Search Results (7,941)

In Korea, the demand for complete underground installation of power distribution equipment installed on roads and green areas is increasing. In addition, KEPCO is making efforts to build a more reliable system for the underground distribution system. To meet these needs, this paper proposes the S-substation. In the S-substation, an RMU, a large power transformer, and an LV-Board (including ATCB and MCCB) are installed within the underground structure. This paper proposes three models to apply the S-substation to the underground distribution system. Power flow analysis is conducted for each model by simulating a variety of loads and DERs, and the frequency fluctuations are also examined under different distribution system events. An economic analysis is also conducted to select the optimal model. The economic analysis focuses on VOLL and construction costs. Based on power flow and economic analysis, one model is selected, and the underground distribution system that the model is applied is presented. Full article

Due to the complex nature of the built environment, urban wind flow is unpredictable and characterised by high levels of turbulence and low mean wind speed. Yet, there is a potential for harnessing urban wind power by carefully integrating wind turbines within the built environment at the optimum locations. This requires a thorough investigation of wind resources to use the suitable wind turbine technology at the correct location—thus, the need for an accurate assessment of wind resources at the proposed site. This paper reviews the commonly used wind assessment tools for the urban wind flow to identify the optimum tool to be used prior to integrating wind turbines in urban areas. In situ measurements, wind tunnel tests, and CFD simulations are analysed and reviewed through their advantages and disadvantages in assessing urban wind flows. The literature shows that CFD simulations are favoured over other most commonly used tools because the tool is relatively easier to use, more efficient in comparing alternative design solutions, and can effectively communicate data visually. The paper concludes with recommendations on best practice guidelines for using CFD simulation in assessing the wind flow within the built environment and emphasises the importance of validating CFD simulation results by other available tools to avoid any associated uncertainties. Full article

The electrical protection of active distribution networks is crucial for ensuring reliable, safe, and flexible operations. However, protecting these networks presents several challenges due to the emergence of bi-directional power flows, network reconfiguration capabilities, and changes in fault current levels resulting from the integration of inverter-based resources. This paper introduces an innovative protection strategy for active distribution networks, leveraging the principles of distributed coordination and multi-agent systems. The proposed strategy consists of two stages. The first stage involves a fault detection algorithm that relies solely on local measurements, while the second stage uses agent classification to compute the optimal operating time based on a dynamic matrix representation of the fault path, combined with a simplified distributed optimization problem. The coordination process is formulated as a set of linear optimization problems, simplifying the solution. The proposed protection strategy is validated in a real-time simulation environment using a modified CIGRE MV European grid as a case study, considering low-impedance symmetric fault scenarios and topological changes. The results demonstrate that the protection scheme exhibits robust performance, enhancing the adaptability of the protection equipment while ensuring suitable sensitivity and operational speed. Full article

Our recent analysis of empirical limit order flow data in financial markets reveals a power-law distribution in limit order cancellation times. These times are modeled using a discrete probability mass function derived from the Tsallis q-exponential distribution, closely aligned with the second form of the Pareto distribution. We elucidate this distinctive power-law statistical property through the lens of agent heterogeneity in trading activity and asset possession. Our study introduces a novel modeling approach that combines fractional Lévy stable motion for limit order inflow with this power-law distribution for cancellation times, significantly enhancing the prediction of order imbalances. This model not only addresses gaps in current financial market modeling but also extends to broader contexts such as opinion dynamics in social systems, capturing the finite lifespan of opinions. Characterized by stationary increments and a departure from self-similarity, our model provides a unique framework for exploring long-range dependencies in time series. This work paves the way for more precise financial market analyses and offers new insights into the dynamic nature of opinion formation in social systems. Full article

With the increasing share of renewable energy in the power system, traditional power flow calculation methods are facing challenges of complexity and efficiency. To address these issues, this paper proposes a new framework for AC optimal power flow analysis based on a physics-informed convolutional neural network (PICNN) approach, which enables the neural network to learn solutions that follow physical laws by embedding the power flow equations and other physical constraints into the loss function of the network. Compared with the traditional power flow calculation method, the calculation speed of this method is improved by 10–30 times. Compared to traditional neural network models, the method provides higher accuracy, with an average increase in accuracy of up to 2.5–10 times. In addition, this paper introduces a methodology to extract worst-case guarantees for violations of the neural network’s predicted power generation constraints, determining the worst possible violation that could result from any neural network output across the entire input domain, and taking appropriate measures to reduce the violation. The method is experimentally shown to be highly accurate and reliable for the AC optimal power flow (AC-OPF) analysis problem, while reducing the dependence on a large amount of labelled data. Full article

