End-use Electrification Research Articles

Diverse decarbonization pathways under near cost-optimal futures

Energy system optimization models offer insights into energy and emissions futures through least-cost optimization. However, real-world energy systems often deviate from deterministic scenarios, necessitating rigorous uncertainty exploration in macro-energy system modeling. This study uses modeling techniques to generate diverse near cost-optimal net-zero CO2 pathways for the United States’ energy system. Our findings reveal consistent trends across these pathways, including rapid expansion of solar and wind power generation, substantial petroleum use reductions, near elimination of coal combustion, and increased end-use electrification. We also observe varying deployment levels for natural gas, hydrogen, direct air capture of CO2, and synthetic fuels. Notably, carbon-captured coal and synthetic fuels exhibit high adoption rates but only in select decarbonization pathways. By analyzing technology adoption correlations, we uncover interconnected technologies. These results demonstrate that diverse pathways for decarbonization exist at comparable system-level costs and provide insights into technology portfolios that enable near cost-optimal net-zero CO2 futures.

The role of electrification and the power sector in U.S. carbon neutrality

The United States has pledged to achieve net-zero greenhouse gas emissions by 2050. We examine a series of net-zero CO2 scenarios to investigate the impact of advanced electrification of end-use sectors on the dynamics of America's net-zero transition through 2050. Specifically, we use an integrated assessment model, GCAM-USA, to explore how advanced electrification can influence the evolution of the electricity system in pursuit of net-zero. State-level resolution for end-use demand sectors and energy transformation is a key feature of GCAM-USA that allows for elucidation of the variation in end-use electrification across states. All scenarios in this study are designed to be consistent with the modeling protocol for the Energy Modeling Forum Study 37 model inter-comparison project. Our scenarios show the scale of transformation in the power sector with average annual capacity additions reaching 121-143 GW/year and 172-190 GW/year in 2050 net-zero CO2 scenarios and 2045 net-zero CO2 scenarios, respectively, in the 2040s — approximately three to five times the 2021-2023 average. In 2050 net-zero CO2 scenarios, electrification rates in 2050 range from 15-48 % for transportation, 65-83 % for buildings, and 20-38 % for industry. If net-zero CO2 is achieved in 2045, transportation, buildings, and industry are 27-53 %, 78-84 %, and 41-53 % electrified by 2050, respectively. Advanced electrification of end-use sectors can reduce the magnitude of reliance on negative emissions by driving down residual positive emissions by mid-century. Altogether, our results demonstrate that a net-zero transition in the United States will require deep and rapid structural changes to the energy system.

Hydrogen Blending in Natural Gas Grid: Energy, Environmental, and Economic Implications in the Residential Sector

The forthcoming implementation of national policies towards hydrogen blending into the natural gas grid will affect the technical and economic parameters that must be taken into account in the design of building heating systems. This study evaluates the implications of using hydrogen-enriched natural gas (H2NG) blends in condensing boilers and Gas Adsorption Heat Pumps (GAHPs) in a residential building in Rome, Italy. The analysis considers several parameters, including non-renewable primary energy consumption, CO2 emissions, Levelized Cost of Heat (LCOH), and Carbon Abatement Cost (CAC). The results show that a 30% hydrogen blend achieves a primary energy consumption reduction of 12.05% and 11.19% in boilers and GAHPs, respectively. The presence of hydrogen in the mixture exerts a more pronounced influence on the reduction in fossil primary energy and CO2 emissions in condensing boilers, as it enhances combustion efficiency. The GAHP system turns out to be more cost-effective due to its higher efficiency. At current hydrogen costs, the LCOH of both technologies increases as the volume fraction of hydrogen increases. The forthcoming cost reduction in hydrogen will reduce the LCOH and the decarbonization cost for both technologies. At low hydrogen prices, the CAC for boilers is lower than for GAHPs; therefore, replacing boilers with other gas technologies rather than electric heat pumps increases the risk of creating stranded assets. In conclusion, blending hydrogen into the gas grid can be a useful policy to reduce emissions from the overall natural gas consumption during the process of end-use electrification, while stimulating the development of a hydrogen economy.

