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

Senyong Fan, Weige Zhang, Yulu Li et al.

Sunil Subedi, Jongchan Choi, Yaosuo Xue

Traditionally, distribution system planning has focused on steady-state analyses, with limited consideration of dynamic behavior. However, as large or medium-scale inverter-based resources (IBRs), particularly grid-following (GFL) inverters in commercial or industry buildings, become more prevalent, understanding their dynamic impact is essential for grid planning and operation. This article presents an innovative deep-learning (DL)-approach using convolutional neural networks technique to model the GFL inverters. Developed from real grid-tied commercial IBR transient data, these dynamic DL models overcome proprietary constraints by requiring minimal knowledge of internal converter physics while maintaining high accuracy and flexibility. To demonstrate their applicability, the models were incorporated into GridLAB-D, an open-source, three-phase distribution analysis tool. This integration enables dynamic simulations of large-scale distribution networks with high IBR penetration stability analysis. Rigorous testing and validation, aligned with industry standards, confirmed the reliability and efficiency of this approach, paving the way for enhanced planning and operational assessments of modern power systems.

Min Li, Jie Cao

With the increasing penetration of renewable energy, power systems face escalating challenges in maintaining operational flexibility and enhancing renewable energy hosting capacity. Electric vehicle clusters, enabled by large-scale deployment and controllable charging and discharging capability, offer substantial potential as distributed flexibility resources. However, temporal mismatches between renewable generation and electric vehicle charging demand, along with insufficient incentive mechanisms and concerns about battery degradation, constrain effective participation in vehicle-to-grid coordination. This paper proposes a degradation-aware bi-level scheduling framework that represents electric vehicle clusters as shared mobile energy storage. At the user level, battery degradation is quantified through an equivalent full-cycle cost formulation, and degradation costs are embedded in charging and discharging decisions. At the aggregator level, a bi-level dynamic pricing and coordination mechanism is established: the upper level determines system-level scheduling and issues price signals, while the lower level captures heterogeneous price-responsive behaviours under operational constraints. To solve the resulting multi-objective optimization model, an improved nondominated sorting genetic algorithm is developed, and a weighted time-slot benefit allocation method based on the Shapley value is introduced to characterize time-varying marginal contributions and allocate benefits. Case studies show that the proposed framework reduces peak-period grid power purchases, mitigates load fluctuations, and increases renewable energy utilization to approximately ninety-six percent. The results indicate that degradation-aware coordinated aggregation of electric vehicle clusters provides an effective and scalable pathway to enhance renewable hosting capacity and support the low-carbon transition of power systems.

Xian-yong Xiao, Gui-shan Song, Wen-Xi Hu et al.

Voltage sags often disrupt the normal functioning of sensitive equipment and distributed generators (DGs), making voltage sag mitigation based on corresponding assessments crucial. Voltage sag characteristics, including voltage magnitude and sag duration, are affected by the low-voltage ride-through (LVRT) requirement of inverter-interfaced distributed generators (IIDGs). Moreover, voltage sags inversely affect the tripping behavior of IIDGs. However, inadequate analysis of the mutual effect of IIDGs and voltage sags degrades the performance of voltage sag assessment. To address this issue, the current study proposes a voltage sag assessment method considering the LVRT of IIDGs, where voltage sag characteristics are calculated in two modules. In the first module, given the nonlinear relationship between the fault current and terminal voltage of an IIDG in LVRT, voltage magnitude calculation is performed iteratively, where the computational cost is reduced by an adaptive partitioned iterative model. In the second module, the tripping behavior of different IIDGs is analyzed according to the ride-through time estimation model. Finally, the voltage sag assessment result is obtained by modifying voltage magnitude under different estimated trip behaviors. The effectiveness and reliability of the proposed method are validated by considering various test systems and IIDG penetration extents. The results demonstrate the superiority of the proposed voltage sag assessment method over traditional methods in terms of accuracy and efficiency.

Kah Chun Lau, Xiangbo Meng

While we are pursuing a fully electrified society, high-energy rechargeable batteries are undergoing intensive investigation. In this respect, atomic and molecular layer deposition (ALD and MLD) have been drawing increasing interest, due to their unmatched capabilities to precisely modify electrodes’ surfaces for better electrochemical performance. In this work, we reviewed the recent studies using ALD/MLD for interface engineering of several important electrode materials, including nickel (Ni)-rich metal oxide cathodes, silicon (Si), and lithium (Li) anodes in lithium-ion and lithium metal batteries. We particularly discussed the most promising coatings from these studies and explored the underlying mechanisms based on experiments and modeling. We anticipate that this work will inspire more studies using ALD/MLD as an important technique for securing new solutions for batteries.

