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

Jianbo Yi, Yujie Gu, Ran Xu et al.

Abstract In recent years, bifacial solar panels are accelerating to replace single‐side PV devices in traditional PV power generation system due to their high utilisation rate and price advantages. This makes the stability and control strategy of grid‐connected bifacial PV systems (GCBPVS) to be different from the traditional method after it is connected to the power systems. This paper fully considers each detailed module in GCBPVS using virtual synchronous generator (VSG) technology and derives the small‐signal model of the fully grid‐connected (GC) system using the linearisation method of each sub‐module. Then, it analyses the small disturbance stability and oscillation mode characteristics of GCBPVS by combining the effects of partial system parameters change on eigenvalues. Especially for the key parameters that affect the control stability of the system, this paper proposes a novel global optimisation design method of key control parameters to reform the distribution of system eigenvalues and improve the stability of GCBPVS. Finally, case simulation and result analysis show that the accuracy of the above small‐signal model is very high and the related stabilisation control method is very effective. In addition, hardware‐in‐the‐loop (HIL) experiments demonstrate that the proposed control method has strong engineering practicability and is better suitable for application.

Dayoung Kim, Cheolhwan Song, Oh B. Chae

Recent advancements in lithium-metal-based battery technology have garnered significant attention, driven by the increasing demand for high-energy storage devices such as electric vehicles (EVs). Lithium (Li) metal has long been considered an ideal negative electrode due to its high theoretical specific capacity (3860 mAh g⁻¹) and low redox potential. However, the commercialization of Li-metal batteries (LMBs) faces significant challenges, primarily related to the safety and cyclability of the negative electrodes. The formation of lithium dendrites and uneven solid electrolyte interphases, along with volumetric expansion during cycling, severely hinder the commercial viability of LMBs. Among the various strategies developed to overcome these challenges, the introduction of artificial protective layers and the structural engineering of current collectors have emerged as highly promising approaches. These techniques are critical for regulating Li deposition behavior, mitigating dendrite growth, and enhancing interfacial and mechanical stability. This review summarizes the current state of Li-negative electrodes and introduces methods of enhancing their performance using a protective layer and current collector design.

Yuqi Wu, Zhengtian Li, Xiangning Lin et al.

The delayed operation of a zone-2 impedance relay for handling faults on the end-section of a protected line can exacerbate power system instability. To accelerate the trip of a zone-2 circuit breaker (CB), many accelerated trip (AT) schemes have been proposed for AC power grids. However, these schemes remain by their pre-fault operating conditions, tripping modes, fault resistance, and fault types. Considering these limitations, this paper presents a novel AT scheme based on open-switching traveling waves (TWs) generated by CB operation. First, characteristic differences in the oscillation period and wavefront polarity of the open-switching TWs generated by remote CB operation under internal, remote busbar, and external faults are analyzed. Then, an identification criterion for open-switching TWs utilizing the order and number of wavefront polarities is proposed, thereby forming a new AT scheme. Finally, based on the PSCAD/EMTDC software, the effectiveness, sensitivity, and reliability of the proposed AT scheme are verified. The proposed AT scheme can operate at high speed without being affected by pre-fault operating conditions, tripping modes, or fault types, and its ability to endure fault resistance reaches 300 Ω.

Zhiqiang HU, Yuanyu YE, Lingang YU et al.

In order to solve the problems of increased losses and reduced power supply quality caused by unbalanced three-phase loads, an automatic equalization method for three-phase load unbalance in low-voltage stations involving active loads is proposed. Based on the high-speed carrier technology of the power Internet of Things, the meter load data of the low-voltage station area is collected, and the load data is monitored and collected in real time. A three-phase load imbalance equalization control terminal is designed and the objective function is established. The pigeon swarm algorithm is used to solve the function to achieve automatic balancing control of three-phase load imbalance in the low-voltage station area, which has good control effects.

Dmitriy A. Martyushev, Inna N. Ponomareva, Vasiliy I. Chernykh et al.

