Climate change and its influence on water systems increases the cost of electricity system decarbonization

doi:10.21203/rs.3.rs-3359999/v1

Download PDF

Article

Climate change and its influence on water systems increases the cost of electricity system decarbonization

https://doi.org/10.21203/rs.3.rs-3359999/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

The electricity sector faces a dual challenge: decarbonization and adaptation to climate change. In many regions, this challenge is complicated by interdependence of electricity and water systems, through hydropower and energy-intensive water resources. By coupling detailed water and electricity system models, we evaluate how climate change alters pathways to carbon-free generation across the Western Interconnect, emphasizing water interactions. We find that grid planning that ignores climate projections and water linkages underestimates the capacity and investment needed to achieve decarbonization and maintain grid reliability. By 2050, electricity use could grow by up to 2% annually but up to 8% in July from cooling and water-related electricity demand, while hydropower generation could decrease annually by 23%. To adapt, the region would need to build up to 139 GW of capacity between 2030 and 2050, which is equivalent to nearly thrice California’s peak demand and adds up to $150 billion (7%) in costs.

Earth and environmental sciences/Climate sciences/Climate change/Climate-change impacts

Scientific community and society/Energy and society/Energy supply and demand

Earth and environmental sciences/Hydrology

Decarbonization of the electric sector is a critical strategy to mitigate climate change ¹. To that end, several states in the Western United States (WUS) have set ambitious carbon-free generation targets ^2,3. At the same time, the WUS electricity system is also vulnerable to the impacts of climate change—including rising temperatures, changing precipitation patterns, declining snowpack, and more frequent extremes^4–8—which have already caused major grid disruptions in California and in the Pacific Northwest and are projected to intensify ^9–11, especially from energy demand for cooling ^12,13.

Further, climate change does not affect the electricity system in isolation. Electricity and water systems are closely connected in the WUS, where hydropower comprises about 20% of annual average generation¹⁴, and electricity use for water (including conveyance, groundwater pumping, and drinking and wastewater treatment) comprises about 7% of electricity consumption ¹⁵. Climate change may decrease surface water availability, which lowers hydropower generation and makes it more difficult to reach zero emissions targets. ^16–18 These impacts are likely to coincide with increased water demand from warming, which together typically raises associated energy use, such as for groundwater pumping ¹⁹. Additionally, climate adaptation measures by the water sector to augment supplies, such as with desalination or water recycling, can also be energy-intensive ^20,21. Failing to account for these changes in energy supply and demand via the water sector may overlook cascading vulnerabilities, jeopardize electricity system climate resilience, and make decarbonization goals elusive ^21–24.

Several studies have analyzed operations of the Western Coordinating Council (WECC), or the Western Interconnect region of the North American grid, with individual impacts of climate change either on electricity supply or on demand ^18,25–27, but few account for the compounding impacts on multiple power system components ^11,12, and most do not consider water system interactions with a detailed model²⁸. Similarly, climate vulnerability studies that evaluate energy-related aspects of water systems often only focus on hydropower, which ignores related changes to the complex and energy-intensive water system ^21,29, or only focus on thermal power plant cooling ^27,30–33, which is mostly irrelevant for the WECC ^34–36. Furthermore, evaluations of climate impacts on electricity systems typically hold the generation and transmission infrastructure fixed at their current levels ³⁷. The few electricity system planning studies ^33,38–42 that include multiple impacts from climate change as constraints on new infrastructure do not typically account for the different climate vulnerabilities and resource needs (i.e., energy storage) of a fully decarbonized grid.⁴³ For example, for a grid with majority intermittent renewable generation, it is particularly important to study the technologies that can replace any losses in hydropower resources, which are a key source of flexibility to buffer against fluctuations in solar and wind ⁴⁴. Such studies also often lack the high temporal or spatial representation of the transmission network and generators to evaluate complex power system dynamics. Finally, climate projections in prior work^11,42 are often from one or two Global Circulation Models (GCM) rather than from a larger ensemble, which is considered the best practice to account for climate model uncertainty, the largest source of climate uncertainty in the mid-century time horizon relevant for grid planning ^45,46.

Addressing these gaps, we link a water system model and an electricity system model to evaluate how the WECC grid could adapt to a range of potential climate futures and water sector pressures between 2030 to 2050, while transitioning to a carbon-free generation portfolio. Under an ensemble of climate projections, we first quantify the climate impacts that are expected to be most significant for the grid, including changes in energy demand for cooling and heating⁴⁷, energy demand related to water pumping and conveyance, and hydropower generation potential⁴⁸. We then use a high-resolution grid capacity expansion model of the WECC ⁴⁹ to optimize the buildout of generation and transmission and reach zero carbon emissions by 2050, subject to the estimated changes in demand and hydropower availability under the climate projections. Our results suggest that if the WECC ignores climate change impacts and associated water sector dynamics in planning, the grid will have insufficient resources to maintain system reliability and meet decarbonization goals. We find that because of climate change, by 2050 WECC electricity use could increase annually by +0.5% to +2.3% because of higher cooling and water-related electricity demand, while hydropower generation could change by -23% to +7%. Increases in electricity demand and decreases in hydropower availability are particularly detrimental because they are both concentrated in the summer, compounding stress on the grid during peak times. To adapt to these climate impacts, the WECC region would need to build up to 139 GW (+14%) more generating capacity and up to 13 GW (+16%) more transmission capacity between 2030 and 2050, increasing the cumulative cost of grid decarbonization over this period by up to $150 billion (+7%).

