon how it is operated and the technical characteristics of the power system into which it is integrated.
Thus, there is a need to optimize the operation of energy storage to achieve desired economic and environmental outcomes. Many studies optimize the operation and size of an energy storage system for a given grid application based on economic criteria26,27. Others propose optimization models for sizing and operating energy storage to minimize total electricity cost or to maximize investor profits28,29,30. Another set of studies model emissions and economic considerations in optimizing energy storage use31,32,33.
Our study extends the existing literature by evaluating the role of energy storage in allowing for deep decarbonization of electricity production through the use of weather-dependent renewable resources (i.e., wind and solar). The model optimizes the power and energy capacities of the energy storage technology in question and power system operations, including renewable curtailment and the operation of generators and energy storage. This is done to minimize total system costs, which consist of the capital cost of energy storage, generator-operations costs, and CO2-emissions costs. Technical constraints in the model include operating limits of generators and energy storage and load-balance requirements. We examine nine currently available energy storage technologies: pumped-hydroelectric storage (PHS), adiabatic (ACAES), and diabatic (DCAES) compressed air energy storage (CAES), and lead-acid (PbA), vanadium-redox (VRB), lithium-ion (Li-ion), sodium-sulfur (NaS), polysulfide bromide (PSB), and zinc-bromine (ZNBR) batteries. Our model allows us to determine which energy storage technologies are most cost-effective in aiding renewable integration and the extent to which the cost of a currently uneconomic technology must come down to make it cost-effective. We use two case studies, which are based on the California and Texas power systems in 2010–2012, and consider up to 20 GW of wind and 40 GW of solar capacity added to the system. We also consider the impact of a CO2 tax of up to $200 per ton. Our analysis of the cost reductions that are necessary to make energy storage economically viable expands upon the work of Braff et al.20, who examine the combined use of energy storage with wind and solar generation assuming small marginal penetrations of these technologies. Conversely, we examine their economics at significant renewable penetrations that are necessary for deep decarbonization of electricity production.
Our findings show that renewable curtailment and CO2 reductions depend greatly on the capital cost of energy storage. Moreover, increasing the renewable penetration or CO2 tax makes energy storage more cost-effective. This is because higher renewable penetrations increase the opportunities to use stored renewable energy to displace costly generation from non-renewable resources. Among the energy storage technologies that we consider, PHS and DCAES are deployed in more of the scenarios that we examine. This is due to the lower capital costs of these technologies. Other technologies see deployment under some scenarios. We also find that relatively modest reductions in the capital costs of other energy storage technologies can make them cost-effective for this proposed application…
Our case study shows that energy storage can play a non-trivial role in decarbonizing California’s electricity production through greater use of renewables. Some technologies (e.g., PHS, CAES, and VRB and PSB batteries) can eliminate cost-effectively over 90% of CO2 emissions relative to a no-renewables case. Without energy storage, massive renewable deployment can only achieve about 72% CO2-emissions reductions (with the base-case 7.0-GW minimum-dispatchability requirement and a $200 per ton CO2-emissions tax). In Texas, energy storage deployment yields 57% CO2-emissions reductions compared to a no-renewables case (assuming an 8.2-GW minimum-dispatchability requirement and a $200 per ton emissions tax). Without energy storage, 60 GW of renewables reduce emissions by 54% relative to a no-renewables case. Recent analyses1,34 show that Texas had over 22 GW of wind installed as of 2017. Thus, the case with 60 GW of renewables represents a significant increase in solar capacity and an already-achieved wind-penetration level.
California has less supply-side flexibility (i.e., more output from nuclear, geothermal, biomass, and hydroelectric units and energy transactions) compared to Texas, resulting in relatively high renewable curtailment in California. Thus, energy storage is valuable in reducing renewable curtailment and displacing fossil-fueled generation. Conversely, even without added renewables, energy storage is cost-effective in Texas with a carbon tax, as it can be used to shift generating loads away from coal-fired units toward natural gas-fired generation.