Zhao Sun, Kun Lei, Louise R. Smith et al.

ABSTRACT Advanced oxygen carrier plays a pivotal role in various chemical looping processes, such as CO2 splitting. However, oxygen carriers have been restricted by deactivation and inferior oxygen transferability at low temperatures. Herein, we design an Fe–Ov–Ce–triggered phase‐reversible CeO2−x·Fe·CaO ↔ CeO2·Ca2Fe2O5 oxygen carrier with strong electron‐donating ability, which activates CO2 at low temperatures and promotes oxygen transformation. Results reveal that the maximum CO2 conversion and CO yield obtained with 50 mol% CeO2−x·Fe·CaO are, respectively, 426% and 53.6 times higher than those of Fe·CaO at 700°C. This unique multiphase material also retains exceptional redox durability, with no obvious deactivation after 100 splitting cycles. The addition of Ce promotes the formation of the Fe–Ov–Ce structure, which acts as an activator, triggers CO2 splitting, and lowers the energy barrier of C═O dissociation. The metallic Fe plays a role in consuming O2−lattice transformed from Fe–Ov–Ce, whereas CaO acts as a structure promoter that enables phase‐reversible Fe0 ↔ Fe3+ looping.

Sugunakar Mamidala, Pavan Kumar Y. V.

To encourage an eco-friendly environment and pollution-free transportation, most of the automobile industries are promoting electric vehicles. However, with the adoption of electric vehicles, various power quality problems are encountered mainly during vehicle battery charging. Thus, this research work focuses on power quality improvement in electric vehicle battery charging stations. In this article, a closed-loop battery current-controlled zeta converter with a PI controller is introduced to achieve quality power to charge electric vehicles. The proposed converter enhances the overall performance of the system by reducing voltage fluctuations, harmonic content, and frequency variations. Besides, this suggested closed-loop battery-controlled zeta converter improves the power factor and overall efficiency of the system. The converter provides a wide range of output with ripple-free current. In the proposed scheme, the vehicle battery current feedback to the PI controller generates the switching pulses, thereby generating the desired duty ratio to operate the converter to maintain a constant current. The entire system is implemented in MATLAB/Simulink and various power quality parameters namely voltage and current characteristics, active and reactive power characteristics, frequency, total harmonic distortion (THD), power factor, and efficiency are measured. To validate the usefulness of the proposed scheme, it is compared with conventional buck converter-based charging station and conventional zeta converter-based charging station. From the results, it is found that the proposed closed-loop battery current-controlled zeta converters charging station produce improved power quality characteristics over conventional methods. It achieved a voltage THD of 4.93%, current THD of 1.9%, power factor of 0.96, and efficiency of 91.8%, which are far better than the conventional buck and zeta models.

Shuhong Wu, Jingyu Zhou, Yihong Zhang et al.

Zesen Li, Xiaoyan Hu, Jing Shi et al.

Hao Zhang, Jingwei Zhang, Wenjie Chen et al.

Abstract A series of carbon nitride (CN) materials represented by graphitic carbon nitride (g‐C3N4) have been widely used in bioimaging, biosensing, and other fields in recent years due to their nontoxicity, low cost, and high luminescent quantum efficiency. What is more attractive is that the luminescent properties such as wavelength and intensity can be regulated by controlling the structure at the molecular level. Hence, it is time to summarize the related research on CN structural evolution and make a prospect on future developments. In this review, we first summarize the research history and multiple structural evolution of CN. Then, the progress of improving the luminescence performance of CN through structural evolution was discussed. Significantly, the relationship between CN structure evolution and energy conversion in the forms of photoluminescence, chemiluminescence, and electrochemiluminescence was reviewed. Finally, key challenges and opportunities such as nanoscale dispersion strategy, luminous efficiency improving methods, standardization evaluation, and macroscopic preparation of CN are highlighted.

Anamika Yadav, Rashmi Bareth, Matushree Kochar et al.

