Desalination can be an important component of drought-resilient regional water systems, however, energy costs are significant contributors to the cost of desalinated water. The time-varying nature of electricity prices represents an opportunity for desalination facilities to reduce their energy-related costs through operating such facilities to exhibit time-varying electric loads that maximize load when electricity is cheap and minimize load when electricity is expensive. Here, we investigate the extent to which flexible operation of a brackish water desalination facility, represented by the Chino Desalter Authority II facility, in response to time-varying electricity tariffs can reduce the cost of desalinated water. We show that flexible operation does not reduce the cost of desalinated water under current electricity tariffs but may net cost of desalinated water by up to 16.1% on an all-cost basis of the facility under more aggressive real-time pricing tariffs. If the facility was designed to accommodate flexible operation with larger feed pumps and lower minimum flow rates, potential cost reductions increased to 47% under aggressive tariff structures. Further, installing a battery energy storage system instead of operating treatment trains flexibly provided similar benefits as that of flexible operation. Finally, we show that flexible operation to minimize costs does not necessarily reduce greenhouse gas emissions. Overall, we show that there is potential for flexible operation of brackish water desalination facilities to reduce their cost of desalinated water, but these reductions are only realized when electricity tariffs are sufficiently aggressive and when the facility is designed to accommodate flexible operation.

The reliable operation of the infrastructure underlying the provision of energy services is critical for supporting a modern quality of life. While energy infrastructure undergoes a transformation to increasingly incorporate cleaner energy resources, it is already experiencing disruptions to its operation from the effects of physical and natural threats such as extreme weather events. Further, the continued progression of climate change is expected to both intensify and increase the frequency of these events, which energy infrastructure must be able to withstand. This focus issue, ‘ Physical and Natural Threats to Energy Infrastructure and Systems ’, presents recent research that details the interaction between extreme weather events and the operation and planning of future regional energy infrastructure, with many of the lessons learned transferable across threat types. Specifically, the articles in this issue address two themes. First, to improve our understanding of the types and extents of how extreme weather events impact one or more assets of regional energy infrastructure. Second, to improve our understanding of how to plan such infrastructure to be resilient against these impacts while meeting clean energy transition goals. As regional entities engage in planning the transformation of their energy infrastructure, proactive planning that accounts for the potential of intensified threats from climate change-driven extreme weather events is critical to ensure that future energy systems are not only cleaner but also more resilient against disruption than current energy systems.

As power systems transition to renewable energy, integrating battery electric vehicles (BEVs) into grid operations presents new opportunities and challenges for managing electricity demand and the associated environmental impacts from BEV charging. This study examines two grid-integration strategies: supplier-managed charging (SMC), which gives utilities control over charging timing, and vehicle-to-grid (V2G), which transforms BEVs into distributed energy storage resources. Using a discrete choice experiment with 1,356 current BEV owners, we quantify how program attributes influence enrollment decisions. Using multinomial logit models, results suggest that SMC participants predominantly value operational flexibility and recurring payments while V2G participants prefer monetary incentives, indicating a willingness to provide grid services for compensation. Through simulation analysis, we identify program ‘attribute equivalencies’ that quantify changes needed in attributes to achieve equivalent enrollment levels. These findings can be used in the design of market mechanisms and policy frameworks that accelerate BEV integration into future energy systems.

The decarbonization of regional electricity systems is a critical enabler of broader economy-wide decarbonization strategies and has motivated robust research on how to decarbonize electricity systems at minimum monetary cost. Since these efforts often focus on the operation of electricity systems, however, they do not account for emissions of the full life cycle associated with different resources. Different resource mixes can achieve a similar level of decarbonization apparent decarbonization through operational emissions, while achieving very different levels of life cycle greenhouse gas (GHG) emissions reductions. To explore these differences, we model the expansion of the California electricity system from 2030 to 2045 using a simplified electricity dispatch model to investigate how the planning of future electricity systems may differ between prioritizing minimum cost versus minimum life cycle GHG emissions under a common target for operational GHG reductions. We find that explicitly planning for minimum life cycle GHG emissions yields an additional 1.6-2.0% reduction in annual life cycle GHG emissions at a cost penalty of 3.2–9.6% and that electricity resource mixes that minimize life cycle GHG emissions tend to favor high capacity factor zero-carbon resources and long-duration storage compared to a minimum cost approach. Comparatively, we find that aggressive supply chain decarbonization of generation and storage technologies reduces life cycle GHG emissions of electricity supplies by 3.0% to 14% and combining both increases these reductions to 5.0% to 16%. Further, we find that applying a carbon tax to minimum cost-based capacity expansion can incentivize planning to account for life cycle GHG emissions. Our results indicate that a planning approach focused on minimizing life cycle GHG emissions may not be palatable, but significant reductions in life cycle emissions can be realized through conventional mechanisms like carbon taxes, import standards, and targeted supply chain decarbonization.

