Energy Resources Research Articles

Dynamic in‐motion wireless charging systems: Modelling and coordinated hierarchical operation in distribution systems

AbstractThe high adoption of electric vehicles (EVs) and the rising need for charging power in recent years calls for advancing charging service infrastructures and assessing the readiness of the power system to cope with such infrastructures. This paper proposes a novel model for the integrated operation of dynamic wireless charging (DWC) and power distribution systems offering charging service to in‐motion EVs. The proposed model benefits from a hierarchical design, where DWC controllers capture the traffic flows of in‐motion EVs on different routes and translate them into estimations of charging power requests on power distribution system nodes. The charging power requests are then communicated with a central controller that monitors the distribution system operation by enforcing an optimal power flow model. This controller coordinates the operation of distributed energy resources to leverage charging power delivery to in‐motion EVs and mitigate stress on the distribution system operation. The proposed model is tested on a test distribution system connected to multiple DWC systems in Salt Lake City, and the findings demonstrate its efficiency in quantifying the traffic flow of in‐motion EVs and its translation to charging power requests while highlighting the role of distributed energy resources in alleviating stress on the distribution system operation.

PV Based Microgrid for Remote Area Electrification in Nigeria: A Systematic Review of Concepts and Extant Strategies

Centralized power generation, transmission and distribution system operations in Nigeria can no longer deliver affordable and reliable electricity to remote households, both on and off the national grid. Therefore, a balanced approach, through renewable energy generation is the best option that would potentially lead accelerated journey to full electrification in the country. Renewable energy has become a panacea to energy problems worldwide because it is clean, environmentally friendly and ultimately cheaper. Due to the massive capacity of Nigeria to generate electricity from its numerous green energy resources, it has become crystal clear that access to sustainable and reliable energy in Nigeria is required for proper economic and social development. This work is based on an extensive review of recent experiences of more than 120 papers covering mostly the off-grid PV sector in the past 15years. The review included: scientific journals, conference papers, (PhD) theses, books and scientific reports from governments/NGOs and publications from energy institutions. A comprehensive review of relevant concepts and current microgrids optimization strategies applied to sizing, siting, load estimation and energy management has been conducted. Future research directions and potential of PV based microgrids for rural electrification have equally been specified.

Trust-Based Detection and Mitigation of Cyber Attacks in Distributed Cooperative Control of Islanded AC Microgrids

In this study, we address the challenge of detecting and mitigating cyber attacks in the distributed cooperative control of islanded AC microgrids, with a particular focus on detecting False Data Injection Attacks (FDIAs), a significant threat to the Smart Grid (SG). The SG integrates traditional power systems with communication networks, creating a complex system with numerous vulnerable links, making it a prime target for cyber attacks. These attacks can lead to the disclosure of private data, control network failures, and even blackouts. Unlike machine learning-based approaches that require extensive datasets and mathematical models dependent on accurate system modeling, our method is free from such dependencies. To enhance the microgrid’s resilience against these threats, we propose a resilient control algorithm by introducing a novel trustworthiness parameter into the traditional cooperative control algorithm. Our method evaluates the trustworthiness of distributed energy resources (DERs) based on their voltage measurements and exchanged information, using Kullback-Leibler (KL) divergence to dynamically adjust control actions. We validated our approach through simulations on both the IEEE-34 bus feeder system with eight DERs and a larger microgrid with twenty-two DERs. The results demonstrated a detection accuracy of around 100%, with millisecond range mitigation time, ensuring rapid system recovery. Additionally, our method improved system stability by up to almost 100% under attack scenarios, showcasing its effectiveness in promptly detecting attacks and maintaining system resilience. These findings highlight the potential of our approach to enhance the security and stability of microgrid systems in the face of cyber threats.

Potential applications of microbial genomics in nuclear non-proliferation.

