Hasil untuk "Production of electric energy or power. Powerplants. Central stations"

Pengcheng Wang, Xuqi Lin, Houlin Cheng et al.

ABSTRACT Na3V2(PO4)3 (NVP) is a promising electrode material that exhibits magnetic anisotropy; however, the potential of this magnetic anisotropy to optimize battery performance has been largely unexplored. This study proposes a cost‐effective and efficient method to induce the alignment of NVP along the (113) crystal plane by applying a vertical magnetic field during the slurry coating process, thereby enhancing its battery performance. Comprehensive structural characterizations and theoretical analysis elucidate the structure‐activity relationship between the preferred crystal orientation and ion transport kinetics, facilitating the formation of more ordered Na+ deintercalation pathways in NVP electrodes. This alignment reduces electrode tortuosity, enhances interfacial compatibility, and substantially improves battery performance, particularly in terms of high‐rate cycling capability. As a result, the magnetic‐field‐modulated NVP (NVP−M⊥) electrode exhibits a high capacity retention of 85.1% after 500 cycles at 5 C, significantly surpassing that of the pristine electrode. The NVP−M⊥ electrode also demonstrates considerable reversible capacity at 40 C and maintains excellent stability under high temperature and prolonged cycling conditions. Furthermore, superior battery performance is observed in the assembled NVP−M⊥||hard−carbon pouch cell and commercial NVP electrode following magnetic‐field modulation, thereby validating the efficacy of this method. Consequently, this magnetic‐field‐induced crystal‐orientation optimization strategy provides an innovative approach for low‐cost and high‐throughput preparation of high‐performance sodium‐ion batteries.

Yunrui Lan, Mahesh S. Illindala

This paper proposes a resilient distributed load frequency control (DLFC) strategy for interconnected power systems with high penetration of solar photovoltaic (PV) under physical-layer denial-of-service (DoS) attacks targeting phasor measurement units (PMUs). Firstly, to address the uncertainty in the conventional small-signal models due to the intermittency and the operating point shift caused by renewable energy integration, the system dynamics are reformulated using an uncertain but bounded time-varying parameter matrix. Secondly, a probabilistic attack model is constructed based on Bernoulli random processes to characterize the physical PMU DoS attacks. This model is explicitly embedded into the DLFC controller design, enabling the system to tolerate intermittent measurement losses. Thirdly, a distributed robust controller synthesis method is developed under linear matrix inequality constraints, providing sufficient conditions to ensure mean-square stability and robust performance in the presence of measurement dropouts and parameter uncertainties. The effectiveness of the proposed control strategy is verified on a four-area interconnected power system subjected to varying levels of system uncertainties and DoS attack conditions. The simulation results demonstrate the strategy’s robustness and resilience in maintaining frequency stability and ensuring cooperative control performance despite adverse disturbances.

Dávid Kóczi, József Sárosi

In the safety technology of collaborative robots, standards differentiate between various collision types, the identification and differentiation of which are essential for ensuring safe operation. The objective of this paper is to develop and test a mechanism actuated by artificial muscle to examine the detection of these profiles in different collision scenarios. The ISO 15066 standard distinguishes between two types of collisions: quasi-static and transient. Using a simplified model, experiments were conducted to evaluate whether sensors could identify collision types accurately. The results demonstrate the feasibility of identifying collision types through sensor data. The findings have the potential to enhance the safety of collaborative robots.

Sirisak Pangvuthivanich, Wirachai Roynarin, Promphak Boonraksa et al.