Laboratory filtration experiments are employed to investigate effective well killing while minimizing its impacts on surrounding rocks. The novelty of this experimental study lies in the prolonged exposure of rock samples to the killing fluid for seven days, corresponding to the average duration of well workovers in the oilfields in Perm Krai, Russia. Our findings indicate that critical factors influencing the interactions between rocks and the killing fluid include the chemical composition of the killing fluid, the mineralogical composition of the carbonate rocks, reservoir pressure and temperature, and the contact time. Petrophysical analyses using multi-scale X-ray computed tomography, field emission scanning electron microscopy, and X-ray diffraction were conducted on samples both before and after the well killing simulation. The experiments were performed using real samples of cores, crude oil, and the killing fluid. The results from this study indicate that low-mineralized water (practically fresh water) is a carbonate rock solvent. Such water causes the dissolution of rock components, the formation of new calcite crystals and amoeba-like secretions, and the migration of small particles (clay, quartz, and carbonates). The formation of deep channels was also recorded. The assessment reveals that the change in the pH of the killing fluid indicates that the observed mineral reactions were caused by carbonate dissolution. These combined phenomena led to a decrease in the total number of voids in the core samples, which was 25% on average, predominantly among voids measuring between 45 and 70 μm in size. The change in the pore distribution in the bulk of the samples resulted in decreases in porosity of 1.8% and permeability of 67.0% in the studied core samples. The results from this study indicate the unsuitability of low-mineralized water as a well killing fluid in carbonate reservoirs. The composition of the killing fluid should be optimized, for example, in terms of the ionic composition of water, which we intend to investigate in future research.

Yao Wu, Biao Tang, Shuo Qiao et al.

In the domain of bionic walking control for biped robots, optimizing the parameters of the central pattern generator (CPG) presents a formidable challenge due to its high-dimensional and nonlinear characteristics. The traditional particle swarm optimization (PSO) algorithm often converges to local optima, particularly when addressing CPG parameter optimization issues. To address these challenges, one improved particle swarm optimization algorithm aimed at enhancing the stability of the walking control of biped robots was proposed in this paper. The improved PSO algorithm incorporates a spiral function to generate better particles, alongside optimized inertia weight factors and learning factors. Evaluation results between the proposed algorithm and comparative PSO algorithms were provided, focusing on fitness, computational dimensions, convergence rates, and other metrics. The biped robot walking validation simulations, based on CPG control, were implemented through the integration of the V-REP (V4.1.0) and MATLAB (R2022b) platforms. Results demonstrate that compared with the traditional PSO algorithm and chaotic PSO algorithms, the performance of the proposed algorithm is improved by about 45% (two-dimensional model) and 54% (four-dimensional model), particularly excelling in high-dimensional computations. The novel algorithm exhibits a reduced complexity and improved optimization efficiency, thereby offering an effective strategy to enhance the walking stability of biped robots.

Xue WANG, Lin LIU, Wendi LIU et al.

The power system, traditionally dominated by synchronous generators, is evolving into a new power system where virtual synchronous generators (VSGs) take the lead. This transition results in significant changes in the system's dynamic characteristics. Currently, most literature focuses on analyzing the dynamic behaviors of standalone or multi-machine grid systems based on an assumption of infinite power supply, with limited research on the dynamic characteristics of new power systems dominated entirely by VSGs. Therefore, this study first builds a model of a three-machine, nine-node system where VSGs are the primary controllers and conducts transient simulations using differential equations. Subsequently, the crisscross optimization (CSO) algorithm is employed to optimize the inertia delay in the new power system. A comparison is made between the optimized control system and the non-optimized system. The results demonstrate that the optimized system exhibits reduced oscillation amplitude and shorter adjustment times after disturbances occur. Through simulations, the validity of the conclusions is verified.

Minh Tran, Lukas Gabert, Tommaso Lenzi

Across different fields within robotics, there is a great need for lightweight, efficient actuators with human-like performance. Linkage-based passive variable transmissions and torque-sensitive transmissions have emerged as promising solutions to meet this need by significantly increasing actuator efficiency and power density, but their modeling and analysis remain an open research topic. In this paper, we introduce the sensitivity between input displacement and output torque as a key metric to analyze the performance of these complex mechanisms in dynamic tasks. We present the analytical model of sensitivity in the context of two different torque-sensitive transmission designs, and used this sensitivity metric to analyze the differences in their performance. Experiments with these designs implemented within a powered knee prosthesis were conducted, and results validated the sensitivity model as well as its role in predicting actuators’ dynamic performance. Together with other design methods, sensitivity analysis is a valuable tool for designers to systematically analyze and create transmission systems capable of human-like physical behavior.

Ao Yu, Nimanyu Joshi, Wei Zhang et al.

