Search Results (256)

In 2022, the Russia–Ukraine conflict has severely impacted the EU’s energy supply chain, and the EU’s natural gas import pattern has begun to reconstruct, and exploring the spatiotemporal differentiation of EU natural gas trade and its driving factors is the basis for improving the resilience of its supply chain and ensuring the stable supply of energy resources. This paper summarizes the law of the change of its import volume by using the complex network method, constructs a multi-dimensional index system such as demand, economy, and security, and uses the geographic detector model to mine the driving factors affecting the spatiotemporal evolution of natural gas imports in EU countries and propose different sustainable development paths. The results show that from 2000 to 2023, Europe’s natural gas imports generally show an upward trend, and the import structure has undergone great changes, from pipeline gas dominance to LNG diversification. After the conflict between Russia and Ukraine, the number of import source countries has increased, the market network has become looser, France has become the core hub of the EU natural gas market, the importance of Russia has declined rapidly, and the status of countries in the United States, North Africa, and the Middle East has increased rapidly; natural gas consumption is the leading factor in the spatiotemporal differentiation of EU natural gas imports, and the influence of import distance and geopolitical risk is gradually expanding, and the proportion of energy consumption is significantly higher than that of other factors in the interaction with other factors. Combined with the driving factors, three different evolutionary directions of natural gas imports in EU countries are identified, and energy security paths such as improving supply chain control capabilities, ensuring export stability, and using location advantages to become hub nodes are proposed for different development trends. Full article

The growing demand for low-emission maritime transport and efficient onboard energy management has intensified research into advanced control strategies for hybrid shipboard microgrids. These systems integrate both AC and DC power domains, incorporating renewable energy sources and battery storage to enhance fuel efficiency, reduce greenhouse gas emissions, and support operational flexibility. However, integrating renewable energy into shipboard microgrids introduces challenges, such as power fluctuations, varying line impedances, and disturbances caused by AC/DC load transitions, harmonics, and mismatches in demand and supply. These issues impact system stability and the seamless coordination of multiple distributed generators. To address these challenges, we proposed a hierarchical control strategy that supports sustainable operation by improving the voltage and frequency regulation under dynamic conditions, as demonstrated through both MATLAB/Simulink simulations and real-time hardware validation. Simulation results show that the proposed controller reduces the frequency deviation by up to 25.5% and power variation improved by 20.1% compared with conventional PI-based secondary control during load transition scenarios. Hardware implementation on the NVIDIA Jetson Nano confirms real-time feasibility, maintaining power and frequency tracking errors below 5% under dynamic loading. A comparative analysis of the classical PI and sliding mode control-based designs is conducted under various grid conditions, such as cold ironing mode of the shipboard microgrid, and load variations, considering both the AC and DC loads. The system stability and control law formulation are verified through simulations in MATLAB/SIMULINK and practical implementation. The experimental results demonstrate that the proposed secondary control architecture enhances the system robustness and ensures sustainable operation, making it a viable solution for modern shipboard microgrids transitioning towards green energy. Full article

Energy-intensive industries (EIIs) face mounting pressure to reduce greenhouse gas emissions while maintaining international competitiveness—a balance that is central to achieving the EU’s 2030 and 2050 climate objectives. In this context, energy management (EM) emerges as a strategic instrument to decouple industrial growth from fossil energy consumption. This study proposes a redefinition of EM to support carbon-neutral supply chains within the European Union’s EIIs, addressing critical limitations of conventional EM frameworks under increasingly stringent carbon regulations. Using a modified systematic literature review based on PRISMA methodology, complemented by expert insights from EU Member States, this research identifies structural gaps in current EM practices and highlights opportunities for integrating sustainable innovations across the whole industrial value chain. The proposed EM concept is validated through an analysis of 24 EM definitions, over 170 scientific publications, and over 80 EU legal and strategic documents. The framework incorporates advanced digital technologies—including artificial intelligence (AI), the Internet of Things (IoT), and big data analytics—to enable real-time optimisation, predictive control, and greater system adaptability. Going beyond traditional energy efficiency, the redefined EM encompasses the entire energy lifecycle, including use, transformation, storage, and generation. It also incorporates social dimensions, such as corporate social responsibility (CSR) and stakeholder engagement, to cultivate a culture of environmental stewardship within EIIs. This holistic approach provides a strategic management tool for optimising energy use, reducing emissions, and strengthening resilience to regulatory, environmental, and market pressures, thereby promoting more sustainable, inclusive, and transparent supply chain operations. 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