ABSTRACT Insufficient dissolved oxygen in aquaculture systems poses a significant challenge to sustainable fish farming, while traditional aeration systems rely heavily on grid electricity, contributing to both operational costs and environmental impact. This study addresses these challenges by integrating a compressed air oxygenation system with floating solar photovoltaic (PV) power generation, supported by deep learning‐based forecasting for optimal system control. Our key contributions include: (1) development of an integrated floating PV‐powered compressed air oxygenation system for aquaculture, (2) implementation and comparative analysis of three deep learning models (RNN, GRU and LSTM) for forecasting both PV power generation and compressed air production and (3) validation through a real‐world case study in Thailand's Pathum Thani Province. The LSTM model demonstrated superior performance, achieving the highest accuracy with RMSE of 172.59 kW and MAPE of 13.87% for PV power forecasting, and a MAPE of 21.72% for compressed air production forecasting. The implemented system successfully improved water quality in a 1200‐cubic‐metre freshwater fish pond, increasing dissolved oxygen levels from 1.7 to 6.47 mg/L over a 4‐month period. These results demonstrate the feasibility and effectiveness of renewable energy integration in aquaculture water treatment, offering a sustainable solution for fish farming operations while reducing dependency on grid electricity.

Jatin, Divya Bharathi Raj, Venkatakirthiga Murali

Mateus A. Fernandes, Michael M. Furlanetti, Eduardo Gildin et al.

Forecasting production reliably and anticipating changes in the behavior of rock-fluid systems are the main challenges in petroleum reservoir engineering. This project proposes to deal with this problem through a data-driven approach and using machine learning methods. The objective is to develop a methodology to forecast production parameters based on simple data as produced and injected volumes and, eventually, gauges located in wells, without depending on information from geological models, fluid properties or details of well completions and flow systems. Initially, we performed relevance analyses of the production and injection variables, as well as conditioning the data to suit the problem. As reservoir conditions change over time, concept drift is a priority concern and require special attention to those observation windows and the periodicity of retraining, which are also objects of study. For the production forecasts, we study supervised learning methods, such as those based on regressions and Neural Networks, to define the most suitable for our application in terms of performance and complexity. In a first step, we evaluate the methodology using synthetic data generated from the UNISIM III compositional simulation model. Next, we applied it to cases of real plays in the Brazilian pre-salt. The expected result is the design of a reliable predictor for reproducing reservoir dynamics, with rapid response, capability of dealing with practical difficulties such as restrictions in wells and processing units, and that can be used in actions to support reservoir management, including the anticipation of deleterious behaviors, optimization of production and injection parameters and the analysis of the effects of probabilistic events, aiming to maximize oil recovery.

Seda Hatice Gökler

A. V. Sinyukov, E. Yu. Abdullazyanov, T. V. Sinyukova et al.

THE RELEVANCE of the research lies in the need to improve existing control systems for industrial mechanisms with minimal investment in reconstruction, as well as the demand for reliable control systems, the use of which can increase the service life of the device as a whole.THE PURPOSE. To develop a simple and at the same time effective control system for an industrial facility that allows damping vibrations of a flexible load. On overhead cranes, one of the mechanisms for moving cargo around the workshop is the trolley mechanism. The overhead crane trolley is used to move cargo along the bridge span, and the transported cargo can have either a rigid or flexible suspension. The use of a flexible suspension leads to vibrations in the form of rocking of the moved load. These vibrations are a negative phenomenon that has a negative impact on the mechanical structure of the crane and on the electrical control system of the electric drive of the trolley. An asynchronous motor with a squirrel-cage rotor is installed on the mechanism under consideration; based on the research carried out, a vector system was selected to control it, into which, in order to suppress load fluctuations, it was proposed to introduce a controller operating on the basis of fuzzy logic. The proposed fuzzy controller adjusts the engine speed depending on the angle of deflection of the flexible load; its uniqueness lies in its ease of implementation and the minimum number of control signals. Regulators of this type have proven themselves well, as they have high speed, good response in dynamics, and allow optimization of the control system by indirectly determining parameters.METHODS. During the study, mathematical modeling techniques were used to solve the identified problems. The study of the control system was carried out in the MATLAB modeling environment in the Simulink subsystem.RESULTS. The article reflects the significance of the research topic and discusses the available methods for damping vibrations of a flexible load. For the study, a system was developed containing a subsystem whose functions include tracking the dynamics of the movement of the cart and cargo. This article proposes a control controller operating on the basis of fuzzy logic rules. The controller is simple to implement, has one control signal, while fuzzy logic allows you to flexibly configure the control system, which makes it possible to obtain the required control characteristics.CONCLUSION. Simulation of the trolley operation process in the MATLAB Simulink environment took place with a change in the mass of the load and the length of the suspension; the analysis of all modeling options led to the conclusion that the proposed controller based on fuzzy logic makes it possible to dampen load fluctuations for various initial parameters.

