Future Low-carbon Energy System Research Articles

Dynamic Modeling of a HeXe-Cooled Mobile Nuclear Reactor with Closed Brayton Cycle

Helium-xenon (HeXe)-cooled mobile nuclear reactors have promising potential in future low-carbon energy systems. However, there is currently a lack of fast and reliable tools for analyzing the complicated dynamic characteristics of such systems. In this study, we developed a comprehensive dynamic modeling approach for a HeXe-cooled nuclear power system coupled with a closed Brayton cycle (CBC). The system’s key components, including the reactor, printed circuit heat exchanger (PCHE), and turbomachinery, are lumped-modeled to capture their time-varying behavior. A step-solving algorithm that incorporates HeXe mass conservation iteration is designed. The verification results demonstrate that the dynamic program is robust and reliable, with each time step converging within 25 iterations and the HeXe mass remaining within the range of 3.755 ± 0.01 kg throughout the simulation meeting the law of mass conservation. Then, a 1500 s frozen start-up simulation for the coupled system is conducted, in which the CBC is started in the first 500 s by increasing the main shaft speed to 40% of the rated value, and then the reactor is started by inserting external reactivity between 500 and 800 s. Both the dynamic process and the steady-state performance after the start-up are analyzed. The results show that the system achieved a stable electrical output of 5.7 MWe with a thermal efficiency of 32.5%. This study lays a solid foundation for future work aimed at improving the overall efficiency and performance of HeXe-cooled nuclear power systems.

Electrolyte-supported solid oxide electrochemical cells for versatile operations

Electrolyte-supported solid oxide electrochemical cells (SOCs) offer advantages in terms of easier fabrication and enhanced mechanical properties, but achieving high performance and multifunctionality remains challenging. In this study, we develop high-performance and versatile electrolyte-supported SOCs using La0.9Sr0.1Ga0.8Mg0.2O3-δ (LSGM) electrolyte materials through microstructural engineering of Sr2Fe1.5Mo0.5O6-δ (SFM)-based fuel electrodes. We evaluate the cells for power generation, hydrogen production, and carbon dioxide reduction, showcasing the diverse potential of various fuel electrode configurations. Among these, the impregnated SFM@LSGM electrode achieves the best overall performance, with a maximum power density of 739 mW cm−2 in fuel-cell mode, a current density of −0.81 A cm−2 at 1.3 V during steam electrolysis, and an unprecedented current density of −1.92 A cm−2 at 1.5 V in CO₂ electrolysis. Furthermore, it exhibits satisfactory stability across all operational modes. These findings provide valuable insights into the design of versatile electrolyte-supported SOCs and open new possibilities for their flexible applications in future low-carbon energy systems.

Is Power-to-Gas always beneficial? The implications of ownership structure

Power-to-gas (PtG), a technology that converts electricity into hydrogen, is expected to become a core component of future low-carbon energy systems. While its economics and performance as a sector coupling technique have been well studied in the context of perfectly competitive energy markets, the distortions caused by the presence of large strategic players with a multi-market presence have received little attention. In this paper, we examine them by specifying a partial equilibrium model that provides a stylized representation of the interactions among the natural gas, electricity, and hydrogen markets. We calibrate our model using the future Dutch energy system as a reference. Using this model, we compare several possible ownership organizations for PtG to investigate how imperfect competition affects its operations. Evidence gained from these market simulations show that the effects of PtG vary with the multi-market profile of its operator. Producers of fossil-based hydrogen tend to make little use of PtG, whereas renewable power producers use it more to increase the electricity prices. Although PtG operations are profitable and can be welfare-enhancing, welfare distribution among agents is highly unequal when PtG is strategically operated in conjunction with variable renewable generation. In that case, PtG also raises environmental concerns as it stimulates the use of polluting thermoelectric generation.

