Energy Science & Engineering最新文献

The vertical two-stage centrifugal pump (VTSP) is well-suited for small pumped storage power stations with high head and low discharge, such as those found in underground mines. Based on entropy theory, this study presents a comparative numerical analysis of the flow energy dissipation (FED) in a VTSP under two distinct operating conditions: pump condition and turbine condition, both characterized by relatively high hydraulic efficiencies of 88.9% and 87.4%, respectively. The numerical solutions were obtained using the steady-state single-phase SST k-ω turbulence model. The results indicate that the region within 2 mm of the wall contributes the majority of the FED production in both pump and turbine conditions. This portion of the FED is influenced by the viscosity-dominated flow-wall interaction. In pump condition, the highest FED production occurs in the return channel, with the backward vane and forward vane regions contributing 38.3% and 14.4%, respectively. In turbine condition, the highest FED production occurs in the runners, with the first and second-stage runners contributing 43.7% and 21.4%, respectively. To enhance efficiency in both modes, reducing the surface roughness of the flow channels is recommended. Additionally, optimizing the alignment between the guide vanes within the return channel and the fluid, as well as improving the matching between the runner blades and the fluid, can further improve efficiency in pump and turbine conditions, respectively.

In this study, a novel optimization approach is proposed for cleanroom ventilation systems with a specific focus on plastic injection molding machines used in pharmaceutical manufacturing. The research uses MATLAB-based numerical modeling to analyze the effects of air changes per hour (ACH), fresh air intake percentage, and internal heat generation on energy consumption. Three different climatic conditions—winter, mild spring, and summer—are examined to determine the optimal operating parameters for heating, ventilation, and air conditioning (HVAC) systems. The results indicate that adjusting ACH and fresh air intake percentages dynamically based on seasonal variations reduces heating and cooling loads significantly. In winter conditions, a 50% fresh air intake at an ACH of 50 minimizes heating demand by utilizing internally generated heat. In summer, increasing fresh air intake optimally lowers cooling demand by exhausting excess equipment-generated heat. Moreover, implementing intelligent control strategies based on real-time temperature monitoring reduces unnecessary energy consumption while maintaining required cleanroom standards. These findings demonstrate that strategic HVAC adjustments can enhance energy efficiency, reducing overall heating and cooling loads without compromising cleanroom air quality and regulatory compliance.

This study introduces an advanced adaptive protection approach for AC power systems, designed to address key limitations in current clustering-based relay coordination methods. Using K-means, hierarchical, and spectral clustering techniques, the proposed scheme classifies grid operating conditions more effectively, ensuring that relay settings adapt to different network scenarios. A key feature of this study is a practical method for identifying the optimal number of clusters and selecting the fine-tuning relay settings using the Genetic and Tug of War Optimisation algorithms, which improves the speed of fault detection and isolation over twenty different network topologies. The proposed scheme supports standard and non-standard Overcurrent Relay (OCR) characteristics, in which the IEC inverse-time curve is expanded beyond its conventional pickup-current limit to capture higher fault-current levels in renewable-integrated networks, ensuring faster and more selective relay operation. In Clustering 1 (Topology 1), the total tripping time was reduced to 23.15 s, while Clustering 2 (Topology 16), involving more relays, recorded 29.77 s. The total tripping time for Clustering 3 (Topology 2) was 29.34 s. Hardware-in-the-Loop (HIL) testing verified the real-time performance of the proposed scheme, showing high performance with simulation results and less than 2% deviation in relay tripping times. These outcomes demonstrate the scheme's ability to deliver reliable and responsive protection across various grid environments.