Fullerenes are widely applied in the field of ORR, OER, and HER due to their well-defined molecular structures, excellent electron affinity potential that can be used to regulate the electronic structures when composited with other materials, the π-π intermolecular self-assembly into super crystals, and the customizable chemical modifications including heteroatom doping, metal encapsulation, and functionalization. These advantages endow fullerene with a great number of derivates and composites. Many theoretical and experimental works are reported on electrocatalysts. To better understand the study progress, herein, we give a common review of the latest research. We first introduce the theoretical calculations of fullerenes and their derivates towards ORR, OER, and HER, aiming to give understandable reaction mechanisms and electrocatalytic active sites. Then, the experimental identification of the electrocatalytic performance was summarized. The experimental section is organized based on fullerene-based composites including fullerene/carbon composites, fullerene/sulfide composites, fullerene/LDH or metal composites, and fullerene molecular and its derivates including fullerene crystals, fullertubes, as well as endohedral fullerene. Finally, the challenges and opportunities for rational designing of electrocatalysts using fullerene as a precursor or additive are summarized and highlighted. The review not only points out the recent progress in fullerene application in electrocatalysts but also gives an in-depth insight into the materials design theoretically and experimentally that helps the future study directions.

Jia ZHU, Feng WANG, Yiquan LI et al.

As one of the important transformer protections, zero sequence differential protection has the advantages of high sensitivity and strong anti-interference ability. The comparison object of its protection criterion is the self-generated zero sequence current and neutral zero sequence current obtained by the sum of three phase currents on the side of the three-phase incoming line. The difference of saturation characteristics between the three phase incoming-line side CT and the neutral side NCT will cause errors of zero sequence current transmission. The zero sequence current waveform after CT transmission will produce distortion in different degrees, which leads to the generation of false differential current, and then causes the misoperation of zero sequence differential protection. To solve this problem, on the basis of an analysis of the magnitude and phase characteristics of zero sequence current on both sides after CT transmission under various working conditions, a Tanimoto similarity-based constraint scheme for transformer zero-sequence differential protection is proposed, and the effectiveness of the proposed constraint scheme is verified by simulation.

Yanhui XU, Yijia XU

In order to smooth the output power of wind farms and reduce the influence of wind power fluctuations on power grid, a hybrid energy storage system consisting of energy-based energy storage element electrolyzer and power-based energy storage element supercapacitor is adopted to smooth wind power fluctuations. Firstly, the energy storage output in a large number of time slots is analyzed by probability statistics, and the smoothing effect of wind power fluctuation is evaluated by the probability change of the grid-connected power fluctuation within the limit of wind power fluctuation, and the power at a given confidence level is taken as the rated power of the hybrid energy storage. On this basis, the hybrid energy storage power is decomposed by the adaptive sliding window algorithm considering the economy, and the rated capacity of the supercapacitor and the rated power of the electrolyzer are determined, so as to realize the capacity allocation which takes into account the economy and fluctuation stability effect. Secondly, based on the charging state of the supercapacitor, the rated power of the electrolytic cell and the overall power command of the energy storage system, the operation control strategy of the hybrid energy storage system is formulated. Finally, the simulations results show that this method can effectively reduce the fluctuation of wind power while realizing the power distribution and ensuring the normal operation of each energy storage module.

Edurne Jaime-Barquero, Yan Zhang, Nicholas E. Drewett et al.

Solid-state batteries represent a promising technology in the field of high-energy-density and safe storage systems. Improving the understanding of how defects form within these cells would greatly facilitate future development, which would be best served by applying nondestructive analytical tools capable of characterization of the key components and their changes during cycling and/or aging. Spatially offset Raman spectroscopy (SORS) represents a potentially useful technique, but currently there is a lack of knowledge regarding its use in this field. To fill this gap, we present an investigation into the use of simple defocused micro-SORS on systems constructed using typical components found within solid-state cells. By analyzing the constituents and the assembled system, it was possible to obtain depth profiling spectra and show that spectra may be obtained from layers which are normally obscured, demonstrating the technique’s potential for nondestructive chemical analysis of the subsurface. In this way, the results presented validate the potential of micro-SORS as a technique to develop to support future solid-state battery development, as well as the nondestructive battery analytical field.

Ning Zhou, Shaobu Wang, Junbo Zhao et al.