Coupling climate projections with water, load, and capacity expansion models to explore climate impacts and adaptation needs

In the first step of this analysis, we use a water resources model, the Western US Water Systems Model (WWSM; Figure 1b), ⁴⁸ that evaluates the change in hydropower generation potential and in water-related energy use from the WUS water system (from groundwater pumping, water conveyance, domestic water heating, irrigation, distribution, and drinking and wastewater treatment). The WWSM is run under an ensemble of climate projections (Figure 1a) from 15 Global Circulation Models (GCM) with the Representative Concentration Pathways (RCP) 8.5 emissions scenario, compared to historical climate from 1980 to 2010 ^50,51. Next, using load sensitivity factors⁴⁷, we estimate changes in electricity demand for building heating and cooling for each of 50 WECC load zones for the same climate projections (Figure 1c). Finally, these hydropower and energy demand changes for each climate projection are the basis for 15 climate scenarios for the electricity capacity expansion model SWITCH (Figure 1d), which co-optimizes the generation and transmission expansion and operations of the WECC grid across 50 load zones, choosing among more than 7000 candidate generation projects. With the SWITCH model we then compare the infrastructure buildout, dispatch, and cost of each climate scenario against a Baseline Scenario wherein the WECC region reaches carbon-free generation by 2050 but has a stationary climate. Below we describe results for these 15 climate scenarios with both hydropower and energy demand changes included. The Supplemental Information also includes results for each of the climate scenarios that isolate the impacts of (i) only changes in cooling and heating load, and (ii) only changes in water-related load and hydropower.

Climate change impacts hydropower generation, water-related energy demand, and heating and cooling demand

Under the ensemble of climate projections, temperatures rise across the entire WUS, especially in the Intermountain West. Drying is concentrated in the Southern half of the region, with some increases in precipitation in the Pacific Northwest (Figure 1a, Supplementary Figure 4). Consequently, the majority of these climate projections produce decreasing streamflow in key basins (such as the Colorado River Basin) and increasing agricultural water demand, resulting in a substitution of surface water for groundwater use, especially in California’s Central Valley ⁴⁸.

We first focus on how these impacts of climate change may affect WECC electricity demand and supply in 2050, the year targeted by many decarbonization goals. Across all climate scenarios, we find that load increases compared to the Baseline— by up to 35 TWh (+2.3% of annual load) (Figure 2a). These load increases are predominantly driven by changes in building cooling (up to 31 TWh or 2% of total WECC load) and compounded by water-related electricity use (up to 6 TWh or +0.4% of total WECC load), primarily from more groundwater pumping at greater depths. On the supply-side, hydropower generation in 2050 decreases across 10 of the 15 climate scenarios, declining by as much as 56 TWh (-23% of hydropower) annually from the Baseline Scenario. Even in the scenarios with wetter projected conditions (for example, CESM1-CAM5), additional hydropower generation is insufficient to offset load increases. Further, across all scenarios load increases are concentrated in the summer (by up to +8% or +11 TWh in July), exactly during the months when hydropower generation decreases are the greatest (Figure 2b), exacerbating grid stress during peak season.

While these climate impacts on electricity supply and demand coincide seasonally, they are not uniformly distributed throughout the WECC because of geographic variation in temperature and precipitation changes and in building and hydropower infrastructure. Decomposed regionally, the largest 2050 energy changes are from increased cooling loads in the Southwest (SW; defined as California, Nevada, Arizona, New Mexico), where about 90% of households currently use air-conditioning ⁵². In the SW, 2050 average temperature increases of up to 3 ^oC raise annual electricity use by up to 30 TWh compared to the Baseline Scenario (Figure 2c). In the Pacific Northwest (PacNW; defined as Oregon and Washington), where historically electric heating has been more prevalent and air-conditioning has been relatively rare, decreased electricity use for heating partially offsets increased electricity use for cooling. However, this lower net total result may underestimate future challenges if more PacNW households adopt air-conditioning to cope with warming, as has been the case since the unprecedented 2021 heat wave . Water-related load grows under most climate projections across the Mountain region (MT, defined as Colorado, Montana, Wyoming, Idaho, and Utah) and SW regions, although the increases are small (up to 5 TWh) relative to cooling load changes. This water-related load is not well correlated with precipitation in the SW, likely due to offsetting factors (groundwater pumping loads partially offset by less conveyance pumping from decreased inter-basin water transfers under drier scenarios). As expected, hydropower generation is strongly positively correlated with precipitation levels in all regions, and is negatively correlated with temperature, showing the harmful amplifying effects of climate futures that are both warmer and drier.

Adapting to climate impacts affects the buildout and operation of generating and transmission capacity and system costs

We find that adapting to these anticipated hydropower and load changes while meeting WECC-wide 2050 decarbonization requires investing in substantially more generating capacity for all climate scenarios. Cumulatively over the five modeled investment periods (2030, 2035, 2040, 2045, and 2050), 24 GW to 139 GW (+2% to +14%) more generating capacity is built under the climate scenarios than in the Baseline Scenario (Figure 3a). For reference, California’s 2022 peak demand during a record heat wave was 52 GW⁵³. Thus in the best-case, adapting to climate change would require building about half the generating capacity across the WECC as is currently needed to meet peak demand in California, and in the worst-case, adapting to climate change would require building almost three times California’s capacity (now about a 30% share of WECC peak demand ⁵⁴) by 2050.

Because of forecasted technology cost declines, across all climate scenarios the majority of this new generating capacity comes from battery storage and solar PV (up to 110 GW and 78 GW, respectively). However, there is also a tradeoff between building generation capacity or transmission capacity to adapt to climate change and reach decarbonization goals. Over the 2030 - 2050 period, 37 GW less to 13 GW more new transmission capacity is built under the climate scenarios (47 GW to 97 new capacity relative to 84 GW built under the Baseline; Figure 3a). The climate scenarios with less transmission investment (for example, CMCC-CM) tend to have more renewable generation capacity investments to compensate for the flexibility otherwise provided by the transmission network, and vice versa (for example, GFDL-CM3).