Andrius Čeponis, Dalius Mažeika

This paper introduces a novel piezoelectric actuator designed for precise linear and rotational movements of a cylindrical slider-rotor. The actuator’s design features two elliptical frames interconnected by two plates, with a cylindrical contact situated on the top of the upper plate to facilitate the motion or rotation of the slider. Two piezoelectric multilayer transducers are housed within each elliptical frame and are used to excite vibrations of the elliptical frames using two harmonic signals with a phase difference of π/2 and varying excitation schemes. This excitation pattern generates elliptical motion trajectories of the contact in two orthogonal planes, enabling both linear and rotational displacements of the slider-rotor. Numerical and experimental investigations were conducted to validate the performance and accuracy of the actuator. Additionally, harmonic response and transient analysis were performed to investigate elliptical motion trajectories of the contact in perpendicular planes under various excitation schemes and frequencies. The results confirm that the rotational and linear motions of the slider-rotor can be independently controlled. The actuator achieved a maximum rotational speed of 163.1 RPM and a maximum linear speed of 41.4 mm/s, with a corresponding peak output torque and force of 236.1 mN·mm and 368.1 mN, respectively. A resolution measurements showed that the actuator can achieve an angular resolution of 1.02 mrad and a linear resolution of 53.8 µm.

Jiang Chen, Ying Xu, Jiantao Zhang et al.

Abstract The DC multi‐port converter's applications are increasing owing to its favourable features, including variable control mode, high power density, and bi‐directional power supply. On the other hand, the impedance interaction between each port of the electrolytic capacitor‐less DC multi‐port converter may generate an instability. To address the above mentioned problem, a method is proposed in this paper for reshaping the impedances of the energy storage converter by constructing a virtual impedance connected in parallel with the output impedance of the electrolytic capacitor‐less DC multi‐port converter. Furthermore, this paper introduces the stability criterion based on the unified impedance theory, which classifies a converter as either the bus current‐controlled converter or the bus voltage‐controlled converter. The proposed control approaches raise the magnitude of the output impedance of the electrolytic capacitor‐less DC multi‐port converter to satisfy the unified impedance theory criterion without modifying each port. The simulation results show that the proposed method is better than the traditional methods, and comprehensive experimental results are provided to validate the proposed methods.

Xiao Lei, Chunpeng Zhao, Qiaoliang Zhang et al.

Experimental methods, including mercury pressure, nuclear magnetic resonance (NMR) and core (water-oil) displacement, are used to examine the effects of high-multiple water injection (i.e. water injection with high injected pore volume) on rock properties, pore structure and oil displacement efficiency of an oilfield in the western South China Sea. The results show an increase in the permeability of rocks along with particle migration, an increase in the pore volume and the average pore throat radius, and enhanced heterogeneity after high-multiple water injection. Compared with normal water injection methods, a high-multiple water injection is more effective in improving the oil displacement efficiency. The degree of recovery increases faster in the early stage due to the expansion of the swept area, and the transition from oil-wet to water-wet. The degree of recovery increases less in the late stage due to various factors, including the enhancement of heterogeneity in the rocks. Considering both the economic aspect and the production limit of water flooding, it is recommended to adopt other technologies to further enhance oil recovery after 300 PV water injection.

Caitlin Ho, Thomas Looi, Glenn Maguire et al.