As nuclear technology evolves in response to increased demand for diversification and decarbonization of the energy sector, new and innovative approaches are needed to effectively identify and deter the proliferation of nuclear arms, while ensuring safe development of global nuclear energy resources. Preventing the use of nuclear material and technology for unsanctioned development of nuclear weapons has been a long-standing challenge for the International Atomic Energy Agency and signatories of the Treaty on the Non-Proliferation of Nuclear Weapons. Environmental swipe sampling has proven to be an effective technique for characterizing clandestine proliferation activities within and around known locations of nuclear facilities and sites. However, limited tools and techniques exist for detecting nuclear proliferation in unknown locations beyond the boundaries of declared nuclear fuel cycle facilities, representing a critical gap in non-proliferation safeguards. Microbiomes, defined as "characteristic communities of microorganisms" found in specific habitats with distinct physical and chemical properties, can provide valuable information about the conditions and activities occurring in the surrounding environment. Microorganisms are known to inhabit radionuclide-contaminated sites, spent nuclear fuel storage pools, and cooling systems of water-cooled nuclear reactors, where they can cause radionuclide migration and corrosion of critical structures. Microbial transformation of radionuclides is a well-established process that has been documented in numerous field and laboratory studies. These studies helped to identify key bacterial taxa and microbially-mediated processes that directly and indirectly control the transformation, mobility, and fate of radionuclides in the environment. Expanding on this work, other studies have used microbial genomics integrated with machine learning models to successfully monitor and predict the occurrence of heavy metals, radionuclides, and other process wastes in the environment, indicating the potential role of nuclear activities in shaping microbial community structure and function. Results of this previous body of work suggest fundamental geochemical-microbial interactions occurring at nuclear fuel cycle facilities could give rise to microbiomes that are characteristic of nuclear activities. These microbiomes could provide valuable information for monitoring nuclear fuel cycle facilities, planning environmental sampling campaigns, and developing biosensor technology for the detection of undisclosed fuel cycle activities and proliferation concerns.

Ventography and the spatial politics of wind

This article explores the co-production of wind energy resources and UK maritime territories in the North Sea. It shows how endeavors to map wind for energy are shaped by specific spatial imaginations, which are in turn making it possible for the UK to advance sovereign claims over volumetric spaces offshore. This follows a long history of efforts to study and map wind movements alongside significant chapters of colonialism, imperialism, and territorial dispossession. The practices involved in the transformation of atmospheric circulations into territorial claims center on what I call ventography: the systematic study and cartographic representation of wind in relation to political boundaries, a project which is shaped by, and subsequently enrolled in, territorialization, sovereign performances, and border regimes. In this vein, the intangible nature of wind, often thought to be beyond the grasp of spatial politics, is being transformed into a resource that is coming to play a role in the production and reconfiguration of space in altogether new ways. Through a focus on the UK’s attempts to transmute wind power into territorial power, this article traces how ventography is reshaping the scales and configurations of contemporary political geographies.

Enhancing the accuracy of wind power projections under climate change using geospatial machine learning models

This paper presents a geospatial artificial intelligence (GeoAI) approach for generating wind power projection maps employing various Machine Learning (ML) models. These models include Artificial Neural Network (ANN), Decision Tree (DT), Gaussian Process Regression (GPR), and Support Vector Regression (SVR), which collectively aim to provide insightful wind power forecasts under the effects of climate change. The framework considers different influential parameters affecting wind speed, including pressure gradient, temperature gradient, humidity, and topography. The study’s geographic focus is Cork City, Ireland. The investigation covers a historical period from 2000 to 2014 and extends to encompass two future climate scenarios, between 2015 and 2050. A comprehensive set of statistical skill scores is computed to gauge the models’ performance. The study’s findings underscore the efficacy of the ML models in generating dependable estimates of wind power fluctuations. Notably, the SVR model emerges as the frontrunner in performance across most pixels examined. Despite the inherent complexity of wind power dynamics, this research highlights that the SVR model can produce accurate wind power maps, even when operating with limited input data. The results emphasize the importance of considering influential factors in wind speed projections. This approach opens up promising avenues for improving the management of renewable energy resources.

Coal ash resources and potential for rare earth element production in the United States

The renewable energy industry is heavily reliant on rare earth elements, underscoring the need to develop resources and production. The objective of this work was to estimate coal ash resources and potential for extraction of rare earth elements using data for the US. Data on spatiotemporal variability in coal ash resources and disposition were compiled from various federal databases and rare earth elements levels in ash were compiled from the literature. Results show that ~ 52 gigatons (Gt) of coal were produced in the US (1950–2021). Power plants account for most of the coal use, particularly since 1980. Coal ash (5.3 Gt) represents a mean of 10% of coal by weight, ranging from 6% for subbituminous to 14% for lignite. About 70% of coal ash is potentially accessible for rare earth element extraction (1985–2021) and was disposed in landfills and ponds with the remaining coal ash used onsite or sold. Median values of total rare earth elements are much higher in ashes derived from the Appalachian Basin (median 431 mg/kg) than in the Illinois (282 mg/kg) or Powder River basins (264 mg/kg). Considering the market value of rare earth oxides, potentially accessible ash volumes, and percent rare earth element extraction (30% Appalachian and Illinois Basins; 70% Powder River Basin) results in an estimated $8.4 billion value. This study provides fundamental information on accessible coal ash resources in the US, linkages to coal sources, and preliminary estimates of rare earth element levels for future development within the US.