An analysis of the physical and chemical phenomena accompanying electrical discharges is carried out, and the main factors influencing microorganisms’ abatement are studied. The similarity of the cavitation processes in water systems induced by underwater electric discharges and ultrasound is experimentally demonstrated. The characteristic features of electrical discharge in the cavitation mode, providing effective water disinfection with electric discharges with a significantly reduced amount of active chlorine, are identified in order of importance. The inactivation of microorganisms is intensified, firstly, by the generation of chemically active particles from the water medium itself, due to the integral action of the electro-discharge cavitation of the whole treated volume, and by local shock waves, acoustic flows, and ultraviolet radiation in the area near the cavitating bubbles. The main advantages of electric discharge cavitation over ultrasonic range are the wider range of high-frequency acoustic radiation inherent in an electric discharge, the high intensity and power of the cavitation processes, and the possibility of a significant increase in the volume of disinfected liquid. This study allows for a better understanding and prediction of the bacterial effects that occur during a high-voltage underwater electrical discharge. Full article

Entrepreneurial activities are crucial for activating the endogenous power of the countryside, promoting integrated urban and rural development, and achieving comprehensive rural revitalization. This paper empirically examines the mechanisms through which entrepreneurial activities influence rural revitalization by incorporating the theory of dissipative structures into the research paradigm of rural revitalization. Using interdisciplinary analysis methods, it deeply analyzes the underlying logic of entrepreneurial activities affecting rural revitalization, relying on panel data from 2045 counties from 2011 to 2020. The study finds that entrepreneurial activities attract negative entropy flows, such as information and materials, into the rural revitalization system by increasing employment opportunities and promoting capital agglomeration. This fosters a stable and orderly dissipative structure within the system, thereby empowering comprehensive rural revitalization. The heterogeneity test indicates that the promotion effect of entrepreneurial activities on rural revitalization is more pronounced in the eastern region and non-e-commerce demonstration counties. Further research reveals that the facilitating effect of entrepreneurial activities on the rural revitalization system is particularly evident in four dimensions: ecological viability, a civilized rural culture, effective governance, and an affluent life. This study provides theoretical and empirical support for implementing the rural revitalization strategy in China. Full article

Many dynamic random-access memory (DRAM) manufacturing companies encounter significant resistance value deviations during the PVD sputtering process for manufacturing Ti thin films. These resistance values are influenced by the thickness of the thin films. Current mitigation strategies focus on adjusting film thickness to reduce resistance deviations, but this approach affects product structure profile and performance. Additionally, varying Ti thin film thicknesses across different product structures increase manufacturing complexity. This study aims to minimize resistance value deviations across multiple film thicknesses with minimal resource utilization. To achieve this goal, we propose the TSDTM-ANN-GA framework, which integrates the two-stage dynamic Taguchi method (TSDTM), artificial neural networks (ANN), and genetic algorithms (GA). The proposed framework requires significantly fewer experimental resources than traditional full factorial design and grid search method, making it suitable for resource-constrained and low-power computing environments. Our TSDTM-ANN-GA framework successfully identified an optimal production condition configuration for five different Ti thin film thicknesses: Degas temperature = 245 °C, Ar flow = 55 sccm, DC power = 5911 W, and DC power ramp rate = 4009 W/s. The results indicate that the deviation between the resistance values and their design values for the five Ti thin film thicknesses decreased by 86.8%, 94.1%, 95.9%, 98.2%, and 98.8%, respectively. The proposed method effectively reduced resistance deviations for the five Ti thin film thicknesses and simplified manufacturing management, allowing the required design values to be achieved under the same manufacturing conditions. This framework can efficiently operate on resource-limited and low-power computers, achieving the goal of real-time dynamic production parameter adjustments and enabling DRAM manufacturing companies to improve product quality promptly. Full article