Co-optimization of miller degree and geometric compression ratio of a large-bore natural gas generator engine with novel Knock models and machine learning

Large-bore natural gas reciprocating generator engines will play crucial roles in future low-carbon energy systems. Knock, as an abnormal combustion phenomenon, is a bottleneck for long time to restrict the engine performance improvement. Development and application of the reliable knock model can contribute the predictive engine control and optimization to further improve the engine efficiency and performance. The biggest challenge of developing the predictive knock model is the stochastic nature of the knock phenomenon. To bridge the technological gap, this study aims to develop a novel predictive knock model for a large-bore natural gas engine and showcase its application for co-optimization of the engine design and control parameters, together with the machine learning. The knock model, taking the effects of hot spots heat release rate and energy density into account, is calibrated by the statistical phenomenological knock factor. The 1-D engine simulation model embedded with the knock model is built and calibrated. The data-driven model based on machine learning is developed and used to predict the relation between the key parameters and the engine performance. The genetic algorithms are employed to achieve the multi-objectives global optimization of geometric compression ratio, Miller degree and other control parameters of the engine to reduce the exhaust gas temperature and improve the engine performance. The co-optimized results show that the engine exhaust gas temperature can be remarkably lowered and the indicated thermal efficiency is increased by 1–3% depending on the operational conditions, without degrading the engine power output and increasing the exhaust NOx emissions.

Incentivizing Frequency Provision of Power-to-Hydrogen Toward Grid Resiliency Enhancement

As a most promising alternative carrier of energy in the future low-carbon energy system, the possibility of power-to-hydrogen (P2H) generally proton exchange membrane (PEM)-based water electrolyzers, has been explored for frequency response provision. However, there remains an open question as to how to capture the interaction of P2H operation and frequency response provision, and incentivize such behaviors to enhance system resiliency. In this paper, we propose a marginal pricing mechanism for frequency response service provision to enhance grid resilience considering the participation of P2H. To depict the interaction between P2H operation and frequency response provision, a dynamic model of P2H is partially simplified to be incorporated into the system frequency response process. Case studies based on the IEEE RTS-24 system and a realistic Northwest power grid of China show that P2H can significantly improve the frequency response ability, especially reduce the startup of conventional units, so as to reduce carbon emissions. This effect is extremely appealing in the renewable-dominated cases.

Role of electrolytic hydrogen in smart city decarbonization in China

Distributed renewable energy is penetrating the urban energy system with a continuously increasing proportion. However, due to its natural randomness, a large number of energy storage resources are necessary. Electrolytic hydrogen could quickly follow the fluctuations of renewable energy and transform excess renewable energy into hydrogen stored for future use, which not only promotes the accommodation of renewable energy, but also drives the low-carbon development of construction, transportation, electricity, and other industries, thereby helping construct future low-carbon energy systems (FCES). However, few existing studies have conducted a systematic investigation on the role of electrolytic hydrogen in smart city decarbonization from both the supply and demand sides. Here, we develop a full-life-cycle optimization model of FCES with photovoltaic (PV) and power-to-hydrogen (P2H) planning to achieve decarbonization goals in China. Our results show that the annual hydrogen potential of 10 selected cities with different energy structures and quantities varies from 0.236 to 9.795 megatons, with a gap of more than 40-fold. Considering PV and P2H integration in FCES, the CO2 emissions of 10 cities in related fields decreased obviously under an 80 % photovoltaic penetration level (PPL). Compared with electrochemical storage, P2H shows better performance in PV integration of FCES from both economics and CO2 emissions. However, this advantage needs to be based on diverse terminal uses of electrolytic hydrogen.

Long-duration thermo-mechanical energy storage – Present and future techno-economic competitiveness

The extent to which long-duration energy storage (LDES) will support grid decarbonisation by enabling large penetration of renewable generation is subject to the achievement of suitable technical and economic performance. This study investigates the potential of established and novel thermo-mechanical energy storage (TMES) technologies to meet LDES targets, benchmarks TMES current and future techno-economic performance and highlights critical research developments. Results justify the priority of ensuring low storage costs over high roundtrip efficiency for LDES, thus endorsing novel concepts based on thermochemical energy storage. Besides adiabatic compressed air energy storage, novel TMES using metal oxidation/reduction and CaO hydration/dehydration reactions can potentially already meet the 20 USD/kWh cost target at 200 h duration, with current technology performance. The need for suggested and wide-ranging enhancements at material, device and system level is discussed, which may lead to TMES costs below 14 USD/kWh – competitive with long-duration solutions like hydrogen for covering the energy balancing needs of future low-carbon energy systems.