Life cycle assessment of ceramic tiles manufactured using industrial waste fly ash

Sustainability in the ceramic tile industry is critical due to its significant resource and energy consumption. With limited life cycle assessment (LCA) studies on waste materials in tile production, a research gap exists specifically for industrial waste fly ash (IWA). Building upon previous research that has confirmed the technical feasibility of IWA as a sustainable alternative material in ceramic tile, this study explores the environmental and economic feasibility of replacing potash feldspar with IWA in ceramic tiles. A comparative LCA across scenarios with varying IWA additions from 0 % to 30 % was conducted, focusing on six key environmental impact categories: climate change, terrestrial acidification, human toxicity, terrestrial ecotoxicity, freshwater eutrophication, and fossil depletion. Additionally, a sensitivity analysis on increased production energy and an environmental life cycle cost analysis (ELCC) were performed. Results reveal significant reductions in environmental impacts with increased IWA incorporation compared to the conventional construction. Notably, the IWA30 (30 % IWA addition) scenario, which entirely substitutes potash feldspar, achieves the most substantial benefits, reducing climate change impacts by 8 %, terrestrial acidification by 10 %, and terrestrial ecotoxicity by 22 %. These reductions demonstrate that incorporating IWA significantly decreases the overall environmental footprint of ceramic tile production by reducing the reliance on non-renewable resources and mitigating pollution. IWA30 also proves to be the most cost-effective option, with an 11 % cost reduction due to IWA's availability as a waste material. Overall, adopting IWA decreases the environmental burden and enhances economic viability, providing strong incentives for industries to adopt more sustainable practices by minimising waste management challenges and raw material consumption.

Delay sensitive and energy adaptive clustering hierarchy protocol using enhanced agglomerative hierarchy algorithm with time‐controlled jellyfish optimization

AbstractWireless sensor networks have sensing functions which made up of small sensor nodes that are processing and communication capabilities. However, the traditional approach of designating a single sensor node as the cluster head often leads to a faster depletion of its energy resources than another node. So, periodic reassignment of the cluster head role among different sensor nodes is crucial to extend operational lifetime and ensure sustained performance. Therefore, this research proposes an Enhanced Agglomerative Hierarchy Algorithm based on the Low Energy Adaptive Clustering Hierarchy (EAHALEACH) protocol, coupled with an enhanced time‐controlled optimization algorithm, to enhance energy efficiency by selecting the optimal cluster head from a candidate pool. The proposed method enhances energy efficiency by optimally selecting cluster heads, which reduces energy consumption and extends the lifespan of the network. Additionally, a lightweight energy‐aware cluster head rotation algorithm is introduced to efficiently rotate the cluster head role within the sensor node network, minimizing unnecessary data transmissions and extending the network lifetime. A hybrid approach combining Carrier Sense and Time Division Multiple Access (CSTDMA) optimizes packet forwarding by dynamically allocating time slots, reducing collisions and contention to improve packet forwarding efficiency. Comparative analysis with existing techniques demonstrates that the hybrid clustering‐based LEACH protocol achieves superior performance in terms of throughput 4600 bps by 2000 rounds, energy consumption 50 J, latency as 1 ms and network lifetime in 1000th node attains 3500 s. These advancements contribute to prolonged operational efficiency and sustained performance in wireless sensor network deployments.