Demand response programs: Comparing price signals and direct load control

Canada's electric power system is responsible for approximately 9 % of national emissions, 53 % of which occur in the province of Alberta. Integrating new variable renewable energy resources is a key part of the supply-side decarbonization pathway, while end-use electrification unlocks further opportunities on the demand side. The inherent variability of variable renewable energy output necessitates network flexibility. Supply-side flexibility solutions require significant investment, but demand-side management programs have potential to deliver network flexibility at a lower cost. An integrated framework consisting of demand and supply models investigates the efficacy of demand response programs for improving network flexibility in Alberta's power system, as measured by multiple operational metrics. The framework is applied to two demand response programs: real-time pricing and direct load control. These programs are assessed for two generation capacity mixes derived from an expansion planning model. Results indicate that substantial network flexibility benefits are achievable in a zero-emission power system via both programs resulting in avoided wind curtailment by 7.7 %. Improvement in operational costs, up to 1.4 % of the base output, is also observed in all scenarios accompanied by savings in household power bill expenditure by up to 15 %. These improvements, however, are only achieved fully when sufficient flexible load is provided.

Electric-gas infrastructure planning for deep decarbonization of energy systems

The transition to a deeply decarbonized energy system requires coordinated planning of infrastructure investments and operations serving multiple end-uses while considering technology and policy-enabled interactions across sectors. Electricity and natural gas (NG), which are vital vectors of today’s energy system, are likely to be coupled in different ways in the future, resulting from increasing electrification, adoption of variable renewable energy (VRE) generation in the power sector and policy factors such as cross-sectoral emissions trading. This paper develops a least-cost investment and operations model for joint planning of electricity and NG infrastructures that considers a wide range of available and emerging technology options across the two vectors, including carbon capture and storage (CCS) equipped power generation, low-carbon drop-in fuels (LCDF) as well as long-duration energy storage (LDES). The model incorporates the main operational constraints of both systems and allows each system to operate under different temporal resolutions consistent with their typical scheduling timescales. We apply our modeling framework to evaluate power-NG system outcomes for the U.S. New England region under different technology, decarbonization goals, and demand scenarios. Under a global emissions constraint, ranging between 80%–95% emissions reduction compared to 1990 levels, the least-cost solution relies significantly on using the available emissions budget to serve non-power NG demand, with power sector using only 14%–23% of the emissions budget. Increasing electrification of heating in the buildings sector results in greater reliance on wind and NG-fired plants with CCS and results in similar or slightly lower total system costs as compared to the business-as-usual demand scenario with lower electrification of end-uses. Interestingly, although electrification reduces non-power NG demand, it leads to up to 24% increase in overall NG consumption (both power and non-power) compared to the business-as-usual scenarios, resulting from the increased role for CCS in the power sector. The availability of low-cost LDES systems reduces the extent of coupling of electricity and NG systems by significantly reducing fuel (both NG and LCDF) consumption in the power system compared to scenarios without LDES, while also reducing total systems costs by up to 4.6% for the evaluated set of scenarios.

Integrated analysis of end-use electrification and cross-border electricity trade policies for hydropower enabled energy transformation in Nepal

Whether an enormous untapped hydropower resource should be utilized domestically by heavily electrifying energy end-uses or should be exported to neighboring countries is often debated in Nepal. This study attempts to bring both policy options together and justifies with evidence the need to integrate end-use electrification and cross-border electricity trade policies in the energy transformation of Nepal. We found out that Nepal will continue to import electricity till 2027 to meet its electricity demand throughout the year though it has already started exporting its surplus electricity during the wet season because of the full availability of run-of-river type hydropower. The run-of-river will continue to dominate Nepal's least-cost generation mix with a two-thirds share resulting in considerable surplus electricity during the high-flow season. Such surplus will exceed one-third of its total energy generation capacity in long-run in all end-use electrification scenarios (low to high). Nepal can use its existing cross-border electricity trade mechanism to sell its surplus electricity and can generate revenue of 67 billion USD in the high electrification scenario, which, combined with savings from fossil fuel import savings, can provide 85 % of total electricity generation investment needs.