Federated reinforcement learning for smart building joint peer-to-peer energy and carbon allowance trading

The multi-energy system (MES), which is regarded as an optimum solution to a high-efficiency, green energy system and a crucial shift towards the future low-carbon energy system, has attracted great attention at the district building level. However, the current exploration of flexible MES operation has been hampered by (1) the increasing penetration of renewable energies and the complicated operation of coupling multi-energy sectors; (2) the privacy concern in the decentralization of the energy system; and (3) the lack of integration of the energy market and carbon emission trading scheme. To address the aforementioned challenges, this paper proposes a joint peer-to-peer energy and carbon allowance trading mechanism for a building community, and then models it as a multi-agent reinforcement learning (MARL) paradigm. In this setting, the flexibility of building local trading and the decarbonization of building energy management can both be fully utilized. To stabilize the training performance, an abstract critic network capturing system dynamics is introduced based on a deep deterministic policy gradient method. The technique of federated learning (FL) is also applied to speed up the training and safeguard the private information of each building in the community. Empirical results on a real-world test case evaluate its superior performance in terms of achieving both economic and environmental benefits, resulting in 5.87% and 8.02% lower total energy and environment costs than the two baseline mechanisms of peer-to-grid energy trading and peer-to-peer energy trading, respectively.

Shaping future low-carbon energy and transportation systems: Digital technologies and applications

Digitalization and decarbonization are projected to be two major trends in the coming decades. As the already widespread process of digitalization continues to progress, especially in energy and transportation systems, massive data will be produced, and how these data could support and promote decarbonization has become a pressing concern. This paper presents a comprehensive review of digital technologies and their potential applications in low-carbon energy and transportation systems from the perspectives of infrastructure, common mechanisms and algorithms, and system-level impacts, as well as the application of digital technologies to coupled energy and transportation systems with electric vehicles. This paper also identifies corresponding challenges and future research directions, such as in the field of blockchain, digital twin, vehicle-to-grid, low-carbon computing, and data security and privacy, especially in the context of integrated energy and transportation systems.

Shaping future low-carbon renewable energy systems

Shaping future low-carbon renewable energy systems

Land-use intensity of electricity production and tomorrow's energy landscape.

The global energy system has a relatively small land footprint at present, comprising just 0.4% of ice-free land. This pales in comparison to agricultural land use- 30-38% of ice-free land-yet future low-carbon energy systems that shift to more extensive technologies could dramatically alter landscapes around the globe. The challenge is more acute given the projected doubling of global energy consumption by 2050 and widespread electrification of transportation and industry. Yet unlike greenhouse gas emissions, land use intensity of energy has been rarely studied in a rigorous way. Here we calculate land-use intensity of energy (LUIE) for real-world sites across all major sources of electricity, integrating data from published literature, databases, and original data collection. We find a range of LUIE that span four orders of magnitude, from nuclear with 7.1 ha/TWh/y to dedicated biomass at 58,000 ha/TWh/y. By applying these LUIE results to the future electricity portfolios of ten energy scenarios, we conclude that land use could become a significant constraint on deep decarbonization of the power system, yet low-carbon, land-efficient options are available.

The value of recycling for low-carbon energy systems - A case study of Germany's energy transition

To achieve climate neutrality, synergies between circular economy and reduction of greenhouse gas emissions must be strengthened. Previously unused emission reduction potentials of resource efficiency are to be exploited. Since all potentially possible emission reduction measures are linked by interactions, the evaluation of a single measure in terms of cost efficiency, effectiveness, and compliance with climate protection targets is very complex and requires a model-based analysis that takes the entire energy system into account.This work advances an energy system model for Germany so that through comprehensive modeling of industrial processes and implementation of recycling options, the impact of recycling measures in the context of national greenhouse gas mitigation strategies can be analyzed.The scenario evaluation shows that different recycling strategies have large effects on the German energy system. Without recycling energy demand in 2050 will increase by more than 300 TWh and cost of transformation will rise by 85% compared to a reference scenario, with today's recycling rates. On the other hand, if maximum recycling rates can be achieved, costs of transformation can be reduced by 26% until 2050. Recycling is an essential and cost-efficient greenhouse gas reduction strategy for future low-carbon energy system designs.