This study addresses the challenges of deformation failure and the difficulty in controlling the surrounding rock in the 2453 floor roadway of a coal mine in Hunan Province, influenced by mining activities. Conducting an in-depth investigation into the evolution law of the principal stress and stability control technologies for the surrounding rock of the floor roadway under the influence of mining. The research employs a combination of on-site investigations, laboratory tests, numerical simulations, and industrial trials. The results indicate that high horizontal tectonic stress and the characteristics of soft rock can easily lead to significant deformation of the surrounding rock in the roadway. By monitoring the principal stress in each part of the surrounding rock from the excavation of the 2453 floor roadway to the completion of upper coal seam mining, we obtained the evolution of the principal stress in the surrounding rock influenced by mining activities. During the mining process, the plastic zone in the “butterfly leaf” region of the surrounding rock in the roadway exhibits malignant extension; however, the depth and extent of the plastic zone on the sides remain largely unchanged. Based on this, a comprehensive support technical scheme is proposed, featuring “full-face high pre-tightening force bolt supporting + enhancing the support with long anchor cables at the key part of the plastic zone in roadway + grouting” as the main supporting body, complemented by “metal mesh + shotcrete” as auxiliary support measures. On-site monitoring has shown that the new support scheme more effectively controls the stability of the surrounding rock.

The current study analyzes the performance and emission attributes of different blends (0%, 20%, 40%, 60%, 80%, and 100% being termed as MB0, MB20, MB40, MB60, MB80 and MB100, respectively) of biodiesel derived from Raphanus Sativus, Jatropha, and Balanites aegyptiaca seeds with conventional diesel. The MB0 blend was pure diesel, and the MB100 blend was pure biodiesel (with no diesel). Critical performance parameters like Brake Thermal Efficiency (BTE), Brake Specific Fuel Consumption (BSFC), and Exhaust Gas Temperature (EGT) were evaluated experimentally. Moreover, the environmental effects were assessed by measuring emission characteristics such as Carbon Monoxide (CO), Hydrocarbons (HC), Nitrogen Oxides (NO_x), and Smoke Opacity. The results indicated that the mixed biodiesel blend MB20 exhibited a higher BSFC by 5.08% and a lower BTE by 3.13% compared to diesel at maximum load. The emission characteristics are much better performed by MB20 when compared with diesel. Additionally, the study examined the influence of diethyl ether as an oxygenated additive on the targeted biodiesel blend. The improved biodiesel blend (MB20) was blended with 5%, 10%, and 15% DEE, and MB95E5, MB90E10, and MB85E15 were prepared. Incorporating diethyl ether dramatically changed combustion behavior. The performance and emission characteristics were substantially changed. The results are presented and discussed here.

This paper presents the Lyapunov stability scheme based nonlinear power transfer matrix (NLPTM) model for controlling and modeling the permanent magnet synchronous generator (PMSG) based wind turbine. The proposed model considers active and reactive power as system state variables; thus, the rotor flux has no impact on the changes in stator active and reactive powers. This approach is based on a nonlinear technique employed on the machine-side ac/dc converter (MSC) and the grid-side dc/ac converter (GSC) of the PMSG wind turbine to reduce the oscillating current during the energy conversion process. The effectiveness of the proposed Lyapunov-integrated NLPTM approach is evaluated on a nonlinear controller-integrated PMSG wind system through simulation and is validated against an existing control scheme under transient operating conditions. The results proved the proposed approach's superiority in enhancing the power flow and suppressing the transient currents to improve the stability of the PMSG wind turbine.

During ultra-deep well drilling, the narrow safety density window of the drilling fluid makes it prone to complex conditions such as gas invasion. The high-temperature and high-pressure environment causes changes in the properties of the drilling fluid, making the gas invasion process highly covert and increasing the difficulty of well control. To address the challenge of accurately predicting gas migration velocity under gas invasion conditions in ultra-deep wells, this study considers the impact of temperature and pressure on the properties of the drilling fluid. A fluid state equation for ultra-deep wells was established. Based on the coupling effects of various parameters, a gas migration velocity model applicable to multi-well types and multi-factor coupling influences was developed. This model can calculate conditions for high-viscosity drilling fluids and analyze the impact of different parameters on gas migration velocity in vertical and horizontal wells. Additionally, suppression methods for gas migration velocity in ultra-deep wells were proposed. The study shows that an increase in drilling fluid viscosity, drilling fluid density, annular backpressure, and gas-liquid density ratio reduces the gas content in the wellbore and suppresses the increase in gas migration velocity. An increase in formation permeability results in a higher gas content in the wellbore, promoting an increase in gas migration velocity. The impact of drilling fluid displacement on wellbore gas content is complex. To reduce gas migration velocity, high-density and high-viscosity drilling fluids can be used, along with appropriate increases in wellhead backpressure and drilling fluid flow rate, to prevent gas invasion. This study helps to better understand the multiphase flow characteristics in the wellbore under gas invasion conditions in ultra-deep wells, ensuring the smooth operation of ultra-deep well drilling.