The Lower–Middle Jurassic of the Kuqa Depression consists of terrestrial clastic deposits containing coal seams and thick lacustrine mudstones, and is of great significance for oil and gas exploration. Based on the comprehensive analysis of core, well-logging, outcrop, and seismic data, the sequence stratigraphy, depositional systems, and the controlling factors of the basin filling in the depression are systematically documented. Four primary depositional systems, including braided river delta, meandering river delta, lacustrine, and swamp deposits, are identified within the Ahe, Yangxia, and Kezilenuer Formations of the Lower–Middle Jurassic. The basin fills can be classified into two second-order and nine third-order sequences (SQ1–SQ9) confined by regional or local unconformities and their correlative conformities. This study shows that the sedimentary evolution has undergone the following three stages: Stage I (SQ1–SQ2) primarily developed braided river, braided river delta, and shallow lacustrine deposits; Stage II (SQ3–SQ5) primarily developed meandering river, meandering river delta, and extensive deep and semi-deep lacustrine deposits; Stage III (SQ6–SQ9) primarily developed swamp (SQ6–SQ7), meandering river delta, and shore–shallow lacustrine deposits (SQ8–SQ9). The uplift of the Tianshan Orogenic Belt in the Early Jurassic (Stage I) may have facilitated the development of braided fluvial–deltaic deposits. The subsequential expansion of the sedimentary area and the weakened sediment supply can be attributed to the planation of the source area and widespread basin subsidence, with the transition of the depositional environments from braided river delta deposits to meandering river delta and swamp deposits. The regional expansion or rise of the lake during Stage II was likely triggered by the hot and humid climate conditions, possibly associated with the Early Jurassic Toarcian Oceanic Anoxic Event. The thick swamp deposits formed during Stage III may be controlled by the interplay of rational accommodation, warm and humid climatic conditions, and limited sediment supply. Milankovitch cycles identified in Stage III further reveal that coal accumulation was primarily modulated by long-period eccentricity forcing. 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

Significant uranium exploration breakthroughs have been achieved in the eolian deposits of the uranium reservoirs in the southwestern part of the Ordos Basin. The redox environment remains a crucial factor in controlling the migration and precipitation of uranium. This study, through rock mineralogical observations and hydrocarbon gas composition analysis, combined with the regional source rock and basin tectonic evolution history, reveals the characteristics of the reducing medium and the mineralization mechanisms involved in uranium ore formation. The Lower Cretaceous Luohe Formation uranium reservoirs in the study area exhibit a notable lack of common reducing media, such as carbonaceous debris and pyrite. However, the total hydrocarbon gases in the Luohe Formation range from 2967 to 20,602 μmol/kg, with an average of 8411 μmol/kg—significantly higher than those found in uranium reservoirs elsewhere in China, exceeding them by 10 to 100 times. Due to the absence of other macroscopically visible organic matter, hydrocarbon gases are identified as the most crucial reducing agent for uranium mineralization. These gases consist predominantly of methane and originate from the Triassic Yanchang Formation source rock. Faults formed during the Indosinian, Yanshanian, and Himalayan tectonic periods effectively connect the Cretaceous uranium reservoirs with the oil and gas reservoirs of the Triassic and Jurassic, providing pathways for the migration of deep hydrocarbon fluids into the Cretaceous uranium reservoirs. The multiphase tectonic evolution of the Ordos Basin since the Cenozoic has facilitated the development of faults, ensuring a sufficient supply of reducing media for uranium reservoirs in an arid sedimentary context. Additionally, the “Replenishment-Runoff-Drainage System” created by tectonic activity promotes a continuous supply of uranium- and oxygen-bearing fluids to the uranium reservoirs, resulting in a multi-energy coupling mineralization effect. Full article

This study analyzes the configurations and control strategies of hybrid heating systems of air-source heat pumps (ASHPs) and gas boilers for space heating in different climatic regions in China, with the aim of improving the comprehensive energy efficiency. Parallel and series hybrid modes were proposed, and simulation analysis was conducted to analyze the energy performance, energy costs, and CO₂ emissions of different hybrid systems. The results show that the supply water temperatures of ASHPs in series mode are lower than that of ASHPs in parallel mode; thus, the COP of ASHPs in series mode reached 2.73 and was higher than the COP of ASHPs in parallel mode with a value of 2.65. Then, the optimal intermediate temperatures of hybrid system in series mode were analyzed, so as to guide the system control. The results show that compared with series mode with a fixed 50% load distribution, the operational costs and CO₂ emissions were reduced by 10.0% and 10.4% in Harbin, reduced by 6.4% and 8.3% in Beijing, and reduced by 10.0% and 15.1% in Wuhan. Additionally, the optimal intermediate temperature was affected by the building load ratio, supply water temperature, ambient air temperature, and the electricity–gas price ratio. The series-hybrid ASHP and gas boiler system achieves remarkable energy and cost savings across different climatic conditions, providing a scientific basis for promoting low-carbon heating solutions. Full article