Time Series Analysis to Estimate the Volume of Drinking Water Consumption in the City of Meoqui, Chihuahua, Mexico

Water is a vital resource for sustaining life and for numerous processes within the transformation industry. It is a finite resource, albeit one that can be renewed, and thus sustainable management is imperative. To achieve this objective, it is necessary to have the appropriate tools to assist with the planning policies for its management. This paper presents a time series analysis approach to measure and predict the pattern of water consumption by humans throughout subsectors (domestic, commercial, public sector, education, industry, and raw water) and total water consumption in Meoqui, Chihuahua, Mexico with data from 2011 to 2023, applying calibration model techniques to measure uncertainty in the forecasting. The municipality of Meoqui encompasses an area of 342 km2. The climate is semi-arid, with an average annual rainfall of 272 mm and average temperatures of 26.4 °C in summer and 9.7 °C in winter. The municipal seat, which has a population of 23,140, is supplied with water from ten wells, with an average consumption of 20 ± 579 m3 per user. The consumption of the general population indicates the existence of a seasonal autoregressive integrated moving average (SARIMA) (0,1,2)(0,0,2)12 model. (Sen’s Slope = 682.7, p < 0.001). The domestic sector exhibited the highest overall consumption, with a total volume of 17,169,009 m3 (13 ± 93). A SARIMA (2,1,0)(2,0,0)12 model was estimated, with a Sen’s slope of 221.65 and a p-value of less than 0.001. The second-largest consumer of total water was the “raw water” sector, which consumed 5,124,795 (30,146 ± 35,841) m3 and exhibited an SARIMA (0,1,1)(2,0,0)12 model with no statistically significant trend. The resulting models will facilitate the company’s ability to define water resource management strategies in a sustainable manner, in alignment with projected consumption trends.

Mimicking nature to design eco-industrial parks: Exploring the influence of connectance on industrial network optimization

The accelerating exhaustion of non-renewable natural resources and the urgent need for sustainable practices have prompted the exploration of alternative methodologies in production processes. Food webs illustrate the predator-prey relationships between species in natural ecosystems, and their properties can offer valuable insights for improving economic and industrial systems, potentially leading to reduced emissions, costs, and improved process efficiency. While some food web metrics have been used for various purposes like establishing industry-nature analogies, comparing industrial networks to natural ecosystems, and configuring industrial networks, investigation of the role of the connectance metric in designing industrial networks, particularly in optimizing theoretical EIPs, is still scarce. This study investigates the role of connectance in optimizing industrial networks within eco-industrial parks, specifically focusing on the construction sector. A scenario analysis for seven conceptual eco-industrial parks serves as an illustration of how this approach can be used. The food web metric values of these eco-industrial parks are compared among themselves and against biological averages. The results reveal that maximizing connectance in eco-industrial parks is not an effective strategy for network optimization, as indicated by previous literature which points to potential instability. Instead, configurations that closely resemble natural food web metrics may provide better sustainability and efficiency if the limitations of the study are addressed, and the validity of this assumption is confirmed through quantitative tests. This study contributes theoretically by developing a guide for designing eco-industrial parks and introduces two key methodologies: based on particular criteria, a method for identifying and selecting potential future industrial symbiosis implementations targeted a sector and an innovative approach for sector-specific park design based on natural objectives and constraints, serving as a valuable decision-making tool for practitioners and policymakers.

Design and Technological Aspects of Integrating Multi-Blade Machining and Surface Hardening on a Single Machine Base

Modern mechanical engineering faces high competition in global markets, which requires manufacturers of process equipment to significantly reduce production costs while ensuring high product quality and maximum productivity. Metalworking occupies a significant part of industrial production and consumes a significant share of the world’s energy and natural resources. Improving the technology of manufacturing parts with an emphasis on more efficient use of metalworking machines is necessary to maintain the competitiveness of the domestic machine tool industry. Hybrid metalworking systems based on the principles of multi-purpose integration eliminate the disadvantages of monotechnologies and increase efficiency by reducing time losses and intermediate operations. The purpose of this work is to develop and implement a hybrid machine tool system and an appropriate combined technology for manufacturing machine parts. Theory and methods. Studies of the possible structural composition and layout of hybrid equipment at integration of mechanical and surface-thermal processes were carried out, taking into account the basic provisions of structural synthesis and componentization of metalworking systems. Theoretical studies were carried out using the basic provisions of system analysis, geometric theory of surface formation, design of metalworking machines, methods of finite elements, and mathematical and computer modeling. The mathematical modeling of thermal fields and structural-phase transformations during HEH HFC was carried out in ANSYS (version 19.1) and SYSWELD (version 2010) software packages using numerical methods of solving differential equations of unsteady heat conduction (Fourier equation), carbon diffusion (2nd Fick’s law) and elastic–plastic behavior of the material. The verification of the modeling results was carried out using in situ experiments employing the following: optical and scanning microscopy; and mechanical and X-ray methods of residual stress determination. Formtracer SV-C4500 profilograph profilometer was used in the study for simultaneous measurement of shape deviations and surface roughness. Surface topography was assessed using a Walter UHL VMM 150 V instrumental microscope. The microhardness of the hardened surface layer of the parts was evaluated on a Wolpert Group 402MVD. Results and discussion. The original methodology of structural and kinematic analysis for pre-design studies of hybrid metalworking equipment is presented. Methodological recommendations for the modernization of multi-purpose metal-cutting machine tool are developed, the implementation of which will make it possible to implement high-energy heating with high-frequency currents (HEH HFC) on a standard machine tool system and provide the formation of knowledge-intensive technological equipment with extended functionality. The innovative moment of this work is the development of hybrid metalworking equipment with numerical control and writing a unique postprocessor to it, which allows to realize all functional possibilities of this machine system and the technology of combined processing as a whole. Special tooling and tools providing all the necessary requirements for the process of surface hardening of HEH HFC were designed and manufactured. The conducted complex of works and approbation of the technology of integrated processing in real conditions in comparison with traditional methods of construction of technological process of parts manufacturing allowed to obtain the following results: increase in the productivity of processing by 1.9 times; exclusion of possibility of scrap occurrence at finishing grinding; reduction in auxiliary and preparatory-tasking time; and reduction in inter-operational parts backlogs.