Energy futures as societal futures: Co-evolutionary scenarios linking futures of society and decarbonized energy systems in Switzerland 2050

There is consensus that the global energy system will have to change substantially in the next decades to reach carbon neutrality. However, there are many visions of future energy systems and possible pathways leading to the corresponding futures. Sciences build scenarios describing possible low-carbon energy futures based primarily on techno-economic models, partially reducing uncertainty for informed policies. However, social scientists have argued that these models miss the social dimension in illustrating the energy transition, especially calling for understanding actors and opportunity spaces. And yet, other scholars go beyond looking at social dimensions within energy futures and try to capture the broader societal environment in backcasting or storytelling scenarios. This paper offers a new approach in capturing the future energy system as part of a co-evolutionary societal system. Complementing the methodological toolbox, we use Formative Scenario Analysis to develop four types of scenarios for the energy system within Switzerland in 2050. We demonstrate that scenarios achieving the political goals set by the Paris Agreement include substantial changes in all socio-political dimensions considered in the analysis. In terms of policy making, this indicates that the future low-carbon energy system can only be achieved by addressing many different fields in the societal sphere.

Gas fields and large shallow seismogenic reverse faults are anticorrelated

We investigated the spatial relationships among 18 known seismogenic faults and 1651 wells drilled for gas exploitation in the main hydrocarbon province of northern-central Italy, a unique dataset worldwide. We adopted a GIS approach and a robust statistical technique, and found a significant anticorrelation between the location of productive wells and of the considered seismogenic faults, which are often overlain or encircled by unproductive wells. Our observations suggest that (a) earthquake ruptures encompassing much of the upper crust may cause gas to be lost to the atmosphere over geological time, and that (b) reservoirs underlain by smaller or aseismic faults are more likely to be intact. These findings, which are of inherently global relevance, have crucial implications for future hydrocarbon exploitation, for assessing the seismic–aseismic behaviour of large reverse faults, and for the public acceptance of underground energy and CO2 storage facilities—a pillar of future low carbon energy systems—in tectonically active areas.

Nuclear fuel materials and its sustainability for low carbon energy system: A review

World energy generation for electricity is still dependent on fossil fuels since it is more reliable and secure than the current intermittent renewable energy systems. Although the integration of renewable energy as an energy mix is in progress, still it could not be able to replace fossil fuels. Dependency on fossil fuels will not only contribute to severe climate change but will also degrade future generation quality of life. Hence, the solution to quandary is by integrating nuclear power plants with those of renewable energy such as solar and wind to meet the energy demand and to ensure sustainability of energy source. The current operating nuclear power plants in the world use the concept of water-cooled reactors. It was designed so that the fast neutrons born from fission reactions were slowed down in the moderator to allow other fission reactions events in sustainable chain reactions. Besides, the slow neutrons with low energy is a favourable reactor feature for safe and efficient operation. The common types of nuclear fuel materials in water-cooled reactors are enriched uranium dioxide and natural uranium contained in nuclear fuel elements. After it has been used, the fuel elements will be stored as spent fuel. Prolonged storage of used nuclear fuels will make the volume of nuclear waste high and become hard to manage after a long period of storage. An effort to reprocess the spent fuel as to extract fissile and fertile material to be used in nuclear fuels usually was undertaken to reduce the waste volume. However, this process may lead to an undesirable proliferation of nuclear material. In this review article, research on the advancement of nuclear fuel materials will be discussed based on the reduction method of the nuclear spent fuel volume and radiotoxicity, as well as to study its sustainability for the future low carbon energy system.

Benefits of the multi-modality formulation in hydrogen supply chain modelling

Hydrogen is recognized as a key element of future low-carbon energy systems. For proper integration, an adequate delivery infrastructure will be required, to be deployed in parallel to the electric grid and the gas network. This work adopts an optimization model to support the design of a future hydrogen delivery infrastructure, considering production, storage, and transport up to demand points. The model includes two production technologies, i.e., steam reforming with carbon capture and PV-fed electrolysis systems, and three transport modalities, i.e., pipelines, compressed hydrogen trucks, and liquid hydrogen trucks. This study compares a multi-modality formulation, in which the different transport technologies are simultaneously employed and their selection is optimized, with a mono-modality formulation, in which a single transport technology is considered. The assessment looks at the regional case study of Lombardy in Italy, considering a long-term scenario in which an extensive hydrogen supply chain is developed to supply hydrogen for clean mobility. Results show that the multi-modality infrastructure provides significant cost benefits, yielding an average cost of hydrogen that is up to 11% lower than a mono-modality configuration.