Data-driven analysis of influential factors on residential energy end-use in the US

Decarbonizing the residential buildings sector is important to realize a net-zero future. However, little research comprehensively explores how residential energy by end-uses, i.e., space heating, space cooling, water heating, and appliances, vary across different climate, building, and occupant characteristics. Therefore, based on Residential Energy Consumption Survey 2015, this study investigates how these energy end-uses correlated with different influential factors, i.e., climate, demographics, housing and appliance features. Recursively random forest regression and partial dependency plots were employed to analyze and quantify the impact of influencing factors on end-use energy usage. The developed models illustrate nonlinear and varying impacts of influential factors on different end-uses, with R-square from 0.481 (appliance) to 0.885 (space cooling). Specifically, housing size and climate are determinant factors of space heating/cooling, while family size and total appliance number determine water heating and appliance usage, respectively. Use frequency, size, and vintage of appliances (e.g., refrigerator, laundry) affect appliance energy consumption. Furthermore, one-way ANOVA confirms the statistically significant differences in energy consumption across varying household income groups, i.e., households with higher incomes consume more energy. Houses with older vintages use more total energy, especially in space heating, while less in cooling due to lower penetration of air conditioners. Finally, the analysis proves that residential end-use electrification, mainly space heating and water heating, is beneficial for energy efficiency. The findings contribute to understanding influential factors on different end-uses in households, which from a holistic level informs the potential pathway for building decarbonization, especially targeting at specific end-uses or occupant groups.

Bidirectional coupling of the long-term integrated assessment model REgional Model of INvestments and Development (REMIND) v3.0.0 with the hourly power sector model Dispatch and Investment Evaluation Tool with Endogenous Renewables (DIETER) v1.0.2

Abstract. Integrated assessment models (IAMs) are a central tool for the quantitative analysis of climate change mitigation strategies. However, due to their global, cross-sectoral and centennial scope, IAMs cannot explicitly represent the temporal and spatial details required to properly analyze the key role of variable renewable energy (VRE) in decarbonizing the power sector and enabling emission reductions through end-use electrification. In contrast, power sector models (PSMs) can incorporate high spatiotemporal resolutions but tend to have narrower sectoral and geographic scopes and shorter time horizons. To overcome these limitations, here we present a novel methodology: an iterative and fully automated soft-coupling framework that combines the strengths of a long-term IAM and a detailed PSM. The key innovation is that the framework uses the market values of power generations and the capture prices of demand flexibilities in the PSM as price signals that change the capacity and power mix of the IAM. Hence, both models make endogenous investment decisions, leading to a joint solution. We apply the method to Germany in a proof-of-concept study using the IAM REgional Model of INvestments and Development (REMIND) v3.0.0 and the PSM Dispatch and Investment Evaluation Tool with Endogenous Renewables (DIETER) v1.0.2 and confirm the theoretical prediction of almost-full convergence in terms of both decision variables and (shadow) prices. At the end of the iterative process, the absolute model difference between the generation shares of any generator type for any year is < 5 % for a simple configuration (no storage, no flexible demand) under a “proof-of-concept” baseline scenario and 6 %–7 % for a more realistic and detailed configuration (with storage and flexible demand). For the simple configuration, we mathematically show that this coupling scheme corresponds uniquely to an iterative mapping of the Lagrangians of two power sector optimization problems of different time resolutions, which can lead to a comprehensive model convergence of both decision variables and (shadow) prices. The remaining differences in the two models can be explained by a slight mismatch between the standing capacities in the real world and optimal modeling solutions based purely on cost competition. Since our approach is based on fundamental economic principles, it is also applicable to other IAM–PSM pairs.

Interpretable data-driven building load profiles modelling for Measurement and Verification 2.0

Accelerating the decarbonisation of the built environment necessitates increasing electrification of end-uses, which in turn poses the issue of rethinking the role of energy efficiency in conjunction with flexibility in grid interaction. This requires a better understanding of the electricity load profiles at hourly or sub-hourly intervals using techniques that are simple, reliable, and interpretable. To this extent, this study proposes a reformulation of the Time Of Week and Temperature modelling approach. This approach is able to separate the energy consumption dependence on building operational characteristics (Time Of Week) and on weather (outdoor air temperature), through a highly automated modelling workflow, necessitating minimal effort for model tuning. These features, along with its intrinsic interpretability due to its formulation using multivariate regression and the availability of open-source software, makes it an ideal starting point for applied research. The case study selected for the research is a fully electrified public building in Southern Italy. The building has been monitored for 5 years, before, during and after the COVID-19 lockdown. The novel model formulation is calibrated using hourly interval data with a Coefficient of Variation of Root Mean Square Error in the range of 20.0–28.5% throughout the various monitoring periods. The counterfactual analysis of electricity consumption indicates a 10.7–26.7% decrease in electricity consumption due to operational adjustments following COVID-19 lockdown, highlighting the impact of behavioural change. Finally, the possibility of additional workflow automation and enhanced interpretability is discussed.