From Bottom-Up Towards a Completely Decentralized Autonomous Electric Grid Based on the Concept of a Decentralized Autonomous Substation

The idea of a decentralized electric grid has shifted from being a concept to a reality. The growing integration of distributed energy resources (DERs) has transformed the traditional centralized electric grid into a decentralized one. However, while most efforts to manage and optimize this decentralization focus on the electrical infrastructure layer, the operational and control layer, as well as the data management layer, have received less attention. Current electric grids rely on centralized control centers (CCCs) that serve as the electric grid’s brain, where operators monitor, control, and manage the entire grid infrastructure. Hence, any disruption caused by a cyberattack or a natural event, disconnecting the CCC, could have numerous negative effects on grid operations, including socioeconomic impacts, equipment damage, market repercussions, and blackouts. This article introduces the idea of a fully decentralized electric grid that leverages autonomous smart substations and blockchain integration for decentralized data management and control. The aim is to propose a blockchain-enabled decentralized electric grid model and its potential impact on energy markets, sustainability, and resilience. The model presented underlines the transformative potential of decentralized autonomous grids in revolutionizing energy systems for better operability, management, and flexibility.

Grid-integrated solutions for sustainable EV charging: a comparative study of renewable energy and battery storage systems

IntroductionThe integration of electric vehicles (EVs) into the power network challenges the 1) grid capacity, 2) stability, and 3) management. This is due to the 1) increased peak demand, 2) infrastructure strain, and 3) intermittent charging patterns. Previous studies lack comprehensive integration of renewable energy and battery storage with EV charging.MethodsTo address these challenges, this study explores the effectiveness of incorporating renewable energy resources (RERs) and battery energy storage systems (BESS) alongside the traditional grid. The proposed study utilizes the HOMER Grid® and conducted a comprehensive analysis.ResultsThe proposed study compares two grid integrated scenarios: 1) Case-1 (grid and photovoltaic (PV) systems), and 2) Case-2 (grid, PV systems, and BESS). Both these scenarios are compared against a Base case relying solely on grid power. The evaluation employed techno-economic analysis while focusing on 1) net present cost (NPC), 2) cost of energy, and 3) annualized savings. Additionally, the proposed study analyzed 4) seasonal variations in EV charging demand, 5) grid interactions, 6) PV production, and 7) the operation of BESS in both summer and winter. The comparative analysis reveals that the Base case incurs a net present cost (NPC) of $546,977 and a cost of energy (COE) of $0.354 per kWh. In contrast, Case-1, which integrates a 100 kW PV system, shows a significantly lower NPC of -$122,962 and a reduced COE of -$0.043 per kWh, with annualized savings of $61,492. Case-2, incorporating both the 100 kW PV system and a BESS with a capacity of 9.8 kWh, has a higher NPC of $309,667 but a COE of $0.112 per kWh and provides annual savings of $51,233 compared to the Base case.DiscussionSeasonal analysis highlights that Case-2 achieves the lowest carbon emissions in summer, ranging from 2.0 to 2.5 tons, while Case-1 shows the lowest emissions in winter, ranging from 3.2 to 3.4 tons. This model 1) reduces operational costs, 2) minimizes carbon emissions, while 3) making it compelling for future energy systems in increasing EV adoption.