The importance of flexible generation to grid operations also grows when climate impacts to hydropower and load are more significant. In the climate scenarios with lower hydropower shortfalls and load increases (such as CanESM), most generation in 2050 tends to come from wind, and in scenarios with greater deficits, generation is primarily from solar complemented by flexible battery storage and geothermal resources (Figure 3b). For example, GFDL-ESM2M, the scenario with the largest net increase in generation compared to the Baseline Scenario in 2050, solar generation and battery discharge increase by 16% and 22%, respectively, and geothermal generates 5.8 TWh compared to 0 in the Baseline Scenario.

Overall, the additional generation, storage, and transmission capacity needed to adapt to climate change could add costs of $8 Billion to $150 Billion in Net Present Value (NPV) terms over 2030 – 2050 (Figure 3c). This is a +0.4% to +7% increase above the Baseline $2,000 Billion NPV of transmission and generating capacity, fuel, variable O&M, and fixed O&M costs to decarbonize the WECC grid by 2050. The technology and timing of capacity investments are key cost drivers; the most expensive scenario, GFDL-ESM2M, relies on pricier geothermal generation in addition to solar and storage to balance demands. Other scenarios like CanESM and bcc-csm1-1 are also more expensive because the least-cost solution includes significant early investments in wind capacity when costs are higher relative to solar costs in later periods (results on the capacity online by investment period in Supplementary Figures 1 -3).

Capacity additions and energy dispatch vary spatially and temporally under climate change

To further explore the impacts of climate change and water system dynamics on decarbonization efforts, we analyze how variations in climate impacts over different temporal and spatial scales may affect grid investment pathways leading up to 2050, and subsequent daily operations across and between the interconnected load zones of the WECC. We illustrate these effects by focusing the remaining discussion on ACCESS-1.0, the scenario with the greatest 2050 combined increase in load and decrease in hydropower generation (Figure 2a, full set of scenarios in Supplemental Figures 1 -3).

First without consideration of climate change impacts, we note that significant investments in solar, wind, and battery storage capacity are already needed to achieve 2050 decarbonization of the Baseline Scenario, especially starting in 2040 (Figure 4a). Adapting to temporally varying climate impacts will accelerate these investments non-linearly. Under ACCESS-1.0, additional wind resources are needed in the earlier investment periods compared to the Baseline, but as hydropower shortfalls increase and relative technology costs decline, by 2045 additional capacity shifts more to solar and storage (Figure 4a).

The changing mix of resources to adapt to climate change impacts also affects the daily and seasonal patterns of dispatch relative to the Baseline Scenario. Mainly solar generation is used to meet the summer peak and the growing fall load in 2050 (Figure 4b). However, the large investment in solar capacity comes at the cost of a substantial increase in spring curtailment (+93 GW at 11 am, i.e. +57%) when loads are not high enough to utilize all available solar generation. These results suggest that flexible demand management programs would be complementary measures to limit curtailment, and should be included in future studies of adaptation.

Finally, we find that the regional variation in climate impacts and water dynamics can have substantial effects on the geographic distribution of grid expansion in the WECC. Under the Baseline Scenario in 2050, the SW region hosts the majority of both solar and battery capacity, whereas the eastern half of the WECC hosts wind capacity (Figure 5a). The eastern half also has the majority of new investments in transmission capacity, enabling exports from the wind resource-rich areas to the western load centers. Under the ACCESS-1.0 scenario in 2050, declines in Pacific Northwest and Colorado River hydropower, and increases in electricity demand for cooling and for water in the SW affect the demand for more capacity locally and in neighboring load zones (Figure 2). To adapt, additional capacity investments come from least-cost solar and battery resources in the regions of greatest hydropower shortfalls and load growth, notably the Pacific Northwest, British Columbia, and the SW, and from wind capacity in the MT region (Figure 5b).

In the WECC, where the fate of the water and electricity systems are already closely tied, climate change impacts mediated through the water system will have important implications in future grid expansion. We find that by 2050, cooling and water-related loads increase in all climate scenarios, which is compounded in the majority of cases by decreases in hydropower generation, and made worse by their coincidence during the peak summer months. In the context of the transition to a zero-carbon grid, these changes in carbon-free hydropower resources and electricity demands affect the timing, magnitude, spatial distribution, and cost of optimal future generation and transmission investment and operation. Indeed, adapting to these climate impacts requires building up to 139 GW more generating capacity by 2050 across the WECC, almost thrice California’s current peak demand, which would add up to $150 Billion (+7%) to decarbonization costs. In scenarios with more substantial changes in hydropower generation and load, flexible resources, including battery storage, geothermal, and transmission capacity take on a larger role in maintaining grid reliability alongside large increases in solar capacity.

Our findings point to several areas of further research that would help to understand the opportunities and constraints for decarbonizing the electricity grid while simultaneously adapting to climate change. It would be valuable for future analyses to evaluate how demand response and other flexible demand programs may reduce the capacity additions needed to address resource shortfalls from climate warming ³⁸. Additionally, it is important to test how parallel transitions in the electricity sector, such as increased adoption of air-conditioning, widespread electrification of transportation and buildings, and availability of long-duration energy storage resources and hydrogen, may reinforce or ameliorate the challenges of climate change and water sector dependencies for the grid. Further study is also needed to understand and overcome the significant political and environmental barriers to transmission expansion across the WUS, which may make capacity additions difficult to achieve in practice. Finally, more study is needed of how climate extremes, such as extended and more intense droughts, could compound water and electricity systems.

