Search Results (870)

To reveal the influence mechanisms of seasonal climatic factors (wind speed, wind direction, temperature) and leakage direction on hydrogen dispersion and explosion behavior from single-source leaks at typical risk locations (hydrogen storage tanks, compressors, dispensers) in hydrogen refueling stations (HRSs), this work established a full-scale 1:1 three-dimensional numerical model using the FLACS v22.2 software based on the actual layout of an HRS in Xichang, Sichuan Province. Through systematic simulations of 72 leakage scenarios (3 equipment types × 4 seasons × 6 leakage directions), the coupled effects of climatic conditions, equipment layout, and leakage direction on hydrogen dispersion patterns and explosion risks were quantitatively analyzed. The key findings indicate the following: (1) Downward leaks (−Z direction) from storage tanks tend to form large-area ground-hugging hydrogen clouds, representing the highest explosion risk (overpressure peak: 0.25 barg; flame temperature: >2500 K). Leakage from compressors (±X/−Z directions) readily affects adjacent equipment. Dispenser leaks pose relatively lower risks, but specific directions (−Y direction) coupled with wind fields may drive significant hydrogen dispersion toward station buildings. (2) Southeast/south winds during spring/summer promote outward migration of hydrogen clouds, reducing overall station risk but causing localized accumulation near storage tanks. Conversely, north/northwest winds in autumn/winter intensify hydrogen concentrations in compressor and station building areas. (3) An empirical formula integrating climatic parameters, leakage conditions, and spatial coordinates was proposed to predict hydrogen concentration (error < 20%). This model provides theoretical and data support for optimizing sensor placement, dynamically adjusting ventilation strategies, and enhancing safety design in HRSs. Full article

The Sichuan Basin is a natural-gas-exploiting area with intensive agriculture activities. However, the spatial and temporal distribution of atmospheric methane concentration and the relationships with intensive agriculture and natural gas extraction activities are not well investigated. In this study, a long-term (2003–2021) dataset of column-averaged dry-air mole fraction of methane (XCH₄) over the Sichuan Basin and adjacent regions was built by integrating multi-satellite remote sensing data (SCIAMACHY, GOSAT, Sentinel-5P), which was calibrated using ground station data. The results show a strong correlation and consistency (R = 0.88) between the ground station and satellite observations. The atmospheric CH₄ concentration of the Sichuan Basin showed an overall higher level (around 20 ppb) than that of the whole of China and an increasing trend in the rates, from around 2.27 ppb to 10.44 ppb per year between 2003 and 2021. The atmospheric CH₄ concentration of the Sichuan Basin also exhibits clear seasonal changes (higher in the summer and autumn and lower in the winter and spring) with a clustered geographical distribution. Agricultural activities and natural gas extraction contribute significantly to atmospheric methane concentrations in the study area, which should be considered in carbon emission management. This study provides an effective way to investigate the spatiotemporal distribution of atmospheric CH₄ concentration and related factors at a regional scale with natural and human influences using multi-source satellite remote sensing data. Full article

With the popularization of electric vehicles and the continuous expansion of the electric vehicle market, the construction and management of charging facilities for electric vehicles have become important issues in research and practice. In some remote areas, the charging stations are idle due to low traffic flow, resulting in a waste of resources. Areas with high traffic flow may have fewer charging stations, resulting in long queues and road congestion. The purpose of this study is to optimize the location of charging stations and the number of charging piles in the stations based on the distribution of traffic flow, and to construct a bi-level programming model by analyzing the distribution of traffic flow. The upper-level planning model is the user-balanced flow allocation model, which is solved to obtain the optimal traffic flow allocation of the road network, and the output of the upper-level planning model is used as the input of the lower-layer model. The lower-level planning model is a generalized minimum cost model with driving time, charging waiting time, charging time, and the cost of electricity consumed to reach the destination of the trip as objective functions. In this study, an empirical simulation is conducted on the road network of Hefei City, Anhui Province, utilizing three algorithms—GA, GWO, and PSO—for optimization and sensitivity analysis. The optimized results are compared with the existing charging station deployment scheme in the road network to demonstrate the effectiveness of the proposed methodology. Full article

The transition to green energy in the transport sector is becoming a priority in the context of global climate challenges and the European Green Deal. This paper investigates the development of alternative fuelling stations, particularly electric vehicle (EV) charging infrastructure and hydrogen stations, across EU countries with a focus on Poland. It combines a policy and technology overview with a quantitative scientific analysis, offering a multidimensional perspective on green infrastructure deployment. A Pearson correlation analysis reveals significant links between charging station density and both GDP per capita and the share of renewable energy. The study introduces an original Infrastructure Accessibility Index (IAI) to compare infrastructure availability across EU member states and models Poland’s EV charging station demand up to 2030 under multiple growth scenarios. Furthermore, the article provides a comprehensive overview of biofuels, including first-, second-, and third-generation technologies, and highlights recent advances in hydrogen and renewable electricity integration. Emphasis is placed on life cycle considerations, energy source sustainability, and economic implications. The findings support policy development toward zero-emission mobility and the decarbonisation of transport systems, offering recommendations for infrastructure expansion and energy diversification strategies. Full article