Probabilistic modelling of seasonal energy demand patterns in the transition from natural gas to hydrogen for an urban energy district

The transition to a low-carbon energy system can be depicted as a “great reconfiguration” from a socio-technical perspective that carries the risk of impact shifts. Electrification with the objective of achieving rapidly deep decarbonisation must be accompanied by effective efficiency and flexibility measures. Hydrogen can be a preferred option in the decarbonisation process where electrification of end-uses is difficult or impractical as well as for long-term storage in energy infrastructure characterised by a large penetration of renewable energy sources. Notwithstanding the current uncertainties regarding costs, environmental impact and the inherent difficulties of increasing rapidly supply capacity, hydrogen can represent a solution to be used in multi-energy systems with combined heat and power (CHP), in particular in urban energy districts. In fact, while achieving carbon savings with natural gas fuelled CHP is not possible when low grid carbon intensity factors are present, it may still be possible to use it to provide flexibility services and to reduce emissions further with switch from natural gas to hydrogen. In this paper, a commercially established urban district energy scheme located in Southampton (United Kingdom) is analysed with the goal of exploring potential variations in its energy demand. The study proposes the use of scalable data-driven methods and probabilistic simulation to generate seasonal energy demand patterns representing the potential short-term and long-term evolution of the energy district.

Long-term multi-sector low-carbon transition pathway planning based on modified-grandfathering emission allocation method: A case study of China

Strict climate goals require a rapid reduction of carbon emissions across society. It is a considerable challenge to design decarbonization pathways considering co-operation in energy and carbon emissions across multiple sectors simultaneously. In order to obtain the decarbonization pathway for the whole society, this paper establishes a long-term multi-sector low-carbon transition pathway planning model. Besides inter-sectoral energy supply and demand, this study fully considers the allocation of carbon emissions quotas among different sectors by modified-grandfathering method, which takes into account both equity and efficiency principles. The decarbonization targets of different sectors, corresponding mitigation pathways and energy consumption can be calculated. China is taken as a case study. Results show that China's total energy consumption peaks at 5 billion tces around 2030, then falls below 4 billion in 2060, with the proportion of primary electricity and other clean energy reaching over 50 percent. Besides, the realisation of carbon neutralisation in China depends heavily on the improvement of carbon capture and storage (CCS) and end-use electrification rate. Moreover, the study of different quota allocation ways shows that the increase in the contribution rate of power system mitigation leads to the reduction of the total low-carbon transition costs, which also aggravates administrative difficulties.

MERLIN: Multi-agent offline and transfer learning for occupant-centric operation of grid-interactive communities

Building and power generation decarbonization present new challenges in electric grid reliability as a result of renewable energy source intermittency and increase in grid load caused by end-use electrification. To restore reliability, grid-interactive efficient buildings can provide grid flexibility services through demand response. Reinforcement learning is well-suited for energy management in grid-interactive efficient buildings as it is able to adapt to unique building characteristics compared to rule-based control and model predictive control. Yet, factors hindering the adoption of reinforcement learning in real-world applications include its sample inefficiency during training, control security and generalizability. Here we address these challenges by proposing the MERLIN framework for the training, evaluation, deployment and transfer of control policies for distributed energy resources in grid-interactive communities for different levels of data availability. We utilize a real-world community smart meter dataset to show that while independently trained battery control policies can learn unique occupant behavior and provide up to 60% performance improvement at the district level, transfer learning provides comparable building and district level performance while reducing training costs.