As market competition intensifies, the survival and development of suppliers increasingly rely on research and development (R&D) investment and innovation. Due to the uncertainty of factors affecting supplier R&D investment, the risks faced by supplier R&D investment are also uncertain. Therefore, identifying and assessing risks in advance and controlling risks can provide effective support for suppliers to carry out risk management of R&D investment. This paper selects key factors through literature review and factor analysis, and establishes a risk index evaluation system for R&D investment of medical material suppliers. Seventeen indicators that affect and constrain project investment factors were identified as input variables of the back propagation (BP) neural network, the comprehensive score of the R&D investment risk assessment was used as the output variable of medical supplies suppliers, and a risk assessment model for the R&D investment of medical material suppliers was established. By leveraging the ability of particle swarm optimization (PSO), whale optimization algorithm (WOA), and genetic algorithm (GA) to search for global optimal solutions, the BP neural network is improved to avoid becoming trapped in local optimal solutions and enhance the model’s generalization ability. The improvement in accuracy and convergence speed of these three methods is compared and analyzed. The results show that the BP neural network improved by the genetic algorithm has better accuracy and faster convergence speed in predicting and assessing risks. This indicates that the BP neural network model improved by genetic algorithm is effective and feasible for predicting the risk assessment of the R&D investment of medical supplies suppliers. 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

The transition to low-carbon heating systems is fundamental to achieving climate neutrality, particularly within the building sector, which accounts for a significant share of global greenhouse gas emissions. Among various technologies, heat pumps have emerged as a leading solution due to their high energy efficiency and potential to significantly reduce CO₂ emissions, especially when powered by renewable electricity. This systematic review synthesizes findings from the recent literature, including peer-reviewed studies and industry reports, to evaluate the technical performance, environmental impact, and deployment potential of air source, ground source, and water source heat pumps. This review also investigates life cycle greenhouse gas emissions, the influence of geographical energy mix diversity, and the integration of heat pumps within hybrid and district heating systems. Results indicate that hybrid HP systems achieve the lowest specific GHG emissions (0.108 kgCO₂eq/kWh of heat delivered on average), followed by WSHPs (0.018 to 0.216 kgCO₂eq/kWh), GSHPs (0.050–0.211 kgCO₂eq/kWh), and ASHPs (0.083–0.216 kgCO₂eq/kWh). HP systems show a potential GHG emission reduction of up to 90%, depending on the kind of technology and energy mix. Despite higher investment costs, the lower environmental footprint of GSHPs and WSHPs makes them attractive options for decarbonizing the building sector due to better performance resulting from more stable thermal input and higher SCOP. The integration of heat pumps with thermal storage, renewable energy, and smart control technologies further enhances their efficiency and climate benefits, regardless of the challenges facing their market potential. This review concludes that heat pumps, particularly in hybrid configurations, are a cornerstone technology for sustainable building heat supply and energy transition. Full article

The long-standing need for a modern public transportation system in Lebanon, a developing country of the Middle East with an almost exclusive dependence on costly and polluting passenger cars, has become more pressing in recent years due to the worsening economic crisis and the onset of hyperinflation. This study investigates the potential reductions in energy use, emissions, and costs from the possible introduction of natural gas, hybrid, and battery-electric buses compared to traditional diesel buses in local real driving conditions. Four operating conditions were considered including severe congestion, peak, off-peak, and bus rapid transit (BRT) operation. Battery-electric buses are found to be the best performers in any traffic operation, conditional on having clean energy supply at the power plant and significant subsidy of bus purchase cost. Natural gas buses do not provide significant greenhouse gas emission savings compared to diesel buses but offer substantial reductions in the emission of all major pollutants harmful to human health. Results also show that accounting for additional energy consumption from the use of climate-control auxiliaries in hot and cold weather can significantly impact the performance of all bus technologies by up to 44.7% for electric buses on average. Performance of all considered bus technologies improves considerably in free-flowing traffic conditions, making BRT operation the most beneficial. A vehicle mix of diesel, natural gas, and hybrid bus technologies is found most feasible for the case of Lebanon and similar developing countries lacking necessary infrastructure for a near-term transition to battery-electric technology. Full article