This study presents a comprehensive case of green remodeling applied to a local fire station in Seoul, South Korea. The project aimed to improve energy performance through an integrated upgrade of passive systems (exterior insulation, high-performance windows, and airtightness) and active systems (electric heat pumps, energy recovery ventilation, and rooftop photovoltaic systems), while maintaining uninterrupted emergency operations. A detailed analysis of annual energy use before and after the remodeling shows a 44% reduction in total energy consumption, significantly exceeding the initial reduction target of 20%. While electricity use increased modestly during winter due to the electrification of heating systems, gas consumption dropped sharply by 63%, indicating a shift in energy source and improved efficiency. The building’s airtightness also improved significantly, with a reduction in the air change rate. The project further addressed unique challenges associated with continuously operated public facilities, such as insulating the fire apparatus garage and executing phased construction to avoid operational disruption. This study contributes valuable insights into green remodeling strategies for mission-critical public buildings, emphasizing the importance of integrating technical upgrades with operational constraints to achieve verified energy performance improvements. Full article

In recent years, carbon dioxide (CO₂) emissions have increased at the fastest rates ever recorded. This is a trend that contradicts global efforts to stabilise greenhouse gas (GHG) concentrations and prevent long-term climate change. Over 90% of global transport relies on oil-based fuels. The continued use of diesel and petrol raises concerns related to oil costs, supply security, GHG emissions, and the release of air pollutants and volatile organic compounds. This study explored electric vehicle (EV) charging networks by assessing environmental impacts through GHG and petroleum savings, developing dynamic pricing strategies, and forecasting infrastructure needs. A substantial dataset of over 259,000 EV charging records from Palo Alto, California, was statistically analysed. Machine learning models were applied to generate insights that support sustainable and economically viable electric transport planning for policymakers, urban planners, and other stakeholders. Findings indicate that GHG and gasoline savings are directly proportional to energy consumed, with conversion rates of 0.42 kg CO₂ and 0.125 gallons per kilowatt-hour (kWh), respectively. Additionally, dynamic pricing strategies such as a 20% discount on underutilised days and a 15% surcharge during peak hours are proposed to optimise charging behaviour and improve station efficiency. Full article

The Jidong Oilfield No. 2 Underground Gas Storage (UGS), located in an active fault zone in Northern China, is a key facility for ensuring natural gas supply and peak regulation in the Beijing–Tianjin–Hebei region. To evaluate the effectiveness of a combined surface and shallow borehole monitoring system under deep reservoir conditions, a 90-day microseismic monitoring trial was conducted over a full injection cycle using 16 surface stations and 1 shallow borehole station. A total of 35 low-magnitude microseismic events were identified and located using beamforming techniques. Results show that event frequency correlates positively with wellhead pressure variations instead of the injection volume, suggesting that stress perturbations predominantly control microseismic triggering. Events were mainly concentrated near the bottom of injection wells, with an average location error of approximately 87.5 m and generally shallow focal depths, revealing limitations in vertical resolution. To enhance long-term monitoring performance, this study recommends deploying geophones closer to the reservoir, constructing a 3D velocity model, applying AI-based phase picking, expanding array coverage, and developing a microseismic-injection coupling early warning system. These findings provide technical guidance for the design and deployment of long-term monitoring systems for deep reservoir conversions into UGS facilities. Full article

Driven by the environmental benefits associated with reduced greenhouse gas emissions, oil companies have intensified research efforts into reassessing the strategies used to meet the electrical demands of offshore production platforms. Among the various alternatives available, the deployment of onshore–offshore interconnections via High-Voltage Direct Current (HVDC) transmission systems has emerged as a promising solution, offering both economic and operational advantages. In addition to reliably meeting the electrical demand of offshore facilities, this approach enables enhanced operational flexibility due to the advanced control and regulation capabilities inherent to HVDC converter stations. Based on the use of interconnection through an HVDC link, aiming to evaluate the operation of the electrical system as a whole, this study focuses on evaluating dynamic events using the PSCAD software version 5.0.2 to analyze the direct online starting of a large induction motor and the sudden loss of a local synchronous generating unit. The simulation results are then analyzed to assess the effectiveness of both Grid-Following (GFL) and Grid-Forming (GFM) control strategies for the converters, while the synchronous generators are evaluated under both voltage regulation and constant power factor control operation, with a particular focus on system stability and restoration of normal operating conditions in the sequence of events. Full article