Abstract Observability and detectability analyses are often used to guide the measurement setup and select the estimation models used in dynamic state estimation (DSE). Yet, marginally observable states of a synchronous machine prevent the direct application of conventional observability and detectability analyses in determining the existence of a DSE observer. To address this issue, the authors propose to identify the marginally observable states and their associate eigenvalues by finding the smallest perturbation matrices that make the system unobservable. The proposed method extends the observability and detectability analyses to marginally observable estimation models, often encountered in the DSE of a synchronous machine. The effectiveness and application of the proposed method are illustrated on the IEEE 10‐machine 39‐bus system, verified using the unscented Kalman filter and the extended Kalman filter, and compared with conventional methods. The proposed analysis method can be applied to guide the selection of estimation models and measurements to determine the existence of a DSE observer in power‐system planning.

Junhao Lin, Yan Zhang, Shuangdie Xu

In response to the imbalance between power generation and demand, demand response (DR) projects are vigorously promoted. However, customers' DR behaviors are still difficult to be simulated accurately and objectively. To tackle this challenge, we propose a new DR behavioral learning method based on a generative adversary network to learn customers' DR habits. The proposed method is also extended to maximize the economic revenues of generated DR policies on the premise of obeying customers' DR habits, which is hard to be realized simultaneously by existing model-based methods and traditional learning-based methods. To further consider customers' time-varying DR patterns and trace the changes dynamically, we de-fine customers' DR participation positivity as an indicator of their DR pattern and propose a condition regulation approach improving the natural generative adversary framework to generate DR policies conforming to customers' current DR patterns. The proposed method is applied to hourly electricity price optimization to reduce the fluctuation of system aggregate loads. An online parameter updating method is also utilized to train the proposed behavioral learning model in continuous DR simulations during electricity price optimization. Finally, numerical simulations are conducted to verify the effectiveness and superiority of the proposed method.

Umut Yusuf Gündoğar, Sibel Zorlu Partal

In recent years, large tilt angles, uniform magnetic flux distributions, strong forces, and large torques for motors have increasingly become important for robotics, biomedical, and automotive applications that have multi-degrees of freedom (MDOFs) motion. Generally, one-degree of-freedom motors are applied in MDOF motion. These situations cause the systems to have very complex and large structures. In order to address these issues, a 2-DOF surface permanent magnet spherical motor with a new mechanical design for the movement of the rotor with a large tilt angle of ±45° was designed, simulated, produced and tested in this paper. The motor consisted of a 4-pole permanent magnet rotor and a 3-block stator with 18 coils. In this study, the mechanical structure of the proposed spherical permanent magnet motor surrounded the rotor with two moving parts to move at a large tilt angle of ±45° without using any mechanical components such as spherical bearings, joint bearings, and bearing covers. Thus, the tilt angle, force, and torque values of the proposed motor have been improved according to MDOF motion motors using spherical bearings, bearing covers, or joint bearings in their mechanical structures in the literature. Ansys Maxwell software was used for the design and simulation of the motor. Three-dimensional (3D) finite element method (FEM) analysis and experimental studies were carried out on the force, torque, and magnetic flux density distribution of the motor. Then, simulation results and experimental results were compared to validate the 3D FEM simulations results.

Naga Venkata Durga Vara Prasad Eluri, Pradipta Kishore Dash, Snehamoy Dhar

Abstract This study presents a novel approach using adaptive variational mode decomposition with detrended fluctuation analysis to detect the islanding disturbances for photovoltaic based DC micro grid. DC parameters are simple to estimate in comparison to AC profile. Thus DC parameters are recorded under islanding scenario, and processed through proposed adaptive variational mode decomposition which decomposes the signals into intrinsic mode functions. These segregated intrinsic mode functions are further selected optimally by choosing the significant weighted kurtosis index. This optimal selection (maximisation of weighted kurtosis index) is ensured by modified particle swarm optimisation in terms of number of modes (K) and penalty factor (σ). For detection and monitoring (D&M) accurate islanding scenario the significant intrinsic mode functions are subjected to detrended fluctuation analysis, where power exponent (α) values are utilised for correct detection (i.e. distinguishing islanding out of other grid contingencies by two and three dimensional scattering plots). The effectiveness of the proposed D&M for DC micro grid is established in this paper in terms of classification accuracy and relative computational time. The proposed DC side islanding D&M method is less complex (as compared to AC signals) to be implemented. Fastness and accuracy of proposed D&M is established and performed in MATLAB/Simulink platforms.

Xinyi Chen, Qinran Hu, Qingxin Shi et al.