Overall, these results underscore the importance of incorporating water sector interactions and climate projections into grid expansion models to help ensure a climate-resilient grid of the future. Without explicitly quantifying how climate change and water interdependencies may together affect future electricity supply and demand, grid planners may significantly underestimate the magnitude and type of resources needed to achieve decarbonization goals and maintain grid reliability.

In this analysis, we (1) quantify the climate impacts on hydropower availability, energy demand for water, and cooling demand in the WUS under a range of potential climate futures; and (2) evaluate the optimal WECC electricity grid buildout and operations both to meet decarbonization targets and to adapt to these projected climate impacts (Figure 1). We evaluate these connected models with the downscaled climate projections for 2030 - 2050 from an ensemble of 15 Global Circulation Models (GCM) that have been selected for skill in characterizing the regionally relevant hydroclimatic phenomenon, with the Representative Concentration Pathways (RCP) 8.5 emissions scenario, compared to historical climate from 1980 – 2010 ^50,51. We start with the water resources model, Western US Water Systems Model (WWSM) ⁴⁸ to evaluate the change in hydropower generation potential for almost 200 individual generators and water-related electric energy use from the WUS water system (including from groundwater pumping, water conveyance, domestic water heating, irrigation, water treatment and distribution, and wastewater treatment), under the climate projections relative to historical climate. The GCM temperature projections are also used with load sensitivity factors to estimate changes in energy demand for heating and cooling for each of 50 utility load zones ⁴⁷. These hydropower and energy demand changes adjust the inputs of the electricity planning model, SWITCH, which optimizes investment in generation and transmission in the WECC at five-year time steps from 2030 to 2050, co-optimized with hourly operations for a sample of representative days for each of the investment years. Each step of this analysis is summarized below and detailed in the Supplementary Information.

Climate Projections

During our study’s near-term, mid-century time horizon the majority of climate uncertainty comes from differences in GCMs, rather than from the relatively similar emissions scenarios ⁵⁵. Therefore, to encompass the range of possible futures we construct climate change scenarios with temperature [ºC] and precipitation [mm] variables from projections of 15 GCMs from the Coupled Model Intercomparison Project 5 (CMIP5) ensemble for 2015 – 2055. The 15 GCMs (ACCESS-1.0, CCSM, CESM-BGC, CMCC-CMS, CMCC-CM, CESM-CAM5, CNRM-CM5, CanESM, GFDL-CM3, GFDL-ESM2M, HadGEM2-CC, HadGEM2-ES, MIROC5, MPI-ESM-LR, and bcc-csm1-1) were chosen in a model selection study ⁵⁰ based on their performance at the global scale ⁵⁶, for the Southwest and Northwest region ⁵⁷, and for the state of California ⁵⁰. The GCM projections have been statistically downscaled based on the Locally Constructed Analog (LOCA) method and use the RCP 8.5 emissions scenario. These climate projections are compared to a Baseline Scenario based on historical 1980 – 2010 climate data ⁵¹.

Modeling hydropower generation and energy demand related to water with the Western U.S. Water Systems Model (WWSM)

The climate projections are inputs into WWSM, as well as into the calculation of energy demand changes for cooling and heating. WWSM is developed using the WEAP water resources management and watershed hydrology modeling platform ⁵⁸, which has been used in numerous studies to assess climate impacts on energy-water linkages ^36,59,60. WWSM covers the US portion of the WECC region with 147 rivers and 311 catchments (including the Columbia River, Snake River, Missouri River, Colorado River, Platte River, Salt River, Sacramento River, Feather River, and San Joaquin, among many others), long-distance and energy-intensive conveyance for inter-basin water transfers (including the State Water Project of California, the Central Valley Project of California, Colorado River Aqueduct from Arizona to California, and the Central Arizona Project), 50 urban water demand nodes, 133 major reservoirs (which together provide 280 Billion m³ of available storage capacity), and about 200 individual hydropower generators (about 48 GW of total generating capacity). WWSM also includes one desalination plant in Carlsbad, California ⁶¹ and non-potable reuse to supply urban outdoor demand from up to 5% of the urban indoor return flows in the drier Southwest states (California, Arizona, and Nevada). WWSM has been calibrated for the historical period of 1980 – 2010 on a monthly timestep for key hydrologic metrics using observational US Geological Survey (USGS) gauge data for streamflow and/or reservoir outflows ⁶².

Hydropower generators are parameterized based on hydraulic head, tailwater elevation, and max turbine flow based on publicly available data ^62–65 and generation in the Baseline Scenario is calibrated to match as closely as possible the historical monthly and annual generation patterns of individual generators ⁶³. WWSM also tracks the embedded energy along parts of the water system—including groundwater pumping, conveyance, treatment, water heating and irrigation, wastewater treatment, reuse, and desalination—by multiplying energy intensity values (energy use per unit of water, kWh/m³) with the monthly water volumes calculated in WWSM throughout the stages of this managed water cycle. Energy intensity values are either derived with first principles from endogenous model data (i.e. groundwater pumping based on water depth and flow, and conveyance energy based on flow and height water is lifted), exogenous calculations (distribution energy, water heating energy, agricultural energy), or averages across literature (desalination, treatment, wastewater treatment, reuse). The mathematical formulations of the mass balance and other model components are documented in detail in prior publications about WEAP and the WWSM model specifically ^48,58.