The replacement of short-distance, low-occupancy automobile trips with electric bicycles (e-bikes) can reduce energy consumption and emissions related to transportation activities. Due to the low electricity consumption per mile of e-bikes compared to battery electric vehicles, e-bikes can also reduce the peak and total electric loads that battery electric vehicles impose on local and regional electricity systems, potentially translating into benefits for electricity system operation and distribution infrastructure lifetimes. This study leverages synthetic travel pattern data for the San Diego, California, region, along with National Household Travel Survey data for bike trip characteristics to estimate the battery electric vehicle trips that e-bikes can displace. Moreover, we use electricity system modeling to estimate the electricity system cost savings in the years 2030 and 2045 from replacing battery electric vehicle trips with e-bikes. We find that using e-bikes to displace battery electric vehicle trips where feasible can reduce California wholesale electricity system costs by up to 3.0% in 2030 and 3.8% in 2045, translating to annual savings of $770 million and $1360 million, respectively. Additional potential savings can also occur in the distribution system through extending the lifetime of distribution transformers, depending on the current loading of distribution transformers on a residential circuit.

Decarbonization plans depend on the rapid, large-scale deployment of batteries to sufficiently decarbonize the electricity system and on-road transport. This can take many forms, shaped by technology, materials, and supply chain selection, which will have local and global environmental and social impacts. Current knowledge gaps limit the ability of decision-makers to make choices in facilitating battery deployment that minimizes or avoids unintended environmental and social consequences. These gaps include a lack of harmonized, accessible, and up-to-date data on manufacturing and supply chains and shortcomings within sustainability and social impact assessment methods, resulting in uncertainty that limits incorporation of research into policy making. These gaps can lead to unintended detrimental effects of large-scale battery deployment. To support decarbonization goals while minimizing negative environmental and social impacts, we elucidate current barriers to tracking how decision-making for large-scale battery deployment translates to environmental and social impacts and recommend steps to overcome them.

As Battery Electric Vehicles (BEVs) gain popularity, managing their charging becomes crucial for grid stability. Smart charging programs can help utilities manage this demand and integrate more renewable energy by controlling when and how BEVs are charged. However, these programs require participation from BEV owners, who may be hesitant to freely provide such control. This study uses a discrete choice experiment (also called conjoint analysis) to measure BEV owners' willingness to participate in smart charging programs under various incentives and features. We examine two types of smart charging: Supplier-Managed Charging (SMC), which controls charging times, and Vehicle-to-Grid (V2G), allowing BEVs to return power to the grid. In an online survey conducted via Facebook and Instagram ads, we collected 858 valid responses, with 815 responses for SMC program choices and 414 for V2G program choices. We used mixed logit (MXL) models to quantify respondents' willingness to participate. The findings indicate a general reluctance to participate in both programs without some form of incentive, with respondents being most sensitive to recurring monetary incentives. For SMC, there is also concern about ensuring sufficient battery levels in the mornings. Simulations were conducted to predict enrollment rates based on different program features. Additional data will be collected to refine the models in the coming months.

AbstractThe large-scale deployment of battery energy storage systems is critical for enabling the electrification of transport and the integration of renewable energy resources into regional electricity systems. Producing these systems, however, can impose various types and extents of environmental impacts and resource requirements. For relatively mature battery technologies, such as lead-acid, nickel-metal hydride, and certain variations of lithium-ion batteries, a robust life cycle assessment (LCA) literature exists that characterizes the environmental impacts and material requirements for these systems. Newer battery technologies, however, are constantly being explored, developed, and refined to improve upon the cost, durability, efficiency, or other performance parameters of relatively mature battery technologies. These newer technologies, including but not limited to solid-state lithium batteries, metal anode-based lithium batteries, non-lithium-based chemistries, flow batteries of different chemistries, and metal-air batteries, show promise from an in-use performance standpoint but do not yet have as robust of an LCA literature that characterizes their environmental impacts and resource requirements at scale. Here, we provide an overview of the present state of the art in the research literature of LCAs that characterize the potential environmental impacts and resource requirements of these emerging technologies as a basis for outlining needs for future research.