Our results represent a lower bound on energy storage’s role in renewable integration and electricity decarbonization. This is because at high renewable penetrations, energy storage may play other roles that are not captured in our model3. For instance, energy storage can be a low-cost source of flexibility to accommodate subhourly or minute-to-minute variability in wind and solar availabilities. Because our model assumes an hourly temporal resolution, such a benefit of energy storage is not captured.
Our results show that its capital cost is the primary factor in determining the scale at which an energy storage technology is deployed. Even with ambitious renewable penetrations and a high emissions tax, a relatively expensive (but high-efficiency) technology, such as Li-ion batteries, has a limited role to play. Our results suggest, however, that modest reductions in Li-ion-battery costs may increase their deployment.
We determine this by examining the reduced cost of energy storage capacity, which is obtained from solving our optimization model. In the context of our model, the reduced cost can be interpreted as indicating how much the capital cost of an uneconomic energy storage technology must change before it is cost-effective to build35. Our results show that in scenarios in which Li-ion batteries are not built, capital cost reductions of between $1 per kWh and $40 per kWh are sufficient to make the technology economically viable.
Given the major reductions in battery-manufacturing costs over the past decade, such cost reductions may be possible. This would mean that energy storage technologies that appear uneconomic in our case study may well be viable in the near future. The reduced costs results for other storage technologies are provided in Supplementary Data 1.
Given the wide range of costs for Li-ion, NaS, and PSB batteries that are reported in the literature (https://www.lazard.com/media/450774/lazards-levelized-cost-of-storage-version-40-vfinal.pdf), we conduct a sensitivity analysis, in which the capital costs of Li-ion batteries are reduced to $259 per kWh and $59 per kW, the costs of NaS batteries are increased to $350 per kW and $350 per kWh, and the costs of PSB batteries are reduced to $200 per kW and $90 per kWh. Table 1 summarizes the impacts of these changed capital costs. Specifically, the table reports changes in renewable curtailments and CO2 emissions relative to the levels that are achieved with the baseline costs, as a percentage of the baseline curtailment and emissions impacts of Li-ion, NaS, and PSB.
The results that are in the table are for 2012, assuming 20 GW of wind and 40 GW of solar are added to each system, a $200 per ton CO2-emissions tax, and the base-case minimum-dispatchability requirement for each system. The amounts of energy storage added, renewable curtailments, and CO2emissions that are achieved in other scenarios are provided in Supplementary Data 1.
Our results demonstrate that increasing the CO2-emissions tax makes energy storage more cost effective. Yong and McDonald36 show that an emissions-tax regime that is set by a government with a willingness to commit to it, has a positive influence on the size and the direction of firm-level investment in clean technologies. Thus, adding a strong emissions tax to the already-established energy storage mandate in California may have beneficial economic, policy, and technology-development impacts. We also show that greater generator flexibility, which is represented through a lower minimum-dispatchability requirement, reduces renewable curtailment and the amount of energy storage that is needed.
There are some important limitations of our analysis that can be examined in future research. The only environmental impact of electricity production and energy storage use that we examine is CO2emissions. There may be other important impacts. Our results show that PHS holds great promise, due to its relatively low cost. There are concerns around other environmental impacts of PHS, such as land and water use, species mortality, and impacts on biological production, however. Moreover, PHS is location-dependent and requires sites with specific characteristics12. The deployment of CAES is also limited, as specific underground formations are needed to store the compressed air12. Further examination of these limitations would provide a more comprehensive understanding of the deployment potential of these technologies.
Our optimization model could be applied to other case studies, with different generation mixes. We assume no degradation of energy storage throughout its operation. Arbabzadeh et al.37 show that its degradation does not change significantly the environmental impacts of using energy storage for generation-shifting. Nevertheless, future work could examine the impact of such degradation on the cost-effectiveness of using energy storage for alleviating renewable curtailment. We also assume that energy storage can operate between 0 and 100% state of charge. Future analyses can define technology-specific operational windows for energy storage…