The changes in hydropower generation potential and water-related energy demand from WWSM relative to a historical Baseline are linked with the capacity expansion model SWITCH. For each climate projection and for each generator we calculate the monthly average WWSM generation potential for a rolling 10-year window to smooth inter-annual variability, centered on the investment years modeled in SWITCH (2030, 2035, 2040, 2045, and 2050). Then we calculate the “Delta ratio” by dividing these monthly average generation levels for each decade by the monthly average Baseline generation for each generator. We multiply these monthly Delta ratios for each decade from WWSM with the Baseline Scenario monthly average power and minimum power parameters by generator in SWITCH. For generators that are not modeled in WWSM (less than 30 MW), we use the average Delta ratios for each generator in that SWITCH load zone. If there are load zones in SWITCH with no hydropower generators included in WWSM, we use the average load zone Delta fractions from the nearest neighboring load zone. We also adjust the reserve capacity value that each hydropower generator can provide by calculating the new capacity factor (monthly average power/max capacity limit) with the Delta ratio-adjusted monthly average power values.

For each climate projection, we link the changes in electricity use related to water relative to the Baseline from WWSM with the total electricity demand by load zone in SWITCH. We first sum up the monthly electricity use in WWSM by category (water heating, treatment, distribution, groundwater pumping, irrigation, conveyance, wastewater treatment, reuse, and desalination) and by load zone. To smooth out inter-annual variability, we calculate the rolling-window decadal average monthly energy use for each energy category under the WWSM Baseline and under each climate projection. For each energy category and load zone, we calculate the absolute monthly delta for each decade as the difference between WWSM energy use under the climate projection and under the Baseline. Next, we allocate the monthly deltas by energy category and load zone to corresponding hourly deltas to match the temporal resolution of load data in SWITCH. We assign each energy category a daily “load shape,” which determines the share of a day’s total electricity that is used in each hour, based on a study of 24-hour patterns of water use of different water sector components⁶⁶ (Figure 6), and a mapping of water sectors and processes included in the WWSM model. For this calculation, we make a simplifying assumption that the electricity use associated with each water sector category follows the same 24-hour pattern as that of the corresponding water use category. We sum the resulting hourly deltas across all energy categories for each load zone and add those to the Baseline SWITCH hourly load to calculate the new total hourly load under each climate projection in SWITCH. Because of limited available data, climate impacts on electricity use related to water are only calculated for the WUS portion of the WECC; load zones in Canada and Mexico are excluded.

Future research is planned to evaluate how changes in water sector policies and climate adaptation measures could affect grid buildout. For example, because of stressed groundwater resources, water managers may need to replace declining surface water with alternative supplies to maintain reliable deliveries ^67–69. There are limited remaining low-energy-intensive water supplies ⁷⁰, therefore, many water adaptation strategies (including desalination and water recycling)^71–73 may also add to electricity capacity needs ^72,74. Additional study is also planned to evaluate scenarios with different 24-hour patterns of energy use related to water, especially for conveyance pumping during off-peak hours.

Modeling changes in energy demand for space heating and cooling

One of the major impacts of climate change on the electricity system is the increased electricity use for air-conditioning and decreased use for heating ⁷⁵. We estimate these electricity demand changes using heating and cooling sensitivity factors in mega-watt (MW) per degree-day change that have been calculated for the entire United States in a prior National Renewable Energy Laboratory (NREL) analysis for the Regional Energy Deployment System (ReEDS) model’s zones ⁴⁷. Degree days are the difference in mean daily temperature and a threshold temperature, above which cooling is typically needed (cooling degree day or CDD), and below which heating is typically needed (heating degree day or HDD) ⁷⁶. We first interpolate these CDD and HDD sensitivity factors from the ReEDS model’s zones to the SWITCH load zones by population-weighting. For each climate projection, we calculate the daily CDD and HDD from daily maximum and minimum temperatures at the population-weighted centroid of each SWITCH load zone using a threshold temperature of 18.3 ºC (65 ºF). To smooth out the inter-annual variability we calculate the change between the 10-year rolling average daily CDD and HDD and the historical daily average. We then calculate the change in energy demand as the product of the delta CDD or HDD and the sensitivity factor for each load zone, and sum these changes with the baseline SWITCH electricity demand in each hour. Only changes in WUS electricity use are included in the analysis because of lack of available data for Canadian and Mexican load zones of the WECC.

Capacity expansion for the WECC with the SWITCH Model

To optimize long-term energy system buildout under climate projections and given water sector adaptations, we use the capacity expansion model SWITCH. SWITCH is an open-source framework that can be configured with high spatial and temporal resolution capable of modeling systems with high levels of renewable resources ⁴⁹, and has been used to evaluate system expansion in several WECC case studies ^77,42,78,79. We build on the SWITCH 2.0 (Python) ⁴⁹, and the academic license of the Gurobi solver ⁸⁰, to evaluate the optimal generation and transmission capacity expansion and operations decisions for the WECC region out to 2050. We used a zonal representation of the WECC with 50 balancing areas or zones that model the existing transmission topology. The objective function minimizes the expected value of the total net present value of generation and transmission operations and investment, with a discount rate of 5%. The key decision variables (and results) include investment in generation and transmission capacity (MW of capacity built of each generator and transmission line for each investment period among the set of available candidate generators and transmission lines), and dispatch for a sample of hours (hourly generation and transmission line flows for each generator and transmission line online in that period).