Abstract In this paper, Gaussian Process Regression (GPR)‐based models which use the Bayesian approach to regression analysis problem such as load forecasting (LF) are proposed. The GPR is a non‐parametric kernel‐based learning method having the ability to provide correct predictions with uncertainty in measurements. The proposed model provides an hourly and monthly load forecast for an Australian city and four Indian cities in the Maharashtra state. Twelve GPR models are trained with historical datasets including hourly load and environmental data. To evaluate the trained model, the actual and predicted load demand curve is plotted and mean average percentage error (MAPE) is calculated corresponding to different kernel functions of the GPR model. To the best of the author's knowledge, the prediction of load demand using GPR for Indian cities of Maharashtra state has been made for the first time. The calculated MAPE in LF is 0.15% for Australia and 0.002%, 0.209%, 0.077%, and 0.140% for Indian cities viz. Nasik, Bhusawal, Kolhapur, and Aurangabad, respectively. The test results illustrate that minimum MAPE in load prediction is obtained using the proposed model that is GPR with ‘Exponential’ kernel functions. Furthermore, the comparative analysis with the existing approaches confirms the dominance of the proposed model.

Moossa Khodadadi Arpanahi, Masoud Hajiakbari Fini, Abolfazl Nateghi

A new fault location method based on single-end measurements is proposed in this paper. The proposed method decomposes the fault location problem into two sub-problems and uses the voltage and current phasors of one of the line ends to solve the sub-problems. In the first iteration, an initial value is assumed for the fault location and then, based on the network equations, the first sub-problem calculates fault characteristics such as its voltage, current, and impedance which are fed into the second sub-problem as its inputs. Then, the second sub-problem updates the estimated fault location based on the received inputs. This approach is efficient and comprehensive method in the sense that it is not susceptible to the value of fault impedance, it is applicable for symmetrical and asymmetrical faults, transposed and untransposed lines, identical and non-identical circuits, and both short and long double circuit transmission lines. Finally, the method converges quickly in maximum three iterations although it is iterative. Numerous case studies by changing the line length, fault impedance, location of fault, line characteristics and noise level are carried out using distributed line model to verify the effectiveness of the proposed method.

Pengcheng Cai, Yang Mi, Haijun Xing et al.

Huan Zhang, Shengzhang Fu, Jianli Jiang

Roland Szabo, Radu-Stefan Ricman

This paper presents a method on how to compute the position of a robotic arm in the 2D and 3D spaces. This method is slightly different from the well-known methods, such as forward or inverse kinematics. The method presented in this paper is an optical method, which uses two video cameras in stereo vision configuration to locate and compute the next move of a robotic arm in space. The method recognizes the coordinates of the markers placed at the joints of the robotic arm using the two video cameras. The coordinate points of these markers are connected with straight lines. Around certain points, circles are drawn. From the tangent to the circles, a non-Cartesian (orthogonal) coordinate system is drawn, which is enough to compute the target position of the robotic arm. All of these drawings are overlaid on the live video feed. This paper also presents another method for calculating the stereo distance using the triangulation method. An alternative method is also presented when a non-Cartesian (orthogonal) 3D coordinate system is created, which is used to compute the target position of the robotic arm in the 3D space. Because the system is in a loop, it can make micro-adjustments of the robotic arm, in order to be exactly in the desired position. In this way, there is no need to make calibrations for the robotic arm. In an industrial system, there is no need to stop the production line, which can be a really big cost saver.

Huiling Wei, Jin Liu, Qinghua Lu et al.

Actively transitioning between clamping and grasping is a challenging problem for most manipulators with limited degrees of freedom. To overcome this problem, a cable-driven rigid–flexible combined manipulator capable of actively transitioning between clamping and grasping is proposed in this paper, which has a certain adaptability and compliance to achieve adaptive operation. First, the cable-driven unit and compliant unit of the cable-driven rigid–flexible combined manipulator are designed. Then, the sensitivity of the mechanism parameters is analyzed using the Monte Carlo method, and then the structure of the cable-driven rigid–flexible combined manipulator is optimized. After that, the force on the finger in two-point clamping mode is modelled using Newton’s second law. Furthermore, the input–output relationship modelling of the finger in envelope grasping mode is deeply analyzed using the principle of energy conservation. Finally, the stable grasping performance of the cable-driven rigid–flexible combined manipulator is verified using numerical simulation and physical prototype tests. The results show that the cable-driven rigid–flexible combined manipulator has good adaptability and compliance, which verifies the effectiveness and rationality of the design and modelling.

Yutaka Kaneko, Hiroyuki Nishida, Yoshiyuki Tagawa

The dielectric barrier discharge plasma actuator is a promising flow control device that uses surface discharge. The actuator generates an electrohydrodynamic force and Joule heating that contribute to the flow control. Thus, it is important to investigate the electrohydrodynamic and thermal effects on the air flow. To this end, the flow velocity field, density field, and surface temperature distribution induced by an alternating current dielectric barrier discharge plasma actuator were experimentally examined, adopting particle image velocimetry, the background oriented schlieren technique, and an infrared camera. These experiments were conducted for plate- and wire-exposed electrode plasma actuators to investigate the effect of the shape of the exposed electrode. It was confirmed that the topology of the discharge is different between the two types of plasma actuators. This results in a difference in the spatial distributions of the velocity and density fields between the two actuators. In particular, we clarified that there is an obvious difference in the peak position of the density and temperature distribution between the two actuators. We also confirmed that the difference in the spatial distribution of the vertical velocity makes the above difference.