Acquiring real-time status information of the distribution system forms the foundation for optimizing the management of power system operations. However, missing measurements, bad data, and inaccurate system models present a formidable challenge for distribution system state estimation (DSSE) in practical applications. This paper proposes a physics-informed graphical learning state estimation approach, to address these limitations by integrating power flow equations and GraphSAGE. The generalization ability of GraphSAGE for unknown nodes is used to perform inductive learning of measurement information. For unseen measurement points in the training set, the simulation proves that the proposed approach can still satisfactorily predict the state quantity. The training process is guided by power flow equations to ensure it has physical significance. Additionally, the possibility of applying the proposed approach to an actual distribution area is explored. Equivalent preprocessing of the three-phase voltage measurement data of the actual distribution area is conducted to improve the estimation accuracy of the transformer measurement points and simplify the computation required for state estimation. Full article

The search for more efficient power grids has led to the concept of microgrids, based on the integration of new-generation technologies and energy storage systems. These devices inherently operate in DC, making DC microgrids a potential solution for improving power system operation. In particular, bipolar DC microgrids offer more flexibility due to their two voltage levels. However, more complex tools, such as optimal power flow (OPF) analysis, are required to analyze these systems. In line with these requirements, this paper proposes an OPF for bipolar DC microgrid reconfiguration aimed at minimizing power losses, considering dispersed generation (DG) and asymmetrical loads. This is a mixed-integer nonlinear optimization problem in which integer variables are associated with the switch statuses, and continuous variables are associated with the nodal voltages in each pole. The problem is formulated based on current injections and is solved by a hybridization of the differential evolution algorithm (to handle the integer variables) and the interior point method-based OPF (to minimize power losses). The results show a reduction in power losses of approximately 48.22% (33-bus microgrid without DG), 2.87% (33-bus microgrid with DG), 50.90% (69-bus microgrid without DG), and 50.50% (69-bus microgrid with DG) compared to the base case. Full article

With the progress of research on ocean thermal energy conversion, the stabI have checked and revised all. le operation of ocean thermal energy conversion experiments has become a problem that cannot be ignored. The control foundation for stable operation is the accurate prediction of operational performance. In order to achieve accurate prediction and optimization of the performance of the ocean thermal energy conversion experimental platform, this article analyzes the experimental parameters of the turbine based on the basic experimental data obtained from the 50 kW OTEC experimental platform. Through the selection and training of experimental data, a GA-BP-OTE (GBO) model that can automatically select the number of hidden layer nodes was established using seven input parameters. Bayesian optimization was used to complete the optimization of hyperparameters, greatly reducing the training time of the surrogate model. Analyzing the prediction results of the GBO model, it is concluded that the GBO model has better prediction accuracy and has a very low prediction error in the prediction of small temperature changes in ocean thermal energy, proving the progressiveness of the model proposed in this article. The dual-objective optimization problem of turbine grid-connected power and isentropic efficiency is solved. The results show that the change in isentropic efficiency of the permeable device is affected by the combined influence of the seven parameters selected in this study, with the mass flow rate of the working fluid having the greatest impact. The MAPE of the GBO model turbine grid-connected power is 0.24547%, the MAPE of the turbine isentropic efficiency is 0.04%, and the MAPE of the turbine speed is 0.33%. The Pareto-optimal solution for the turbine grid-connected power is 40.1792 kW, with an isentropic efficiency of 0.837439. Full article

Acoustic waves can be used for wireless telemetry as an alternative to situations where electrical or optical penetrators are unsuitable. However, the response of the ultrasonic transducer can be greatly affected by temperature variations, mechanical deformations, misalignment between transducers, and multiple layers in the propagation zone. Therefore, this work sought to quantify such influences on communication between ultrasonic transducers. The experimental measurements were performed at the frequency where power transfer is maximized. Moreover, there were four experimental models, each with its own performed setup. The ultrasonic transducers are attached to both sides of a 6 mm thick stainless-steel plate for configuring just one barrier. Multiple layers of transducers are attached to the outer side of two plates immersed in an acoustic fluid with a 100 mm thick barrier. In both cases, the S21 parameter was used to quantify the influence of the physical barrier because it correlates with the power flow between ports that return after a given excitation. The results showed that when a maximum deformation of 1250 $\mathsf{\mu }\mathrm{m}/\mathrm{m}$ was applied, the amplitude of the S21 parameter varied around +0.7 dB. Furthermore, increasing the temperature from 30 to 100 °C slightly affected the S21 (+0.8 dB), but the signal decayed quickly for temperatures beyond 100 °C. Additionally, the ultrasonic communication with a multiple layer was found to occur under misalignment with an intersection area of up to 40%. None of the factors evaluated resulted in insufficient power transfer, except for a large misalignment between the transducers. Such results indicate that this type of communication can be a robust alternative, with a minimum alignment of 40% between transducers and electrical penetrators. Full article

