Voltage Stability Research Articles

High voltage determination and stabilization for collinear laser spectroscopy applications.

Fast beam collinear laser spectroscopy is the established method to investigate nuclear ground state properties such as the spin, the electromagnetic moments, and the charge radius of exotic nuclei. These are extracted with high precision from atomic observables, i.e., the hyperfine splitting and the isotope shift, which become possible due to a large reduction of the Doppler broadening by compressing the velocity width of the ion beam through electrostatic acceleration. With the advancement of experimental methods and applied devices, e.g., to measure and stabilize the laser frequency, the acceleration potential became the dominant systematic uncertainty contribution. To overcome this, we present a custom-built high-voltage divider, which was developed and tested at the German metrology institute, and a feedback loop that enabled collinear laser spectroscopy to be performed at a 100-kHz level. Furthermore, we describe the impact of field penetration into the laser-ion interaction region. This affects the determined isotope shifts and hyperfine splittings if Doppler tuning is applied, i.e., the ion beam energy is altered instead of scanning the laser frequency. Using different laser frequencies that were referenced to a frequency comb, the field penetration was extracted laser spectroscopically. This allowed us to define an effective scanning potential to still apply the faster and easier Doppler tuning without introducing systematic deviations.

LaMnO3-Type Perovskite Nanofibers as Effective Catalysts for On-Cell CH4 Reforming via Solid Oxide Fuel Cells.

CH4 has become the most attractive fuel for solid oxide fuel cells due to its wide availability, narrow explosion limit range, low price, and easy storage. Thus, we present the concept of on-cell reforming via SOFC power generation, in which CH4 and CO2 can be converted into H2 and the formed H2 is electrochemically oxidized on a Ni-BZCYYb anode. We modified the porosity and specific surface area of a perovskite reforming catalyst via an optimized electrostatic spinning method, and the prepared LCMN nanofibers, which displayed an ideal LaMnO3-type perovskite structure with a high specific surface area, were imposed on a conventional Ni-BZCYYb anode for on-cell CH4 reforming. Compared to LCMN nanoparticles used as on-cell reforming catalysts, the NF-SOFC showed lower ohmic and polarization resistances, indicating that the porous nanofibers could reduce the resistances of fuel gas transport and charge transport in the anode. Accordingly, the NF-SOFC displayed a maximum power density (MPD) of 781 mW cm-2 and a stable discharge voltage of around 0.62 V for 72 h without coking in the Ni-BZCYYb anode. The present LCMN NF materials and on-cell reforming system demonstrated stability and potential for highly efficient power generation with hydrocarbon fuels.

Virtual inertia control of distribution grids under automobile charging and discharging load uncertainty

Abstract Automobiles with unstable charging and discharging loads usually have unstable power, frequency, and other parameters of the distribution network. Therefore, a virtual inertia control strategy is proposed to enhance the distribution network’s stability and improve the grid’s voltage quality. This method can enhance the inertia control capability of the grid by incorporating the sag coefficient and SOC control, which in turn achieves the purpose of improving the grid’s reliability. The results show that changing the sag coefficient can enhance the voltage stability to reduce the impact of the battery while incorporating the SOC inertia coefficient control, the distribution grid operation will be more stable, and the power quality will be higher. The new method enhances the stability of voltage load to a certain extent and lays the foundation for the subsequent virtual inertia control technology.

A 5 V Ultrahigh Energy Density Lithium Metal Capacitor Enabled by the Fluorinated Electrolyte

Lithium metal capacitor (LMC), incorporating a redox-type lithium metal anode and a capacitive-type carbon cathode, delivers a combination of high energy and power characteristics, which is regarded as a promising electrochemical energy storage system. However, the unstable interface stability of lithium anode and the unclear capacitive mechanism of carbon cathode seriously restrict the advancement of LMC. Herein, an all-fluorinated electrolyte with high voltage stability has been designed for engineering 5 V LMC. It is noticed that a high-quality LiF-rich solid electrolyte interphase derived from all-fluorinated electrolyte effectively improves the interfacial stability of lithium metal anode, boosting the reversible Li plating/stripping behavior and suppressing dendrite growth. Moreover, analyzed by the thermodynamic perspective, the stable PF6−(FEC)2(FEMC)4 configuration with the lowest solvation energy mainly exists in the all-fluorinated electrolyte, which reveals that the suitable pore size distribution (1.3–4.6 nm) can ensure the strong adsorption/desorption process. Endowed by the all-fluorinated electrolyte, the established 5 V LMC paired with an optimized porous carbon sheet cathode manifests excellent electrochemical performances with an ultrahigh energy density of 537.6 Wh kgcathode−1 and a large power density of 17500 W kgcathode−1. This elaborate work affords in-depth insights based on fluorinated electrolyte strategy into the fabrication guidance of LMC.