The optimization is subject to a number of constraints, including technology operational constraints, limits on capacity investments in both generation and transmission, energy balance requirements for hourly load in each zone to equal generation and net imported energy transmitted into and out of the zone, the dispatch of generation and transmission flows limited to available capacity and line limits net of outages or derating factors, and dispatch constraints specific to variable generators (solar and wind), hydropower, and battery storage. There are also planning reserve constraints, which require the total available capacity of generators and imports meet or exceed a percentage (15%) above peak annual load (a reserve margin) in each “reserves area.” In addition to the above operational and investment constraints, we included two main policy constraints on the model for each investment period: a renewable portfolio standard requiring a percentage of annual load to come from renewable sources (wherever applicable according to current policies)³, and a cap on WECC total carbon emissions from generation which decreases to 0 from 2030 to 2050. The data, assumptions, objective function, and key constraints are described in more detail in the Supplemental Information. A full mathematical formulation of the SWITCH model is described in a prior paper ⁴⁹.

Data Availability Statement

The SWITCH-WECC model (version v2.0.0) is open source and published on GitHub (https://github.com/REAM-lab/switch). The WWSM model (version 1.0.0), the input data files used for WWSM and for the climate projections, and the results files referenced in this paper are available for download from a public “WWSM-WEAP-SWITCH” repository ⁸¹ published on GitHub (https://github.com/jszinai/WWSM-WEAP-SWITCH). The WWSM was developed within the WEAP software version 2022.0002 ⁸², which is developed and maintained by the Stockholm Environmental Institute (SEI). An evaluation version of the WEAP software, which allows users to open and view WWSM’s saved results, is available for free without a license purchase from SEI. To open and view the WWSM, you must first register on the WEAP website and download and install WEAP software from https://www.weap21.org/. A free tutorial on using the WEAP software is available on the WEAP website.

Acknowledgements

This material is based upon work supported by the Office of Science, Office of Biological and Environmental Research, Climate and Environmental Science Division, of the U.S. Department of Energy under contract No. DE-AC02-05CH11231 as part of the HyperFACETS Project, 'A framework for improving analysis and modeling of Earth system and intersectoral dynamics at regional scales' (award No. DE-SC0016605). We are also grateful for the support provided by the California Energy Commission for the prior work^28,42 which this presented study builds upon. Finally, we acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. For CMIP the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.