Uncoordinated electric vehicle (EV) charging can significantly complicate power system operations. In this paper, we develop a hybrid EV charging method that seamlessly integrates centralized EV charging and distributed control schemes to address EV energy demand challenges. The proposed method includes (1) a centralized day-ahead optimal scheduling mechanism and EV shifting process based on mixed-integer linear programming (MILP) and (2) a distributed control strategy based on a genetic algorithm (GA) that dynamically adjusts the charging rate in real-time grid scenarios. The MILP minimizes energy imbalance at overloaded slots by reallocating EVs based on supply–demand mismatch. By combining full and minimum charging strategies with MILP-based shifting, the method significantly reduces network stress due to EV charging. The centralized model schedules time slots using valley-filling and EV-specific constraints, and the local GA-based distributed control adjusts charging currents based on minimum energy, system availability, waiting time, and a priority index (PI). This PI enables user prioritization in both the EV shifting process and power allocation decisions. The method is validated using demand data on a radial feeder with residential and commercial load profiles. Simulation results demonstrate that the proposed hybrid EV charging framework significantly improves grid-level efficiency and user satisfaction. Compared to the baseline without EV integration, the average-to-peak demand ratio is improved from 61% to 74% at Station-A, from 64% to 80% at Station-B, and from 51% to 63% at Station-C, highlighting enhanced load balancing. The framework also ensures that all EVs receive energy above their minimum needs, achieving user satisfaction scores of 88.0% at Stations A and B and 81.6% at Station C. This study underscores the potential of hybrid charging schemes in optimizing energy utilization while maintaining system reliability and user convenience. Full article

The natural gas pipeline network transmission system involved in the coordinated operation of pipeline networks and gas-fired power generation facilities is complex. It consists of multiple components, such as gas sources, users, valves, compressor stations, and pipelines. The addition of natural gas-fired power generation facilities overlaps with the high and low peak periods of civil gas, imposing dual peak-shaving pressures on pipeline networks and requiring more stringent operational control strategies for maintaining system stability. To address the aforementioned issues and improve the overall operating revenues of the system, we proposed the coordinated optimization model of gas-fired power generation facilities, pipeline networks, gas storage, and compressor stations. The optimization algorithm is written using the penalty function method of the Interior Point OPTimizer (IPOPT) solver. Meanwhile, the basic parameters of the system’s pipeline networks, users, gas storage, natural gas-fired power generation facilities, compressors, and electricity prices were input into the solver. The research results reveal that the algorithm ensures solution accuracy while accounting for computational efficiency and practical applicability. The algorithm can be used to effectively calculate the ideal coordinated operation solution, significantly improve the operating revenues of the system, and achieve safe, stable, coordinated, and efficient operation of the system. Full article

The National Institute of Earth Physics (NIEP) in Romania has upgraded its seismic monitoring stations into multifunctional platforms equipped with advanced devices for measuring gas emissions, magnetic fields, telluric fields, solar radiation, and more. This enhancement enabled the integration of a seismic forecasting system designed to extend the alert time of the existing warning system, which previously relied solely on seismic data. The implementation of an Operational Earthquake Forecast (OEF) aims to expand NIEP’s existing Rapid Earthquake Early Warning System (REWS) which currently provides a warning time of 25–30 s before an earthquake originating in the Vrancea region reaches Bucharest. The AFROS project (PCE119/4.01.2021) introduced fundamental research essential to the development of the OEF system. As a result, real-time analyses of radon and CO₂ emissions are now publicly available at afros.infp.ro, dategeofizice. The primary monitored area is Vrancea, known for producing the most destructive earthquakes in Romania, with impacts extending to neighboring countries such as Bulgaria, Ukraine, and Moldova. The structure and methodology of the monitoring network are adaptable to other seismic regions, depending on their specific characteristics. All collected data are stored in an open-access database available in real time, geobs.infp.ro. The monitoring methods include threshold-based event detection and seismic data analysis. Each method involves specific technical nuances that distinguish this monitoring network as a novel approach in the field. In conclusion, experimental results indicate that the Gutenberg-Richter law, combined with gas emission measurements (radon and CO₂), can be used for real-time earthquake forecasting. This approach provides warning times ranging from several hours to a few days, with results made publicly accessible. Another key finding from several years of real-time monitoring is that the value of fundamental research lies in its practical application through cost-effective and easily implementable solutions—including equipment, maintenance, monitoring, and data analysis software. Full article