Reservoir-based hydropower systems represent key interactions between water and energy systems and are being transformed under policy initiatives driven by increasing water and energy demand, the desire to reduce environmental impacts, and interacting effects of climate change. Such policies are often guided by complex system models, whereby divergence in system representations can potentially translate to incompatible planning outcomes, thereby undermining any planning that may rely on them. We review different approaches and assumptions in hydropower representation in water and energy systems. While the models and issues are relevant globally, the review focuses on applications in California given its extensive development of energy and water models for policy planning, but discusses the extent to which these observations apply to other regions. Structurally, both water-driven and energy-driven management models are similar. However, in energy models, hydropower is often represented as a single-priority output. Water management models typically allocate water for competing priorities, which are generally uninformed by dynamic electricity load demand, and often result in a lower priority for hydropower. In water models, constraints are increasingly resolved for non-energy components (e.g. inflow hydrology and non-energy water demand); few analogues exist for energy models. These limitations may result in inadequate representations of each respective sector, and vastly different planning outcomes for the same facilities between the two different sectors. These divergent modeling approaches manifest themselves in California where poorly reconciled outcomes may affect decisions in hydropower licensing, electricity grid flexibility and decarbonization, and planning for environmental water. Fully integrated water-energy models are computationally intensive and specific to certain regions, but better representation of each domain in respective efforts would help reconcile divergences in planning and management efforts related to hydropower across energy and water systems.

While many electricity resource mixes can facilitate a zero-carbon electricity system, different pathways can vary significantly in their contribution to environmental impacts. Many current assessments focus on tradeoffs associated with monetary cost, neglecting these wider impacts. Here, electric grid dispatch modeling and electricity mix optimization is combined with data on resource consumption and electricity technology costs to compare five different approaches for developing a 100% zero-carbon electricity system in California: minimum critical metals use, minimum solid construction materials mass, minimum land use, minimum freshwater consumption, and minimum monetary cost under present-day policy goals and constraints. The modeled scenarios show that prioritizing minimum solid construction materials mass in developing such systems also achieve near-minimal monetary cost and land use and did not exhibit the worst performance on either freshwater consumption or critical metals use. In contrast, the strategy that prioritized minimum freshwater consumption exhibited the largest land use and materials use of the five strategies. The minimum monetary cost strategy exhibited near-minimal freshwater consumption, but large land use and the highest demand for critical metals. The modeled monetary unit cost of electricity was lower than the 2030 reference for all zero-carbon electricity system scenarios. The results highlight tradeoffs between contributions to different types of environmental impact in developing a zero-carbon electricity system. Notably, prioritizing certain metrics can result in electricity systems that balance these tradeoffs better than others given the existing suite of zero-carbon options. More broadly, the results show that the planning of zero-carbon electricity systems should more explicitly incorporate non-carbon environmental externalities as co-priorities in their development.

This study assesses the impacts of on-road light- to heavy-duty zero emission vehicle (ZEV) adoption and charging protocols on greenhouse gas emissions for the years 2030 and 2045 in California, and on air quality for the year 2045. Two scenarios are addressed: (1) a "business-as-usual" (BAU) scenario with modest ZEV adoption, and (2) a "carbon neutral" scenario that achieves carbon neutrality by 2045 with proactive ZEV adoption. Electricity load for fueling ZEVs is projected, including electricity fuel for battery electric vehicles and electrolytic hydrogen for fuel cell electric vehicles. This electric load was input into an electric grid dispatch model and electric grid and air quality analyses were conducted. The results revealed that although medium- and heavy-duty vehicles (MHDVs) are projected to have lower total electric load associated with fueling, they will require roughly double the electricity for hydrogen production of light-duty vehicles. For the electric grid scenarios examined, ZEV loads increased peak electricity demand by 3% to 6% in 2030 and 22% to 31% in 2045. MHDV time-of-use and smart charging strategies were equally able to shift charging demand to off-peak times. Higher ZEV loads under the carbon neutral scenario increased natural gas use up to 6% in 2030 and energy storage requirements up to 45% in 2045 compared with the BAU scenario. The analyses also found that achieving carbon neutrality through ZEV adoption had the cobenefit of significantly reducing ground-level ozone and PM2.5 concentrations in key regions of California, providing health savings of approximately $28 billion annually in 2045.