Williams, J. H. et al. The Technology Path to Deep Greenhouse Gas Emissions Cuts by 2050: The Pivotal Role of Electricity. Science 335, 53–59 (2012).
De León, K. SB-100 California Renewables Portfolio Standard Program: emissions of greenhouse gases. (2018).
U.S. State Electricity Portfolio Standards. Center for Climate and Energy Solutions https://www.c2es.org/document/renewable-and-alternate-energy-portfolio-standards/.
Barnett, T. P. et al. Human-Induced Changes in the Hydrology of the Western United States. Science 319, 1080–1083 (2008).
Dettinger, M., Udall, B. & Georgakakos, A. Western water and climate change. Ecological Applications 25, 2069–2093 (2015).
Hayhoe, K. et al. Emissions pathways, climate change, and impacts on California. PNAS 101, 12422–12427 (2004).
Rhoades, A. M., Jones, A. D. & Ullrich, P. A. The Changing Character of the California Sierra Nevada as a Natural Reservoir. Geophysical Research Letters 45, 13,008-13,019 (2018).
Manzago, O. N. Two-thirds of North America is at risk of energy shortfalls in high summer heat, NERC says. Today in Energy: Energy Information Administration https://www.eia.gov/todayinenergy/detail.php?id=56920.
Geranios, N. K. Rolling blackouts hit Pacific Northwest as cities swelter in record-breaking heat wave. Los Angeles Times (2021).
Roth, S. What caused California’s rolling blackouts? Climate change and poor planning. Los Angeles Times (2020).
Turner, S. W. D., Voisin, N., Fazio, J., Hua, D. & Jourabchi, M. Compound climate events transform electrical power shortfall risk in the Pacific Northwest. Nat Commun 10, 1–8 (2019).
Craig, M. T. et al. A review of the potential impacts of climate change on bulk power system planning and operations in the United States. Renewable and Sustainable Energy Reviews 98, 255–267 (2018).
Vine, E. Adaptation of California’s electricity sector to climate change. Climatic Change 111, 75–99 (2012).
EIA. Net Generation by State, Type of Producer, Energy Source (EIA-906, EIA-920, and EIA-923). EIA Detailed State Data https://www.eia.gov/electricity/data/state/.
Tidwell, V. C., Moreland, B. & Zemlick, K. Geographic Footprint of Electricity Use for Water Services in the Western U.S. Environ. Sci. Technol. 48, 8897–8904 (2014).
Tarroja, B., AghaKouchak, A. & Samuelsen, S. Quantifying climate change impacts on hydropower generation and implications on electric grid greenhouse gas emissions and operation. Energy 111, 295–305 (2016).
Yang, W. et al. Burden on hydropower units for short-term balancing of renewable power systems. Nat Commun 9, 2633 (2018).
Madani, K., Guegan, M. & Uvo, C. B. Climate change impacts on high-elevation hydroelectricity in California. J. Hydrol. 510, 153–163 (2014).
Moran, T., Choy, J. & Sanchez, C. The Hidden Costs of Groundwater Overdraft. Water in the West | Stanford Woods Institute for the Environment http://waterinthewest.stanford.edu/groundwater/ (2014).
Szinai, J. K., Deshmukh, R., Kammen, D. M. & Jones, A. D. Evaluating cross-sectoral impacts of climate change and adaptations on the energy-water nexus: A framework and California case study. Environ. Res. Lett. (2020) doi:10.1088/1748-9326/abc378.
Khan, Z., Linares, P. & García-González, J. Integrating water and energy models for policy driven applications. A review of contemporary work and recommendations for future developments. Renewable and Sustainable Energy Reviews 67, 1123–1138 (2017).
Harrison, P. A., Dunford, R. W., Holman, I. P. & Rounsevell, M. D. A. Climate change impact modelling needs to include cross-sectoral interactions. Nature Climate Change 6, 885–890 (2016).
Molyneaux, L., Wagner, L., Froome, C. & Foster, J. Resilience and electricity systems: A comparative analysis. Energy Policy 47, 188–201 (2012).
Reed, P. M. et al. Multisector Dynamics: Advancing the Science of Complex Adaptive Human-Earth Systems. Earth’s Future 10, e2021EF002621 (2022).
Auffhammer, M. Climate Adaptive Response Estimation: Short and Long Run Impacts of Climate Change on Residential Electricity and Natural Gas Consumption Using Big Data. https://www.energy.ca.gov/sites/default/files/2019-11/Energy_CCCA4-EXT-2018-005_ADA.pdf (2018).
Bartos, M. D. & Chester, M. V. Impacts of climate change on electric power supply in the Western United States. Nature Climate Change 5, 748–752 (2015).
Webster, M., Fisher-Vanden, K., Kumar, V., Lammers, R. B. & Perla, J. Integrated hydrological, power system and economic modelling of climate impacts on electricity demand and cost. Nat Energy 7, 163–169 (2022).
Hidalgo-Gonzalez, P. Learning and Control Systems for the Integration of Renewable Energy into Grids of the Future. (University of California, Berkeley, 2020).
Rheinheimer, D. E., Tarroja, B., Rallings, A. M., Willis, A. D. & Viers, J. H. Hydropower representation in water and energy system models: a review of divergences and call for reconciliation. Environ. Res.: Infrastruct. Sustain. 3, 012001 (2023).
Liu, L., Hejazi, M., Li, H., Forman, B. & Zhang, X. Vulnerability of US thermoelectric power generation to climate change when incorporating state-level environmental regulations. Nat Energy 2, 1–5 (2017).
Miara, A. et al. Climate and water resource change impacts and adaptation potential for US power supply. Nature Climate Change 7, 793 (2017).
Sattler, S. et al. Linking electricity and water models to assess electricity choices at water-relevant scales. Environ. Res. Lett. 7, 045804 (2012).
Steinberg, D. C. et al. Decomposing supply-side and demand-side impacts of climate change on the US electricity system through 2050. Climatic Change 158, 125–139 (2020).
Tidwell, V. C., Bailey, M., Zemlick, K. M. & Moreland, B. D. Water supply as a constraint on transmission expansion planning in the Western interconnection. Environ. Res. Lett. 11, 124001 (2016).
Yates, D., Meldrum, J. & Averyt, K. The influence of future electricity mix alternatives on southwestern US water resources. Environ. Res. Lett. 8, 045005 (2013).
Yates, D. et al. A water resources model to explore the implications of energy alternatives in the southwestern US. Environ. Res. Lett. 8, 045004 (2013).
Voisin, N. et al. Impact of climate change on water availability and its propagation through the Western U.S. power grid. Applied Energy 276, 115467 (2020).
Cohen, S. M. et al. A multi-model framework for assessing long- and short-term climate influences on the electric grid. Applied Energy 317, 119193 (2022).
Handayani, K., Filatova, T., Krozer, Y. & Anugrah, P. Seeking for a climate change mitigation and adaptation nexus: Analysis of a long-term power system expansion. Applied Energy 262, 114485 (2020).
Parkinson, S. C. & Djilali, N. Robust response to hydro-climatic change in electricity generation planning. Climatic Change 130, 475–489 (2015).
Ralston Fonseca, F. et al. Effects of Climate Change on Capacity Expansion Decisions of an Electricity Generation Fleet in the Southeast U.S. Environ. Sci. Technol. 55, 2522–2531 (2021).