There are significant emissions of greenhouse gases into the atmosphere from the transportation industry. As a result, the idea that electric vehicles (EVs) offer a revolutionary way to reduce greenhouse gas emissions and our reliance on rapidly depleting petroleum supplies has been put forward. EVs are becoming more common in many nations worldwide, and the rapid uptake of this technology is heavily reliant on the growth of charging stations. This is leading to a significant increase in their number on the road. This rise has created an opportunity for EVs to be integrated with the power system as a Demand Response (DR) resource in the form of an EV fast charging station (EVFCS). To allocate electric vehicle fast charging stations as a dynamic load for frequency control and on specific buses, this study included the optimal location for the EVFCS and the best controller selection to obtain the best outcomes as DR for various network disruptions. The optimal location for the EVFCS is determined by applying transient voltage drop and frequency nadir parameters to the Particle Swarm Optimization (PSO) location model as the first stage of this study. The second stage is to explore the optimal regulation of the dynamic EVFCS load using the PSO approach for the PID controller. PID controller settings are acquired to efficiently support power system stability in the event of disruptions. The suggested model addresses various types of system disturbances—generation reduction, load reduction, and line faults—when it comes to the Kundur Power System and the IEEE 39 bus system. The results show that Bus 1 then Bus 4 of the Kundur System and Bus 39 then Bus 1 in the IEEE 39 bus system are the best locations for dynamic EVFCS. Full article

Extensive wildfires and logging have affected the Russian boreal forests in recent decades. Scots pine (Pinus sylvestris L.) forests are widespread in Russia and are one of the most disturbed tree species in Siberia. However, the effects of disturbance on soil CO₂ efflux in the vast Siberian forests are still poorly understood. We used the LI 8100A infrared gas analyzer to study changes in soil CO₂ efflux into the atmosphere in mature Scots pine forests in the Siberian central taiga five–six years following fires and logging. Measurements of soil CO₂ efflux rates were performed on sites where automatic weather stations have been continuously operational since 2022, which gives us temporal patterns of meteorological fluctuations across forests with different disturbance histories. We found significant differences in soil efflux rates depending on the site and disturbance characteristics. In the undisturbed dry lichen-dominated forest, CO₂ efflux was 4.8 ± 2.1 µmol m⁻² s⁻¹, while in the wet moss-dominated forest it was 2.3 ± 1.3 µmol m⁻² s⁻¹, with soil efflux in Sphagnum sp. being twofold of that in feather moss. Both fire and logging significantly reduced CO₂ efflux, with a smaller reduction in soil CO₂ efflux observed in the moss-dominated plots (5%–40%) compared to the lichen-dominated plots (36%–55%). The soil efflux rate increased exponentially with increasing topsoil temperatures in lichen-dominated Scots pine sites, with disturbed plots showing less dependence compared to undisturbed forest. In the wet moss-dominated Scots pine forest, we found no significant dependence of soil efflux on temperature for all disturbance types. We also found a positive moderate relationship between soil efflux and forest floor depth in both lichen- and moss-dominated Scots pine forests across all the plots studied. Our findings advance the understanding of the effects of fire and logging on the carbon cycle and highlight the importance of accounting for disturbance factors in Earth system models due to changing climate and anthropogenic patterns. Full article

In gas transmission stations, flame arrestors are typically installed in pipelines and venting systems to prevent the flames resulting from accidental ignition or deflagration of combustible gases during transmission from propagating through the pipelines. During actual operation, the presence of solid particulates in the gas compromises the flame-arresting efficacy and increases the failure rate of current pipeline flame arrestors. This study employs an integrated approach combining theoretical analysis and numerical simulation to establish a numerical model for flame arrestors that accounts for solid particle deposition effects. The model reveals the distribution characteristics of velocity fields, pressure fields, gas phase volumetric concentration fields, and solid deposition rate fields within pipeline flame arrestors. It systematically investigates the influence mechanisms of porosity, flame arrestor core thickness, inlet flame velocity, arrestor length, particle size, particle concentration on pressure drop, flame arrestment velocity, and deposition rate. These findings provide theoretical support for optimizing flame arrestor structural design and reducing operational failure rates. Full article

In Japan, natural disasters occur frequently. Serious disasters may cause damage to traffic networks and telecommunication infrastructures, leading to the occurrence of isolated disaster areas. In this article, unmanned aerial vehicles (UAVs) are used for data collection instead of unavailable ground-based stations in isolated disaster areas. Detailed information about the damage situation will be collected from the user equipment (UE) by a UAV through a fly–hover–fly procedure, and then will be sent to the disaster response headquarters for disaster relief. However, mission completion time minimization becomes a crucial task, considering the requirement of rapid response and the battery constraint of UAVs. Therefore, the author proposed a three-dimensional UAV flight trajectory, discussing the optimal flight altitude and placement of hovering points by transforming the original problem of K-means clustering into a location set cover problem (LSCP) that can be solved via a genetic algorithm (GA) approach. The simulation results have shown the feasibility of the proposed method to reduce the mission completion time. Full article