Experiment strategy for evaluating advanced building energy management system

Buildings are envisioned to play an active role in future low-carbon energy systems. The complexity of building energy management systems increases as they interface more and more subsystems and domains. As an important step to achieve a higher technology readiness level, these energy management systems need to be systematically tested in real-life conditions. Currently, there are no standard testing and experiment strategies in buildings to handle the mentioned complexity. Additionally, the levels of details reported in the existing experimental studies are heterogeneous. This paper summarizes an application of a holistic testing method to a flexible fully-equipped prosumer with the goal of facilitating test preparation, execution, replication, and comparison. Several empirical suggestions are provided, and a hybrid quantification strategy with digital twins is presented.

Incorporation of wind power probabilities into long-term energy system development analysis using bottom-up models

For future low-carbon energy systems with high shares of renewable energy, temporal representation becomes the dominant factor that impacts the model outputs and analysis conclusions; therefore, relevant and complex modelling approaches are required. We present and apply specific methodology for modelling wind power plants in long-term planning models. It is based on wind power probability curves for each time slice and use of the semi-dynamic method for temporal aspect. Benefits of this approach include the representation of wind power extremes, correct address of balancing capacities and costs, partially retained chronology. We also evaluated the quantitative effect of this methodology on the results of the energy model. In determining the reasonable number of approximation steps for wind power probability curves, we found that a three-step approximation is sufficient to ensure the accuracy of model results.

Impact of power-to-gas on the cost and design of the future low-carbon urban energy system

Power-to-gas technology has been proposed as one component for future energy systems facing decarbonization targets. This paper presents a power-to-gas focused open optimization model for studying cost efficient design and operation of future urban energy system. The model is able to distinguish the benefits of different configurations of power-to-gas by modelling several energy vectors, including electricity, heating, and cooling alongside with different plant components. The usefulness of the built multi-vector model is illustrated by a case study where the benefits of power-to-gas are studied in the context of a medium-sized Nordic city. The results show that the city is able to reach carbon neutrality with the help of power-to-gas. Power-to-gas provides cost savings by reducing the need of heat storages and transmission capacity. The savings are greatest when the emission reduction goal is high and transmission capacity expansion is expensive. Direct air capture appears as the superior carbon dioxide source when compared to post combustion capture from flue gases due to costs and annual availability. The case study shows no economic benefit for distributed power-to-gas.

Analyzing the spatio-temporal variation of the CO2 emissions from district heating systems with “Coal-to-Gas” transition: Evidence from GTWR model and satellite data in China

Understanding the spatio-temporal heterogeneous effects of socioeconomic and meteorological factors on CO2 emissions from combinations of different district heating systems with “Coal-to-Gas” transition can contribute to the development of future low-carbon energy systems that are efficient and effective. This work downscales city-level CO2 emissions to a 3 × 3 km2 gridded level in northern China during 2012 to 2018. By employing the Geographically and Temporally Weighted Regression (GTWR) model, nighttime light (NTL) data are adopted as a proxy of the level of urbanization, and the Temperature-Humidity-Wind (THW) Index is used as a proxy of meteorological factors in the downscaling model. The results show that, for more than 85% of the cities, urbanization significantly enhances the CO2 emissions of district heating systems, while the THW Index shows negative impacts on CO2 emissions. Significant spatial and temporal heterogeneity exists. The grids with the highest CO2 emissions from coal-fired boilers (grids with annual variation >0.59 Gg CO2/year) are mainly located in nonurban areas of the two megacities Beijing and Tianjin and also in the capital cities of each province. Urbanization has larger effects on the CO2 emissions of natural gas-fired boilers than of coal-fired boilers and combined heat and power (CHP). The average growth rate of CO2 emissions of gas-fired boilers in the urban areas of the study regions was approximately 4.7 times that of nonurban areas. The spatio-temporal heterogeneous impacts of urbanization on CO2 emissions should therefore be considered in future discussions of clean heating policies and climate response strategies.