Wei, M. et al. Building a Healthier and More Robust Future: 2050 Low-Carbon Energy Scenarios for California. https://www.energy.ca.gov/2019publications/CEC-500-2019-033/CEC-500-2019-033.pdf (2017).
Khan, Z. et al. Impacts of long-term temperature change and variability on electricity investments. Nat Commun 12, 1643 (2021).
Chang, M. K., Eichman, J. D., Mueller, F. & Samuelsen, S. Buffering intermittent renewable power with hydroelectric generation: A case study in California. Applied Energy 112, 1–11 (2013).
Parker, W. S. Predicting weather and climate: Uncertainty, ensembles and probability. Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 41, 263–272 (2010).
Hawkins, E. & Sutton, R. The Potential to Narrow Uncertainty in Regional Climate Predictions. Bull. Amer. Meteor. Soc. 90, 1095–1108 (2009).
Sullivan, P., Colman, J. & Kalendra, E. Predicting the Response of Electricity Load to Climate Change. https://www.nrel.gov/docs/fy15osti/64297.pdf (2015).
Yates, D., Szinai, J. & Jones, A. Modeling the Water Systems of the Western US to Support Climate-Resilient Electricity System Planning. Preprint at https://doi.org/10.1002/essoar.10512623.1 (2022).
Johnston, J., Henriquez-Auba, R., Maluenda, B. & Fripp, M. Switch 2.0: A modern platform for planning high-renewable power systems. SoftwareX 10, 100251 (2019).
Lynn, E., Schwarz, A., Anderson, J. & Correa, M. Perspectives and Guidance for Climate Change Analysis. https://water.ca.gov/-/media/DWR-Website/Web-Pages/Programs/All-Programs/Climate-Change-Program/Climate-Program-Activities/Files/Reports/Perspectives-Guidance-Climate-Change-Analysis.pdf (2015).
Livneh, B. et al. A Long-Term Hydrologically Based Dataset of Land Surface Fluxes and States for the Conterminous United States: Update and Extensions. Journal of Climate 26, 9384–9392 (2013).
Residential Energy Consumption Survey (RECS) 2020. U.S. Energy Information Administration https://www.eia.gov/consumption/residential/data/2020/index.php?view=characteristics.
Araj, J. et al. Summer Market Performance Report Sept 2022 - California Independent System Operator. http://www.caiso.com/Documents/SummerMarketPerformanceReportforSeptember2022.pdf (2022).
Western Electricity Coordinating Council: Demand. Western Electricity Coordinating Council https://www.wecc.org/epubs/StateOfTheInterconnection/Pages/Demand.aspx.
Hawkins, E. & Sutton, R. The Potential to Narrow Uncertainty in Regional Climate Predictions. Bull. Amer. Meteor. Soc. 90, 1095–1108 (2009).
G. Flato et al. 2013: Evaluation of Climate Models. Climate Change 2013: The Physical Science Basis. https://www.ipcc.ch/report/ar5/wg1/evaluation-of-climate-models/ (2013).
Rupp, D. E., Abatzoglou, J. T., Hegewisch, K. C. & Mote, P. W. Evaluation of CMIP5 20th century climate simulations for the Pacific Northwest USA. Journal of Geophysical Research: Atmospheres 118, 10,884-10,906 (2013).
Yates, D., Sieber, J., Purkey, D. & Huber-Lee, A. WEAP21—A Demand-, Priority-, and Preference-Driven Water Planning Model. Water International 30, 487–500 (2005).
Albrecht, T. R., Crootof, A. & Scott, C. A. The Water-Energy-Food Nexus: A systematic review of methods for nexus assessment. Environ. Res. Lett. 13, 043002 (2018).
Howells, M. et al. Integrated analysis of climate change, land-use, energy and water strategies. Nature Climate Change 3, 621–626 (2013).
Carlsbad Desal Plant. Carlsbad Desal Plant https://www.carlsbaddesal.com/.
EIA. Form EIA-860. https://www.eia.gov/electricity/data/eia860/.
Form EIA-923 detailed data with previous form data (EIA-906/920). https://www.eia.gov/electricity/data/eia923/.
National Inventory of Dams. US Army Corps of Engineers https://nid.sec.usace.army.mil/ords/f?p=105:1::::::
Bureau of Reclamation. https://www.usbr.gov/projects/.
Andrew Funk & William B. DeOreo. Embedded Energy in Water Studies Study 3: End-use Water Demand Profiles. (2011).
Herman, J. et al. Advancing Hydro-Economic Optimization to Identify Vulnerabilities and Adaptation Opportunities in California’s Water System. https://www.energy.ca.gov/sites/default/files/2019-12/Water_CCCA4-CNRA-2018-016_ada.pdf (2018).
Medellín-Azuara, J. et al. Adaptability and adaptations of California’s water supply system to dry climate warming. Climatic Change 87, 75–90 (2008).
Tanaka, S. K. et al. Climate Warming and Water Management Adaptation for California. Climatic Change 76, 361–387 (2006).
Cooley, H. & Wilkinson, R. Implications of Future Water Supply Sources on Energy Demands. https://pacinst.org/wp-content/uploads/2012/07/report19.pdf (2012).
Rao, P., Kostecki, R., Dale, L. & Gadgil, A. Technology and Engineering of the Water-Energy Nexus. Annu. Rev. Environ. Resour. 42, 407–437 (2017).
Tarroja, B. et al. Evaluating options for Balancing the Water-Electricity Nexus in California: Part 1 – Securing Water Availability. Science of The Total Environment 497–498, 697–710 (2014).
Plappally, A. K. & Lienhard V, J. H. Energy requirements for water production, treatment, end use, reclamation, and disposal. Renewable and Sustainable Energy Reviews 16, 4818–4848 (2012).
Tarroja, B. et al. Evaluating options for balancing the water–electricity nexus in California: Part 2—Greenhouse gas and renewable energy utilization impacts. Science of The Total Environment 497–498, 711–724 (2014).
Auffhammer, M., Baylis, P. & Hausman, C. H. Climate change is projected to have severe impacts on the frequency and intensity of peak electricity demand across the United States. PNAS 114, 1886–1891 (2017).
Degree-days - U.S. Energy Information Administration (EIA). https://www.eia.gov/energyexplained/units-and-calculators/degree-days.php.
Sánchez-Pérez, P. A., Staadecker, M., Szinai, J., Kurtz, S. & Hidalgo-Gonzalez, P. Effect of modeled time horizon on quantifying the need for long-duration storage. Applied Energy 317, 119022 (2022).
Nelson, J. et al. High-resolution modeling of the western North American power system demonstrates low-cost and low-carbon futures. Energy Policy 43, 436–447 (2012).
Mileva, A., Johnston, J., Nelson, J. H. & Kammen, D. M. Power system balancing for deep decarbonization of the electricity sector. Applied Energy 162, 1001–1009 (2016).
Gurobi - The fastest solver. Gurobi https://www.gurobi.com/.
Szinai, J. WWSM-WEAP-SWITCH: WWSM v1.0. (2022) doi:10.5281/zenodo.7145299.
Jack Sieber, Stockholm Environment Institute. WEAP (Water Evaluation And Planning).

There is NO Competing Interest.

SupplementalInfoCCanditsinfluenceonwaterincreasescostofdecarbonization.docx

Download PDF

Version 1

posted

You are reading this latest preprint version

Climate change and its influence on water systems increases the cost of electricity system decarbonization

Status:

Version 1

Abstract

Figures

Main Text

Discussion and Conclusion

Methods

Declarations

Data Availability Statement

Acknowledgements

References

Additional Declarations

Supplementary Files

Status:

Version 1