Solar photovoltaic (PV) systems can be significantly enhanced through the use of accurate solar cell models. Unfortunately, the absence of precise parameters from manufacturers limits the accuracy of these models. Given the impossibility of reliable modeling without such parameters, this paper introduces a multi-objective optimization algorithm to estimate the necessary parameters effectively. The problem of suboptimal optimization results often arises due to local minima and premature convergence of the optimization algorithm, even though there are a number of optimization algorithms that address this issue. This paper is intended to examine the reliability of the proposed algorithm to determine if it is reliable. For the purpose of showing the proficiency of the proposed optimization algorithms, their performance is compared with that of some other well-known algorithms to show their superiority. The performance of the algorithm is validated by comparing experimental results, including analyses based on statistical data, with estimated parameters based on statistical analysis. Furthermore, the results obtained with the proposed algorithms indicate that they are better suited for estimating solar PV models than the other algorithms i.e., rmse of the proposed algorithm for three diode model is 4.21E−13 as well as 3.20E−13 for four diode model. A simple structure and high accuracy are the main characteristics of the proposed algorithm, which indicates its potential for a variety of applications in the solar energy field in the future. Moreover, the proposed algorithm is computationally efficient as well as easy to use and can be applied to a number of applications.

This paper focuses on the stability of synchronous operation (SSO) of three-stage hydropower stations cascaded by regulating reservoirs (THSRRs). Firstly, the model of synchronous operation of THSRRs is established. According to the model, the Hopf bifurcation theory is utilized to analyze the SSO of THSRRs. Then, the critical stable sectional areas(CSSAs) of the first and second-stage regulating reservoirs (FSRR and SSRR) are identified. The role of the regulating reservoir areas on the stable domain is explored. Finally, the coupling effects of the governor-regulating reservoirs on the system are analyzed. The results show that the largest stable domain is found in the third-stage hydropower station(TSHS). The smallest one is found in the second-stage hydropower station(SSHS). The increase in area of regulating reservoir is beneficial to the upstream hydropower station but detrimental to the downstream hydropower station. Under the parameters of the hydropower stations, there are two positive solutions for the CSSAs of the adjacent regulating reservoirs and only one positive solution for the nonadjacent reservoir. The increase in integral gain is detrimental to the stable domain. As the proportional gain increases, the stable domain firstly increases and then decreases. This study provides technical support for the secure running of THSRRs.

Climate change continues to challenge both environmental stability and economic systems worldwide. Among available mitigation strategies, nature-based carbon management (NBCM) methods provide the dual advantage of reducing atmospheric carbon dioxide (CO₂) and restoring ecosystems. This review examines four main NBCM approaches, forest and grassland restoration, wetland and blue-carbon ecosystems, urban green spaces, and regenerative agriculture, to test the hypothesis that biochar-based regenerative agriculture is the most sustainable and practical pathway for long-term carbon sequestration. Confirming this hypothesis is essential because policy and investment decisions increasingly depend on identifying NBCM options that combine scientific effectiveness with economic feasibility. The study reviews papers, patents, and reports published between 2016 and 2024, integrating environmental, technological, and policy findings. The review reveals several key insights. Nature-based methods collectively offer significant global potential for carbon reduction, yet their success depends on ecological and socioeconomic conditions. Biochar-based regenerative systems stand out by showing persistent improvements in soil-organic-carbon storage, crop productivity, and greenhouse-gas mitigation, supported by numerous international case studies. The analysis also identifies the main constraints, production cost, infrastructure requirements, and limited awareness, that determine the pace of large-scale adoption. The contribution of this review lies in linking biochar's environmental durability with its socioeconomic applicability, providing a bridge between climate science, agriculture, and sustainable development policy. Future efforts should focus on field validation across climates, cost optimization for biomass-to-biochar chains, and supportive policy frameworks to encourage wider adoption. These findings present a clear pathway for scaling NBCM solutions, positioning biochar as a leading nature-based strategy for long-term climate mitigation.