Surgical robotic tools are being developed for a variety of surgical procedures that are executed within small workspaces. Novel designs of miniaturized cable-actuated surgical tools for cleft palate repair have previously been developed. However, the behavior and significance of friction within these tools are largely unknown. A study was conducted to investigate the friction in a pulleyless 3 mm diameter wristed instrument. The wrist utilizes cable guide channels that allow for miniaturization at the cost of increased friction. An experimental rig was developed to measure friction within the wrist link mechanism when the tool is positioned at various pitch angles. A strong relationship between the cable tension and the tool’s pitch angle was found as a result of friction. The cable tension increased as the pitch angle approached extreme values (percent increases in the cable tension of 33% and 67.3% at a pitch of 90° and −90°, respectively). However, the resultant cable tension was below the failure strength of the cable, indicating that the design is feasible. The results of this study would be useful to those considering the design of miniature robotic surgical tools that are cable-driven. Significant tool reduction can be achieved by employing static guide channels for the cables, forgoing the use of additional moving components like pulleys while maintaining cable tension well within its break strength. Future work in the design and optimization of novel miniaturized wrist mechanisms should consider frictional effects and their impact on mechanism function.

Shahid Hussain, Young-Chon Kim

The larger battery capacities and the longer waiting and charging time of electric vehicles (EVs) results in low utilization of charging stations (CSs). This paper, proposes fuzzy logic weight based coordination (FLWC) scheme to enhance the utilization of CSs. Each EV has an associated uncertain information including stay time and the current state-of-charge (SoC). The fuzzy logic controller (FLC) analyze these inputs and determines a weight value. The proposed FLWC scheme then allocates CSs to the EVs according to the weight values. The proposed scheme is simulated for 100 EVs and 5 CSs using Matlab. The simulation result shows about 30% improvement in the average utilization of CSs as compared to first-come-first-serve (FCFS) based scheme.

Ying Zhu, Zhicong Wang, Xubin Guo et al.

Ecaterina Chelaru, Vasilica Dandea, Lvia Noroc et al.

Zhongwei Li, Yang Liu, Peng Qiu et al.

Abstract With the increase in inverter‐based renewable energy resources, the complexity and uncertainty of low‐carbon power systems have increased significantly. Deep reinforcement learning (DRL)–based approaches have been extensively studied for frequency control to overcome the limitations of traditional model‐based approaches. The goal of DRL‐based methods for primary frequency control is to minimise load shedding while satisfying frequency safety requirements, thereby reducing control costs. However, the vulnerabilities of DRL models pose new security threats to power systems. These threats have not been identified and addressed in the existing literature. Therefore, here, a series of vulnerability assessment methods are proposed for DRL‐based frequency control with a focus on the under‐frequency load shedding (UFLS) problem. Three adversarial sample production methods are designed with different optimisation directions: Q‐value‐based FGSM (Q‐FGSM), action‐based JSMA (A‐JSMA), and state‐action‐based CW (SA‐CW). Furthermore, combining the advantages of the above three attack methods, a hybrid adversarial attack algorithm is designed, Q‐value‐state‐action‐based mix (QSA‐MIX), to significantly affect the decision process of the DRL model. In case studies of the IEEE39 bus system, the proposed attack methods had a severe impact on system operation and control. In particular, the high attack transferability of the proposed attack algorithms in a black‐box setting provides further evidence that the vulnerability of current DRL‐based control schemes is prevalent.

L. V. Mostovenko, V. P. Beloglazov

THE RELEVANCE of the research topic is due to the existence of an environmental problem associated with harmful emissions into the atmosphere. The most highly efficient are electrostatic precipitators and fabric filters (~90-99.5% capture). Against the background of these devices, inertial one’s lag behind both in terms of their catching efficiency and the catching spectrum of the ash particle size distribution. The research carried out in the article is aimed at creating such an inertial apparatus that would have both minimal resistance and high efficiency. PURPOSE. Consider the possibility of reducing aerodynamic resistance by changing the design of the device, namely, by increasing the diameter of the inlet pipe in the inertial-vacuum ash collector. Consider a number of other ways to further reduce the aerodynamic drag of the apparatus. To identify the prospects and assessment of capital costs for the reconstruction of the ash collector. METHODS. When solving the problem, the method for calculating the dynamics of a dispersed flow in an inertial-vacuum ash collector, implemented by the MFD, was used. RESULTS. The article describes the relevance of the topic, considers the results of a numerical calculation. The calculation of the influence of boundary conditions, which include the flow rate at the inlet, thermal and hydraulic parameters of the flow of exhaust gases at the inlet to the ash catcher, in relation to the desired pressure drop across the apparatus, as well as the collection efficiency, was made. This article describes the process that results in a change in the hydraulic characteristics along the flow part of the IVAC. CONCLUSION. A change in the design of the apparatus leads to a decrease in the resistance of the IVAC, while these changes are extremely sensitive to the effect on the degree of purification. Calculations have shown that this method justifies itself in terms of reducing resistance. The pressure drops ranges from 279.8-1273 mm. water. pr. The convergence of the iterative calculation, taking into account the quality of the grid, provides flexibility, is achieved by fewer iterations, but the time spent on the calculation does not decrease.