The “carbon neutral power generation” policy of the European Union requires the phasing out of fossil fuel power plants. These plants still play a crucial role in the energy mix in many countries; therefore, efforts are put forward to lower their CO₂ emissions. The available solution for an existing coal plant is the implementation of biomass co-firing, which allows it to reduce twice its carbon footprint in order to achieve the level of natural gas plants, which are preferable on the way to zero-emission power generation. However the side effect is a significant increase in the bulk fuel volumes that are acquired, handled, and finally supplied to the power plant units. A necessary extension of the complex logistic system for unloading, quality tagging, storing, and transporting biomass may increase the plant’s noise emissions beyond the allowed thresholds. For a comprehensive assessment of the concept of expanding the power plant’s biofuel supply system (BSS), a discrete simulation model was built to dimension system elements and verify the overall correctness of the proposed solutions. Then, a dedicated noise emission model was built for the purposes of mandatory environmental impact assessment procedures for the planned expansion of the BSS. The noise model showed the possibility of exceeding the permissible noise levels at night in selected locations. The new simulations of the BSS model were used to analyze various scenarios of biomass supply with regard to alternative switching off the selected branches of the whole BSS. The length of the queue of unloaded freight trains delivering an average quality biomass after a period of 2 weeks is used as a key performance parameter of the BSS. A queue shorter than 1 freight train is accepted. Assuming the rising share of RESS in the Polish energy mix, the thermal plant’s 2-week average power output shall not exceed 70% of its maximum capacity. The results of the simulations indicate that under these constraints, the biofuel supplies can be sufficient regardless of the nighttime stops, if 50% of the supplied biomass volumes are delivered by trucks. If the trucks’ share drops to 25%, the plant’s 2-week average power output is limited to 45% of its maximum power. The use of digital spatial simulation models for a complex, cyclical-continuous transport system to control its operation is an effective method of addressing environmental conflicts at the design stage of the extension of industrial installations in urbanized areas. Full article

Global agriculture remains dependent on nitrogen fertilizers produced through fossil fuel-based processes, contributing to greenhouse gas emissions, energy use, and supply chain vulnerabilities. This review introduces plasma-activated water (PAW) as a novel, electricity-driven alternative for sustainable nitrogen delivery. Generated by non-thermal plasma, PAW infuses water with reactive oxygen and nitrogen species, offering a clean, decentralized substitute for conventional synthetic fertilizers derived from the Haber–Bosch and Ostwald processes. It can be produced on-site using renewable energy, reducing transportation costs and depending on fertilizers. Beyond its fertilizer properties, PAW enhances seed germination, plant growth, stress tolerance, and pest resistance, making it a multifunctional input for controlled environment agriculture. We also assess PAW’s techno-economic viability, including energy requirements, production costs, and potential scalability through renewable energy. These factors are crucial for determining its feasibility in both industrial systems and localized agricultural applications. Finally, the review examines PAW’s contribution to the ten United Nations Sustainable Development Goals, particularly in climate action, clean energy, and sustainable food production. By combining agronomic performance with circular production and emissions reduction, PAW presents a promising path toward more resilient, low-impact, and self-sufficient agricultural systems. Full article

Electric ducted fans are gaining prominence in aviation due to their compact size, low noise, and zero emissions compared to conventional gas turbines. This study presents an experimental test system for a 390 mm electric Ducted Propulsion Fan developed by the Aerospace Propulsion Systems group at Hanoi University of Science and Technology. The carbon fiber composite thruster, driven by a centrally located BLDC motor, was mounted on a test stand equipped with force and rotational speed (rpm) sensors. Power was supplied through two battery configurations, eight-pack and nine-pack, with voltage and current monitored and controlled via an ESC module. Experiments conducted from 2000 to 7000 rpm explored the relationship between electrical inputs and aero-propulsive outputs. The results revealed that input power, current, and sound pressure level (SPL) amplified meaningfully with rpm, while the voltage slightly declined. The maximum rpm reached 6500 rpm for the eight-pack and 7000 rpm for the nine-pack configurations. When greater than 6000 rpm, the SPL reaches close to 120 dB. The eight-pack configuration provided higher thrust per volt, whereas the nine-pack offered better thrust per ampere and improved starting power. Although dimensionless indices, including power coefficient (CP), thrust coefficient (CT), and figure of merit (FM), reduced with rpm, the FM remained between 0.7 and 0.75 at medium speeds, demonstrating effective energy conversion. Full article