The objective of this study is to implement a more realistic integrated analysis model for micro gas turbines by incorporating secondary flow and combustion efficiency into the existing model, which includes main engine components such as the compressor and turbine, and to validate this model by comparing it with test results. The study was based on the JetCat P300-RX, which has a maximum thrust level of 300 N. Simulations were performed using ANSYS CFX, employing the κ-ω SST turbulence model and a mixing plane interface between individual components. The eddy dissipation model (EDM), with a combustion efficiency of 90%, was used as the combustion model. A user subroutine was also applied for the power matching of the compressor and turbine to calculate the fuel flow rate in each iteration. For secondary flow, it was assumed that 3% of the total air flow rate would flow through the secondary path and be applied to the compressor and turbine. Simulations were conducted over a range of 30,000 to 104,000 RPM, with ground conditions evaluated, including altitude-simulated conditions. To validate the analysis model, engine performance metrics such as pressure ratio, air flow rate, fuel flow rate, and exhaust gas temperature (EGT) were compared with test results. The results demonstrated that errors were less than 5% for most engine performance metrics, except for EGT and fuel flow. The discrepancy in EGT was attributed to differences in the sensing methods, while the variation in fuel flow was found to be due to the lubrication system and losses due to the secondary air flow. Consequently, this study confirmed that the integrated simulation model accurately predicts engine performance. The results indicate that the integrated simulation model provides a more realistic prediction of overall engine performance compared to previous studies. Therefore, it can evaluate detailed thermo-fluid properties without the need for component performance maps, enhancing performance evaluation and analysis. Full article

This paper presents reduced-order modeling of thermal power dispatch (TPD) from a pressurized water reactor (PWR) for providing heat to nearby heat consuming industrial processes that seek to take advantage of nuclear heat to reduce carbon emissions. The reactor model includes the neutronics of the reactor core, thermal–hydraulics of the primary coolant cycle, and a three-lump model of the steam generator (SG). The secondary coolant cycle is represented with quasi-steady state mass and energy balance equations. The secondary cycle consists of a steam extraction system, high-pressure and low-pressure turbines, moisture separator and reheater, high-pressure and low-pressure feedwater heaters, deaerator, feedwater and condensate pumps, and a condenser. The steam produced by the SG is distributed between the turbines and the extraction steam line (XSL) that delivers steam to nearby industrial processes, such as production of clean hydrogen. The reduced-order simulator is verified by comparing predictions with results from separate validated steady-state and transient full-scope PWR simulators for TPD levels between 0% and 70% of the rated reactor power. All simulators indicate that the flow rate of steam in the main steam line and turbine systems decrease with increasing TPD, which causes a reduction in PWR electric power generation. The results are analyzed to assess the impact of TPD on system efficiency and feedwater flow control. Due to the simplicity of the proposed reduced-order model, it can be scaled to represent a PWR of any size with a few parametric changes. In the future, the proposed reduced-order model will be integrated into a power system model in a digital real-time simulator (DRTS) and physical hardware-in-the-loop simulations. Full article

In order to achieve low carbon emissions in the power grid, the impact of new energy grid connections on the power grid should be reduced, as well as the peak-to-valley load difference caused by large-scale electric vehicle grid connections. This paper proposes a two-tier, low-carbon optimal dispatch master–slave game model involving virtual power plant operators as well as electric vehicle operators. Firstly, the carbon flow is tracked based on the proportional sharing principle, and the carbon emission factor during the charging and discharging process of electric vehicles is calculated. Secondly, the node carbon potential and time-sharing tariff are used to guide and change the charging behaviour of electric vehicles and to construct a master–slave game model for low-carbon optimal scheduling with the participation of multiple subjects, with economic scheduling at the upper level of the model and demand response scheduling at the lower level. Finally, the IEEE30 node system is used as an example to verify that the method adopted in this paper can effectively reduce the peak-to-valley difference of loads, reduce the carbon emissions of the grid, and reduce the cost of each participating entity. Full article