Achieving Higher Efficiency on N2 Reduction Reaction through Mo‐ and Bi‐Based Active Sites for Sustainable Photoelectrochemical Ammonia Production

Hydrogen energy from water splitting is considered the highly anticipated modern energy resource; however, storage and transportation require complex and high‐cost facilities, which argue about the efficiency of hydrogen fuel compared to conventional fuels. Thereby, ammonia (NH3), which is a liquid at ambient conditions, promises a lower cost of storage and transportation, but the production of ammonia imposes difficulties with selectivity and efficiency over several products and, notably, hydrogen evolution reaction. Among several methods combining the advantages of electrochemical and photocatalytic properties, the photoelectrochemical (PEC) method is destined to improve the efficiency of ammonia production from N2 reduction reaction (NRR). Because of the multistep NRR process, enormous negative potentials, and poor reaction kinetics, the activity and selectivity of NRR are severely compromised. Therefore, Mo‐ and Bi‐based catalysts are rationally developed to promote the activity and selectivity of NRR processes. Combining the benefits of Mo‐ and Bi‐based catalysts is anticipated to result in highly effective PEC NRR activity. This review is predicted to emphasize the role and characteristics of PEC NRR and the value of Mo and Bi catalysts in raising ammonia's activity and selectivity.

The impact of renewable and non-renewable energy consumption on aggregate output in Pakistan: robust evidence from the RALS cointegration test.

Over the past three decades, Pakistan's energy consumption has surged due to industrialization, population growth, and development activities. To meet the escalating energy demands, the country has primarily relied on thermal power projects, which are financially burdensome and environmentally detrimental, compared to hydropower projects. This reliance exposes Pakistan to global oil price shocks and environmental degradation. To address this dilemma, this empirical research investigates the impact of both non-energy factors (labour and capital) and energy-specific factors (renewable and non-renewable) on Pakistan's aggregate output, using annual time-series data from 1980 to 2021. The analysis employs the newly established Residual Augmented Least Square (RALS) cointegration test and the Autoregressive Distributed Lag (ARDL) methodology to estimate the long-term cointegrating relationship among the examined variables. The empirical findings demonstrate that both non-energy and energy-specific factors positively and significantly influence Pakistan's long-term aggregate output. However, petroleum consumption exerts a positive but insignificant influence on Pakistan's long-term aggregate output. The study recommends diversifying the energy supply mix to include more hydroelectricity, non-hydroelectric renewables (mainly solar and wind), and natural gas. Specifically, transitioning from imported, expensive, and more greenhouse gas (GHG)-generating petroleum products to domestically produced natural gas could potentially reduce Pakistan's trade deficit and its vulnerability to global oil price shocks. Besides the economic benefits, shifting from non-renewable energy sources (specifically oil) to renewable energy would enhance Pakistan's image and increase its geopolitical influence over neighboring countries. Additionally, the study emphasizes the need to encourage private sector participation in renewable energy projects and suggests implementing effective carbon tax policies to mitigate CO2 emissions and foster economic growth.

Analysis of the Possibilities of Energy Supply to Consumers in Cold Conditions During Large-Scale Emergency Installations in the Gas Industry

The article presents the main components of the methodological approach to the analysis of the possibilities of supplying final types of energy to consumers in the event of a loss of performance of critical facilities of the Russian gas industry in conditions of cooling in the territories of the federal districts. The principle of choosing a territorial section for analyzing the situation with a simultaneous increase in demand for fuel and energy resources is described. An algorithm for conducting research is given. Research is carried out by modeling the work of the country’s fuel and energy complex during the period of the average day of January in the conditions of a peak-increasing demand for thermal energy in the territories of federal districts. At the same time, the cooling is modeled in turn for each of the federal districts in the zone of operation of the Unified Gas Supply System of Russia. An analysis of the possibilities of meeting the demand for final types of energy in the constituent entities of the Russian Federation is carried out for all key scenarios of cooling and loss of efficiency of critical gas industry facilities. The principles of modeling the situation with the supply of final types of energy to consumers in these situations are shown. The most vulnerable regions under the analyzed conditions are identified. The conclusion is made about the need for a balanced approach to determining the optimal degree of dominance of natural gas in the fuel and energy balance of the regions, taking into account the existing opportunities for its supply in the conditions of large-scale emergencies in the gas industry.