Odin Foldvik Eikeland, Colin C. Kelsall, Kyle Buznitsky et al.

As variable renewable energy sources comprise a growing share of total electricity generation, energy storage technologies are becoming increasingly critical for balancing energy generation and demand. In this study, we modeled an existing thermal energy storage unit with estimated capital costs that are sufficiently low to enable large-scale deployment in the electric power system. Our analysis emphasizes the value of using such units to cost-effectively improve renewable energy dispatchability. This study modeled an existing real-world grid rather than simulating hypothetical future electric power systems. The storage unit coupled with a photovoltaic (PV) system was modeled with different storage capacities, whereas each storage unit size had various discharge capacities. The modeling was performed under a baseline case with no emission constraints and under hypothetical scenarios in which CO$_2$ emissions were reduced. The results show that power availability increases with increasing storage size and vastly increases in the hypothetical CO$_2$ reduction scenarios, as the storage unit is utilized differently. When CO$_2$ emissions are reduced, the power system must be less dependent on fossil fuel technologies that currently serve the grid, and thus rely more on the power that is served from the PV + storage unit. The proposed approach can provide increased knowledge to power system planners regarding how adding PV + storage systems to existing grids can contribute to the efficient stepwise decarbonization of electric power systems.

Tianhui Zhao, Jianxue Wang, Tao Ding et al.

Abstract With the fast development of wind power generation, many countries actively encourage wind power to trade in the medium‐long term market. However, the traditional forward contracts from medium‐long term markets are only suitable to conventional power generation enterprises, instead of wind farms. To facilitate the accommodation of wind power in the medium‐long term market, this paper focuses on two problems: The framework of the block‐based forward contract trading method and the procurement strategy of retailers with block‐based contracts. First, a novel block‐based forward contract is proposed, where the time attributes, that is, starting and ending time, and power during each period are stipulated. Aggregating all the block‐based forward contracts will naturally form the power supply curve, which can provide boundary information for wind farms when they take part in other markets. Secondly, a chance‐constrained procurement strategy model is proposed for retailers, where the uncertainty of wind power generation, constraints of block‐based contracts, and quota obligations of retailers are considered. Furthermore, a bilinear Benders decomposition algorithm with a variant of Jensen's inequalities is applied to solve the proposed model. Finally, experimental results demonstrate the effectiveness of the proposed model and method, which is computationally efficient in solving the chance‐constrained procurement strategy problem.

Sebastian Matthias Hell, Chong Dae Kim

Remaining-useful-life (RUL) prediction of Li-ion batteries is used to provide an early indication of the expected lifetime of the battery, thereby reducing the risk of failure and increasing safety. In this paper, a detailed method is presented to make long-term predictions for the RUL based on a combination of gated recurrent unit neural network (GRU NN) and soft-sensing method. Firstly, an indirect health indicator (HI) was extracted from the charging processes using a soft-sensing method that can accurately describe power degradation instead of capacity. Then, a GRU NN with a sliding window was applied to learn the long-term performance development. The method also uses a dropout and early stopping method to prevent overfitting. To build the models and validate the effectiveness of the proposed method, a real-world NASA battery data set with various battery measurements was used. The results show that the method can produce a long-term and accurate RUL prediction at each position of the degradation progression based on several historical battery data sets.