Impacts of end-use electrification on air quality and CO2 emissions in China's northern cities in 2030

Urban activities such as transportation and household heating and cooking, contribute to current air pollution and climate change. Electrification policies such as the transition to electric vehicles and the substitution of household coal with electricity, have been implemented at unprecedented levels in the “2 + 26” Cities (i.e., Beijing, Tianjin and 26 other cities in northern China), to reduce air pollutants and CO2 emissions at the point of use. We employed the Greenhouse gas and Air pollution Interactions and Synergies model to evaluate the impact of vehicle/residential electrification on air quality and CO2 emissions from 2017 to 2030. Contribution of the end-use sector depends on its relative importance to the emissions of each pollutant and the ability of each sector to reduce their emissions through electrification. Accordingly, electrifying the residential sector improved the air quality in the cities of Shijiazhuang, Xingtai and Baoding, while electrifying the transportation sector generated more local benefits in Beijing and Tianjin. The combination of fleet electrification and coal-to-electricity could reduce the annual mean PM2.5 concentration by 2.0 μg/m3 (4.4%) throughout the “2 + 26” Cities in 2030. Moreover, more rapid decarbonization of the power sector is needed to maximize the synergies between air quality and climate goals.

Net-zero CO2 by 2050 scenarios for the United States in the Energy Modeling Forum 37 study

The Energy Modeling Forum (EMF) 37 study on deep decarbonization and high electrification analyzed a set of scenarios that achieve economy-wide net-zero carbon dioxide (CO2) emissions in North America by mid-century, exploring the implications of different technology evolutions, policies, and behavioral assumptions affecting energy supply and demand. For this paper, 16 modeling teams reported resulting emissions projections, energy system evolution, and economic activity. This paper provides an overview of the study, documents the scenario design, provides a roadmap for complementary forthcoming papers from this study, and offers an initial summary and comparison of results for net-zero CO2 by 2050 scenarios in the United States. We compare various outcomes across models and scenarios, such as emissions, energy use, fuel mix evolution, and technology adoption. Despite disparate model structure and sources for input assumptions, there is broad agreement in energy system trends across models towards deep decarbonization of the electricity sector coupled with increased end-use electrification of buildings, transportation, and to a lesser extent industry. All models deploy negative emissions technologies (e.g., direct air capture and bioenergy with carbon capture and storage) in addition to land sinks to achieve net-zero CO2 emissions. Important differences emerged in the results, showing divergent pathways among end-use sectors with deep electrification and grid decarbonization as necessary but not sufficient conditions to achieve net zero. These differences will be explored in the papers complementing this study to inform efforts to reach net-zero emissions and future research needs.

The rise and stall of world electricity efficiency:1900–2017, results and insights for the renewables transition

In the coming renewables-based energy transition, global electricity consumption is expected to double by 2050, entailing widespread end-use electrification, with significant impacts on energy efficiency. We develop a long-run, worldwide societal exergy analysis focused on electricity. Our 1900–2017 electricity world database contains the energy carriers used in electricity production, final end-uses, and efficiencies. We find world primary-to-final exergy (i.e. conversion) efficiency increased rapidly from 1900 (6%) to 1980 (39%), slowing to 43% in 2017 as power station generation technology matured. Next, despite technological evolution, final-to-useful end-use efficiency was surprisingly constant (∼48%), due to “efficiency dilution”, wherein individual end-use efficiency gains are offset by increasing uptake of less efficient end uses. Future electricity efficiency therefore depends on the shares of high efficiency (e.g. electrified transport) and low efficiency (e.g. cooling and low temperature heating) end uses. Our results reveal past conversion efficiency increases (carbon intensity of electricity production reduced from 5.23 kgCO2/kWh in 1900 to 0.49 kgCO2/kWh in 2017) did little to decrease global electricity-based CO2 emissions, which rose 380-fold. The historical slow-pace of transition in generation mix and the need to electrify end-uses suggest that strong incentives are needed to meet climate goals.