As the penetration of renewable energy continues to increase, stochastic and intermittent generation resources gradually replace the conventional generators, bringing significant challenges in stabilizing power system frequency. Thus, aggregating demand-side resources for frequency regulation attracts attentions from both academia and industry. However, in practice, conventional aggregation approaches suffer from random and uncertain behaviors of the users such as opting out control signals. The risk-averse multi-armed bandit learning approach is adopted to learn the behaviors of the users and a novel aggregation strategy is developed for residential heating, ventilation, and air conditioning (HVAC) to provide reliable secondary frequency regulation. Compared with the conventional approach, the simulation results show that the risk-averse multi-armed bandit learning approach performs better in secondary frequency regulation with fewer users being selected and opting out of the control. Besides, the proposed approach is more robust to random and changing behaviors of the users.

Syed A. Raza, Jin Jiang

A benchmark distribution system is developed for investigating control and energy management of distributed generation (DG) at a residential level in the form of three single-phase microgrids. The benchmark is derived from a typical distribution network architecture with common parameters found in North-America systems including wiring specifications, line impedances and connection details for rooftop PV systems. This benchmark system can accommodate microgrids operating in both grid-connected and islanded modes. Within this benchmark, multiple single-phase DG sources located in different phases can be coordinated to form a dynamically balanced three phase system under different load and generation profiles in different phases. The coordination of DG sources in a particular phase is achieved through an intra-phase power management device, while mitigating loads and generation imbalance among all phases are done by an inter-phase power management scheme. It is expected that this benchmark system will facilitate investigation of impacts posed by proliferation of single-phase distributed generation devices and local storage systems in private residences. Three case studies have been carried out to demonstrate the versatility and effectiveness of this benchmark system.

Edwin Paccha-Herrera, Williams R. Calderón-Muñoz, Marcos Orchard et al.

Temperature prediction of a battery plays a significant role in terms of energy efficiency and safety of electric vehicles, as well as several kinds of electric and electronic devices. In this regard, it is crucial to identify an adequate model to study the thermal behavior of a battery. This article reports a comparative study on thermal modeling approaches by using a <inline-formula><math display="inline"><semantics><msub><mi>LiCoO</mi><mn>2</mn></msub></semantics></math></inline-formula> 26650 lithium-ion battery, and provides a methodology to characterize electrothermal phenomena. Three approaches have been implemented numerically—a thermal lumped model, a 3D computational fluid dynamics model, and an electrochemical model based on Newman, Tiedemann, Gu and Kim formulation. The last two methods were solved using ANSYS Fluent software. Simulations were validated with experimental measurements of the cell surface temperature at constant current discharge and under a highway driving cycle. Results show that the three models are consistent with actual temperature measurements. The electrochemical method has the lower error at 0.5C. Nevertheless, this model provides the higher error ( <inline-formula><math display="inline"><semantics><mrow><mn>1.3</mn></mrow></semantics></math></inline-formula><inline-formula><math display="inline"><semantics><mrow><msup><mrow></mrow><mo>∘</mo></msup><mi mathvariant="normal">C</mi></mrow></semantics></math></inline-formula>) at 1.5C, where the maximum temperature increase of the cell was <inline-formula><math display="inline"><semantics><mrow><mn>18.1</mn></mrow></semantics></math></inline-formula><inline-formula><math display="inline"><semantics><mrow><msup><mrow></mrow><mo>∘</mo></msup><mi mathvariant="normal">C</mi></mrow></semantics></math></inline-formula>. Under the driving cycle, all the models are in the same order of error. Lumped model is suitable to simulate a wide range of battery operating conditions. Furthermore, this work was expanded to study heat generation, voltage and heat transfer coefficient under natural convection.

Christophe Savard, Emiliia V. Iakovleva

Devices operating in complete energy autonomy are multiplying: small fixed signaling applications or sensors often operating in a network. To ensure operation for a substantial period, for applications with difficult physical access, a means of storing electrical energy must be included in the system. The battery remains the most deployed solution. Lead-acid batteries still have a significant share of this market due to the maturity of their technology. However, even by sizing all the system elements according to the needs and the available renewable energy, some failure occurs. The battery is the weak element. It can be quickly discharged when the renewable energy source is no longer present for a while. It can also be overloaded or subjected to high temperatures, which affects its longevity. This paper presents a suggested improvement for these systems, systematically adding extra devices to reduce excess charges and heat and allowing the battery use at lower charges. The interest of this strategy is presented by comparing the number of days of system failure and the consequences for battery aging. To demonstrate the interest of the proposed improvement track, a colored Petri net is deployed to model the battery degradation parameters evolution, in order to compare them.