Public control of coal resources of the United States’ Powder River Basin for a managed decarbonization transition

Abstract The United States (US) has set aggressive targets for reaching a carbon pollution-free power sector by 2035 and a net-zero economy by 2050. Reaching these goals will require both rapid expansion of zero- and negative-carbon infrastructure and a phase-out of unabated fossil fuel infrastructure. New subsidy and regulatory actions focus on eliminating coal emissions at the point of consumption either through carbon capture and storage (CCS) or coal-fired power plant retirement. Yet, these pathways have opposite implications for coal production: CCS is coal intensive, while coal retirement is not. Despite a record of chaotic and harmful transition and significant social scientific research suggesting better outcomes from managed, coordinated decline, these mechanisms rely on uncoordinated private decision making by mine and plant owners. Coal mining has rapidly declined since peak production in 2008. Production has dropped by half; bankruptcies are the norm; and coal mine and power plant host communities have experienced highly disruptive decline as a result of this unmanaged transition. Given this history, we argue the current market-based, plant-driven governance approach could worsen transition challenges, including potentially stranding costly CCS investments. We argue that the US should complement its extensive investments in technology demonstrations with innovative governance demonstrations to facilitate a just energy transition. Specifically, we argue that the Powder River Basin, which is the US’ largest coal basin and consists primarily of federally leased coal, should be brought under public control for managed decline both to meet emissions reduction targets and advance a just energy transition.

Enhanced strategies for depressurization in offshore natural gas hydrate exploitation: An in-depth investigation into pathway optimization and production stability mechanisms

Natural gas hydrates have garnered widespread attention as a high-quality energy resource. Recent offshore extraction experiences suggest that depressurization is a technically mature and economically viable option. However, challenges such as reservoir temperature reduction, reservoir subsidence, secondary hydrate formation, and insufficient dynamics in later-stage hydrate decomposition still require improvements to the depressurization method. This study, based on field data from Japan's first offshore natural gas hydrate extraction, utilizes a self-developed numerical simulator to model and validate reservoirs at the field scale. Long-term production rate stability, total production, secondary hydrate formation, reservoir subsidence, evolution of permeability, and temperature-pressure paths were analyzed and optimized for the three mainstream depressurization modes: steady depressurization, stepwise depressurization, and cyclic depressurization. The results indicate that, under the condition of equal total work done throughout the entire depressurization process, steady depressurization with an effectively lower depressurization rate is the optimal choice. Cyclic depressurization, due to the formation of secondary hydrates reducing the permeability of certain reservoir zones, adversely affects gas production efficiency during the long-term stable production phase. This study enhances insights into the coupled evolution of multiple physical fields during the depressurization of offshore natural gas hydrates, providing valuable guidance for future on-site extraction plan designs.

Ultra-High-Voltage Construction Projects and Total Factor Energy Efficiency: Empirical Evidence on Cross-Regional Power Dispatch in China

Optimizing cross-regional energy dispatch is crucial for addressing regional energy resource imbalances and significantly enhancing energy utilization efficiency. This study aims to analyze the potential impact of China’s ultra-high-voltage (UHV) construction on firms’ total factor energy efficiency and provide empirical evidence supporting the role of cross-regional energy dispatch in improving firms’ energy efficiency. The construction of UHV infrastructure has become a vital part of China’s “New Infrastructure” projects, presenting a “Chinese solution” to the global challenge of regional energy resource mismatches. This study employs an enhanced two-step stochastic frontier method to quantify firms’ total factor energy efficiency and utilizes a difference-in-differences model to evaluate the impact of inter-regional electricity dispatch on this efficiency. The empirical analysis results indicate that UHV construction projects increase the total factor energy efficiency of regional firms by an average of 0.45%, which significantly contributes to firms’ total factor productivity. This conclusion remains valid after a series of robustness tests. Furthermore, the heterogeneity analysis results indicate that the UHV construction project increases the total factor energy efficiency of non-energy-intensive industries by 0.49%, and significantly enhances the total factor energy efficiency of the manufacturing industry by 0.94%. However, it has no significant effect on energy-intensive industries or non-manufacturing enterprises. Additionally, the mechanism analysis shows that UHV construction projects affect total factor energy efficiency through three pathways: industrial structure adjustment, urban innovation, and clean energy transition. This study offers insights for addressing regional energy spatial mismatches and provides policy recommendations for developing a new energy system aligned with regional needs.