Batteries are important for promoting renewable energy, but, like most engineered products, they contain multiple hazardous materials. The purpose of this study is to evaluate industrial-scale batteries using GreenScreen® for Safer Chemicals, an established chemical hazard assessment (CHA) framework, and to develop a systematic, transparent methodology to quantify the CHA results, harmonize them, and aggregate them into single-value hazard scores, which can facilitate quantitative comparison and a robust evaluation of data gaps, inconsistencies, and uncertainty through the implementation of carefully selected scenarios and stochastic multicriteria acceptability analysis (SMAA). Using multiple authoritative toxicity data sources, six battery products are evaluated: three lithium-ion batteries (lithium iron phosphate, lithium nickel cobalt manganese hydroxide, and lithium manganese oxide), and three redox flow batteries (vanadium redox, zinc-bromine, and all-iron). The CHA results indicate that many materials in these batteries, including reagents and intermediates, inherently exhibit high hazard; therefore, safer materials should be identified and considered in future designs. The scenario analysis and SMAA, combined, provide a quantitative evaluation framework to support the decision-making needed to compare alternative technologies. Thus, this study highlights specific strategies to reduce the use of hazardous materials in complex engineered products before they are widely used in this rapidly-expanding industry sector.

To ensure that the production cost of battery energy storage systems for the electric grid does not compromise the environmental benefits gained from the substitution of traditional fossil fuels, it is important to evaluate and manage the cost feasibility of the feedstock materials used in battery production. In this study, we present a techno-economic analysis to evaluate the cost of materials in three emerging redox flow battery products: vanadium pentoxide redox flow batteries (VRFB), zinc-bromine flow batteries (ZBFB), and all-iron flow batteries (IFB), with a focus on primary materials used in functional components. Furthermore, we performed sensitivity analysis for selected materials to explore the uncertainty due to dynamic variation in market prices. The normalized results indicate that the major cost contributors for each battery type vary significantly over time, and the historical variations in material prices could largely affect the battery system production cost. Thus, material costs should be considered as a key attribute in material selection and product design for installing flow battery technologies in the electric grid.

Power grid operations increasingly interact with environmental systems and human systems such as transportation, agriculture, the economy, and financial markets. Our objective is to discuss the modelling gaps and opportunities to advance the science for multisector adaptation and tradeoffs. We focus on power system operational models, which typically represent key physical and economic aspects of grid operations over days to a year and assume a fixed power grid infrastructure. Due to computational burden, models are typically customized to reflect regional resource opportunities, data availability, and applications of interest. We conceptualize power system operational models with four core processes: physical grid assets (generation, transmission, loads, and storage), model objectives and purpose, institutions and decision agents, and performance metrics. We taxonomize the representations of these core processes based on a review of 23 existing models. Using science questions around grid and short term uncertainties, long term global change, and multisectoral technological innovation as examples, we report on tradeoffs in process fidelity and tractability that have been adopted by the research community to represent multisectoral interactions in power system operational models. Our recommendations for research directions are model-agnostic, focusing on core processes, their interactions with other human systems, and consider computational tradeoffs.

Air Resources Division, National Park Service, Denver, Colorado, USA; Department of Meteorology and Measurement, Bay Area Air Quality Management District, San Francisco, California, USA; Integrated Renewable Energy Systems Network, Davis, California, USA; EPRI, Palo Alto, California, USA; Department of Civil and Environmental Engineering, University of California, Irvine, California, USA; Cantech Environmental Services, Toronto, Ontario, Canada