Wen-Xuan Fu, Ping Zhou, Wei-Liang Guo et al.

As one of most advanced transduction techniques, electrochemiluminescence (ECL), such as that generated by tris(2,2′-bipyridyl)ruthenium (Ru(bpy)32+), has been extensively used in chemical sensing and analysis, but the reaction mechanism has not been fully resolved. Aiming at gaining insightful mechanistic information on the coreactant system involving (Ru(bpy)32+) and tri-n-propylamine (TPrA), herein we investigate the variation of thickness of ECL layer (TEL) with the concentration ratio of (Ru(bpy)32+) to TPrA (cRu/cTPrA) by ECL microscopy. Using carbon fiber as the working electrode, TEL was observed to grow with the increase of cRu/cTPrA remarkably. In conjunction with finite element simulations, the extension of ECL layer was rationalized to be associated with the incremental contribution of so-called “catalytic route”. This route offers an additional channel of generating remote light emission in solution, apart from surface-confined emission produced by the “oxidative-reduction route”. Given the quantitative analysis of coreactant-type analytes is often based on the calibration curve, namely a graph generated by plotting the measured light intensity of a series of standard solutions against their concentrations, the contribution of “catalytic route” particularly at a low concentration of analyte (equivalent to a relatively large cRu/cTPrA) is favorable to the analytical sensitivity. Moreover, the presence and absence of this route will result in a nonlinear and linear calibration curve, respectively, for example in the detection of TPrA and pyruvate. The results highlight the microwire-based imaging approach can provide insightful mechanistic information and help unveil the concentration dependence of measured ECL intensity for precise quantitative analysis.

Foad H. Gandoman, Adel El-Shahat, Zuhair M. Alaas et al.

Electric vehicle (EV) markets have evolved. In this regard, rechargeable batteries such as lithium-ion (Li-ion) batteries become critical in EV applications. However, the nonlinear features of Li-ion batteries make their performance over their lifetime, reliability, and control more difficult. In this regard, the battery management system (BMS) is crucial for monitoring, handling, and improving the lifespan and reliability of this type of battery from cell to pack levels, particularly in EV applications. Accordingly, the BMS should control and monitor the voltage, current, and temperature of the battery system during the lifespan of the battery. In this article, the BMS definition, state of health (SoH) and state of charge (SoC) methods, and battery fault detection methods were investigated as crucial aspects of the control strategy of Li-ion batteries for assessing and improving the reliability of the system. Moreover, for a clear understanding of the voltage behavior of the battery, the open-circuit voltage (OCV) at three ambient temperatures, 10 °C, 25 °C, and 45 °C, and three different SoC levels, 80%, 50%, and 20%, were investigated. The results obtained showed that altering the ambient temperature impacts the OCV variations of the battery. For instance, by increasing the temperature, the voltage fluctuation at 45 °C at low SoC of 50% and 20% was more significant than in the other conditions. In contrast, the rate of the OCV at different SoC in low and high temperatures was more stable.

Jian Gao, Mengxin Zhou, Xinyao Wang et al.

The oxygen reduction reaction (ORR) is of great importance for clean energy storage and conversion techniques such as fuel cells and metal–air batteries (MABs). However, the ORR is kinetically sluggish, and expensive noble metal catalysts are required. The high price and limited preservation of noble metal catalysts has largely hindered the wide application of clean power sources such as fuel cells and MABs. Therefore, it is important to prepare non-expensive metal catalysts (NPMC) to cut the price of the fuel cells and MABs for wide application. Here, we report the preparation of a Co₃O₄ carried on the N-doped carbon (Co/N-C) as the ORR NPMC with a facile Pharaoh’s Snakes reaction. The gas generated during the reaction is able to fabricate the porous structure of the resultant carbon doped with heteroatoms such as Co and N. The catalyst provides a high electrocatalytic activity towards ORR via the 4-e pathway with an onset and half-wave potential of 0.98 and 0.79 V (vs. RHE), respectively, in an electrolyte of 0.1 M KOH. The onset and half-wave potentials are close to those of the commercial Pt/C. This work demonstrates the promising potential of an ancient technology for preparing NPMCs toward the ORR.