Home Energy Upgrades as a Pathway to Home Decarbonization in the US: A Literature Review

This work aims to characterize how home energy upgrade projects and programs in the US have evolved over the past decade. It also identifies what changes are needed to drive expansion of the US energy retrofit market in such a way that addresses carbon emissions from buildings, improves resilience and upgrades the housing stock. This review focuses on whole-home energy upgrades, targeting deep energy retrofit savings of >30%. The topics we cover include trends in home electrification, US and European home energy upgrade programs, energy upgrade measure costs, business economics, and health effects. Key changes in project design noted in this review include: (1) the electrification of dwellings with rapidly improving heat pump systems and low-cost solar photovoltaic technology; and (2) a shift away from high-cost building envelope strategies and towards more traditional home performance/weatherization envelope upgrades. Promising program design strategies covered include: (1) end-use electrification programs; (2) novel financing approaches; (3) the use of carbon-based program and project metrics; and (4) “one-stop shop” programs. Based on the existing market barriers, we suggest that the industry should adopt new project performance metrics. Additionally, market drivers are needed to spur widespread energy upgrades in the US housing stock. Costs must be reduced, and projects designed to appeal to homeowners and contractors.

Integrated Assessment Modeling of Korea's 2050 Carbon Neutrality Technology Pathways

This integrated assessment modeling research analyzes what Korea's 2050 carbon neutrality would require for the national energy system and the role of the power sector concerning the availability of critical mitigation technologies. Our scenario-based assessment shows that Korea's current policy falls short of what the nation's carbon-neutrality ambition would require. Across all technology scenarios examined in this study, an extensive and rapid energy system transition is imperative, requiring the large-scale deployment of renewables and carbon capture & storage (CCS) early on and negative emission technologies (NETs) by the mid-century. Importantly, the rapid decarbonization of the power sector, along with the rapid electrification of end-uses, seems to be a robust national decarbonization strategy. Furthermore, we contextualize our net-zero scenario results using policy costs, requirements for natural resources, and the expansion rate of zero-carbon technologies. We find that the availability of nuclear power lowers the required expansion rate of renewables and CCS, alleviating any stress on terrestrial and geological systems. By contrast, the limited availability of CCS without nuclear power necessarily demands a very high penetration of renewables and significantly high policy compliance costs, which would decrease the feasibility of achieving the carbon neutrality target.

Grid-Forming Technologies Enabling a Decarbonized Power System [Technology Leaders

Electric Power Systems are undergoing rapid transformations toward those having increasing proportions of renewable generation (such as wind and solar), significant amounts of energy storage, advanced grid infrastructures, and a myriad of end-use electrification technologies. Driven by drastic cost reductions and deployment incentives, the solar contribution to U.S. electricity generation has increased from less than 0.1&#x0025; in 2010 to 3.3&#x0025; in 2020. Wind generation has seen similar trends in cost reduction and accounted for 8.4&#x0025; of U.S. electricity generation in 2020. [See Frequently Asked Questions (FAQs) - U.S. Energy Information Administration (EIA), &#x201C;What is U.S. electricity generation by energy source?,&#x201D; eia.gov/tools/faqs/.] To achieve the Biden administration&#x2019;s clean energy goals, hundreds of gigawatts more of wind and solar will need to come online in the next 15 years. Similar transformations are happening at a global scale, and countries have laid out pathways to achieve a net-zero energy sector by 2050 to tackle climate change. (See 2 Net Zero by 2050: A Roadmap for the Global Energy Sector, <uri>https://www.iea.org/events/net-zero-by-2050-a-roadmap-for-the-global-energy-system</uri>.)

Electrification: a central piece on the climate agenda

The transition to a net-zero emissions economy is gaining pace in the EU. The ‘Fit for 55’ package, which seeks to establish a clear and steep decarbonization trajectory, marks a significant progress in aligning the long-term net-zero ambitions and committing all economic sectors to contribute. The European electricity industry is leading the charge and offering the most cost-effective solution to decarbonize energy intensive sectors like transport, heating and cooling and industrial applications. As electricity becomes the cleanest energy vector, the ‘Fit for 55’ package introduces electrification as a core avenue for decarbonization. Going forward, the electrification of end-uses coupled with the deployment of clean generation capacities and the modernisation of electricity grids, will be essential for achieving the long-term climate objective.

Impacts of End-Use Electrification on Air Quality and Co2 Emissions in China's Northern Cities in 2030

Impacts of End-Use Electrification on Air Quality and Co2 Emissions in China's Northern Cities in 2030