Battery storage technologies such as redox flow batteries (RFBs) and lithium-ion batteries (LIBs) are appealing candidates for large-scale energy storage requirements to support the integration of renewable energy into electric grids. To ensure that their environmental benefits outweigh the environmental costs of producing battery storage systems, it is vital to assess the potential health impacts of battery materials and waste emissions during production. Here, we present a case study based on life cycle impact assessment (LCIA) to characterize the toxicity hazard associated with the production of six types of battery storage technologies including three RFBs [vanadium redox flow battery (VRFB), zinc-bromine flow battery (ZBFB), and the all-iron flow battery (IFB)], and three LIBs [lithium iron phosphate (LFP), lithium nickel cobalt manganese hydroxide (NCM), and lithium manganese oxide (LMO)]. USETox® v2.0 (USETox®) was used for LCIA and we found higher impacts found higher impacts on human health outcomes for the production of LIBs than for RFBs, noting that uncertainties associated with the characterization factors demand caution in interpreting the results. Overall, the study provides (1) a comprehensive evaluation of life cycle impacts for materials, components, and systems associated with the production of burgeoning six battery energy storage technologies and (2) an important foundation for the identification of battery technologies with lower potential negative impacts associated with integrating energy storage in strategies for upscaling renewable energy sources.

Energy storage systems are critical for enabling the environmental benefits associated with capturing renewable energy to displace fossil fuel-based generation, yet producing these systems also contributes to environmental impacts through their materials use and manufacturing. As energy storage capacity is scaled up to support increasingly renewable grids, the environmental benefits from their use may scale at different rates than the environmental impacts from their production. This implies the existence of capacity thresholds beyond which installing additional storage capacity may be environmentally detrimental. Identifying such thresholds are important for ensuring that energy storage capacity selection in future grids are consistent with net emissions reduction goals, but such thresholds have not been studied in the present literature. To identify such thresholds, here we combine electric grid dispatch modeling with life cycle analysis to compare how the emissions reductions from deploying three different flow battery energy storage types on a future California grid (>80% wind and solar) compare with emissions contributions from producing such batteries as total battery capacity installed on the grid increases. Depending on the type of battery and environmental impact indicator (greenhouse gas or particulate matter emissions), we find that the marginal environmental benefits of storage begin to diminish at deployed capacities of 38-76% of the mean daily renewable generation (256-512 GWh in our California scenarios) and reach zero at 105-284% of mean daily renewable generation (700-1810 GWh). Such storage capacities are conceivable, but upstream impacts of storage must be assessed in evaluating the environmental benefits of large-scale storage deployment, or they could negate the environmental benefits of regional electricity system decarbonization.

Climate change mitigation requires developing zero-carbon, highly renewable energy systems, which require technologies to capture excess renewable electricity such as energy storage. Endeavoring to capture all available excess renewable electricity, however, may require large energy storage capacities and costs. This study therefore investigates how much curtailment is cost-optimal to allow in developing fully decarbonized electricity systems, using compliance with California's Senate Bill 100 goal as a representative case study. We combine electric grid dispatch modeling with an optimization approach for selecting the composition of energy storage technologies to capture excess renewable electricity to minimize overall system costs. We found that overbuilding cheap wind and solar and allowing the curtailment of excess renewable electricity equivalent to 25–43% of the total annual electric load resulted in the lowest cumulative systemwide cost for a fully decarbonized electricity system of about $1.8 trillion, spent between 2020 and 2045. Allowing no renewable curtailment results in significant battery requirements and a cumulative systemwide cost of $5.2 trillion spent between 2020 and 2045. Therefore, allowing some curtailment reduced the cost of building a fully decarbonized electricity system by a factor of 3 when the portfolio of technologies to capture and manage excess renewable electricity is carefully chosen.

Plug-in electric vehicles charged with zero-carbon electricity are important for decarbonizing regional energy systems. Flexible charging of these vehicles aids with grid integration of wind and solar generation but may require drivers to provide information about their travel patterns and allow grid operators to control the charging of their vehicles. Limited acceptance of flexible charging can potentially limit greenhouse gas emissions reductions from electric vehicle deployment. Therefore, here we assess how varying the extent of consumer acceptance of flexible charging affects electric vehicle greenhouse gas emissions reductions in a highly decarbonized California grid (>70% zero-carbon), a region with mandated zero-emission vehicle deployment and electricity decarbonization targets. We quantify the monetary value of flexible charging based on the reduction in stationary storage required to achieve a given zero-carbon penetration as flexible charging is adopted. We find that increased participation in smart charging and vehicle-to-grid increases zero-carbon generation uptake by up to 5.2% and 11.1%, respectively. The value of smart charging only reaches $87 per vehicle-year while that for vehicle-to-grid can reach $2,850 per vehicle-year. Non-monetary incentives may be needed to increase smart charging participation. These results can inform future analyses on the supply and demand for participation in flexible charging programs.