Research on new energy control optimization scheme based on dynamic voltage stability index

Research on new energy control optimization scheme based on dynamic voltage stability index

Power and voltage stability analysis of electric vehicle distribution network considering virtual power plants

Power and voltage stability analysis of electric vehicle distribution network considering virtual power plants

Enhancing voltage stability through wavelet-fuzzy control of hydrogen flow in OC-PEM fuel cell

Open cathode proton exchange membrane fuel cells (OC-PEM fuel cells) serve as electricity generators, utilizing hydrogen as an input source. While effective for fixed loads like residential applications, challenges arise in dealing with output voltage fluctuations caused by rapid load changes. These fluctuations not only impact fuel cell performance but also introduce instability in the supplied power. To solve this issue, the study proposes an innovative hydrogen flow control system employing a feedforward wavelet- fuzzy method. The primary goal of this control system is to enhance fuzzy control performance using wavelets, mitigating signal fluctuations and achieving optimal stability in fuel cell output voltage under constant load conditions. Wavelet functions act as filters on the fuzzy control input, minimizing fluctuations and refining the entire process. Additionally, a feedforward system is incorporated to maintain hydrogen flow at the set point value. The proposed control system is implemented on a validated model using experimental data. Performance analysis reveals that the proposed method effectively stabilizes voltage by accelerating the recovery time from disturbances.

Thermal stability of TiN gate electrode for 4H-SiC MOSFETs and integrated circuits

In this research, the thermal stability of single-stage amplifiers based on a 4H-SiC MOSFET with a TiN gate electrode was investigated. The results show that after 100 h aging at 400 °C in N2 ambient, the amplifier maintained good performance with stable voltage gain. The thermal stability of the amplifier is attributed to the stability of Ni/Nb/4H-SiC source/drain ohmic contact, implanted load resistor, and MOS structure with the TiN gate electrode. The results obtained from the 4H-SiC MOS structure show that the interface trap density at the SiO2/SiC decreases during the aging process. While the gate leakage current of the capacitor based on the Al gate electrode increases, it remains stable in structures with TiN gate electrodes after 100 h aging. The results obtained in this study indicate that TiN is promising for the gate electrode of 4H-SiC MOSFETs for high-temperature applications.

Queen honey bee migration (QHBM) optimization for droop control on DC microgrid under load variation

Transmission line impedance in DC microgrids can cause voltage dips and uneven current distribution, negatively impacting droop control and voltage stability. To address this, this study proposes an optimization approach using heuristic techniques to determine the optimal droop parameters. The optimizcv ation considers reference voltage constraints and virtual impedance at various load conditions, particularly resistive. The optimization problem is addressed using two techniques: queen honey bee migration (QHBM) and particle swarm optimization (PSO). Simulation results show that QHBM reaches an error of 0.8737 at the fourth iteration. The QHBM and PSO algorithms successfully optimized the performance of the DC microgrid under diverse loads, with QHBM converging in 5 iterations with an error of about 0.8737, and PSO in 40 iterations drawn error is 0.9 while keeping the current deviation less than 1.5 A and voltage error less than 0.5 V. The deviation of current control and virtual impedance values are verified through comprehensive simulations in MATLAB/Simulink.

Coordinated voltage control for large-scale wind farms with ESS and SVG based on MPC considering wake effect

The wake effect reduces the wind speed at downstream wind turbines (WTs), making it necessary for the central controller to collect wind power generation data from each WT. However, wind farms (WFs) face a more complex problem in maintaining the voltage stability at the WT terminal while following the transmission system operator (TSO) instructions due to the information collection as well as the possible data loss during transmission. Therefore, this study proposes a coordinated control method for WTs and multiple power sources based on model predictive control under wake disturbance conditions, aiming to reduce the average voltage deviation in WT terminals and go close to the rated voltage and ensure effective compliance with TSO commands in large-scale WFs. Accordingly, the Jensen wake model was utilized to accurately calculate the available active and reactive power limits for each WT. Energy storage systems and static Var generators were modeled to coordinate and maintain the voltage in all WT terminals within the feasible range, providing peak shaving and valley filling support to reduce wind energy waste and shortfall, thereby enhancing the economic and operational reliability of WF. Further, the effectiveness of the proposed method was validated in MATLAB/Simulink.

Optimal planning and partitioning of multiple distribution Micro-Grids based on reliability evaluation.

Power system researcher have turned to Micro-Grids (MG) for higher reliability, greater flexibility, lower operating costs and losses, and lower CO2 emissions at the distribution system. This paper presents a single-level stochastic optimization framework for planning and partitioning of a distribution system including Multiple Micro-Grids (MMGs). The main objective is to minimize the total cost of the system including investment, operation, total losses and reliability costs of the distribution network. The proposed model takes into account the viewpoints of MG owners and distribution system operators, simultaneously. The voltage stability index is introduced to identify the optimal site of MG investment. To deal with uncertainties caused by renewable generations, the Firefly Algorithm (FA) and probability-tree method is used to create various operation scenarios of Photo-Voltaic (PVs) and Wind Turbines (WTs). This model is solved through the genetic algorithm in MATLAB, and to evaluate its effectiveness, numerical studies have been carried out on the experimental IEEE distribution network with four specified locations for investing MGs and seven Tie Switches (TS) for network partitioning. Simulation results reveal that optimal locations for MG investment are determined in such a way all MGs connect to the buses near the beginning of the feeder and as a result, load point reliability is improved, total active power losses are reduced, and the energy program becomes more optimized.

Energy efficiency and electrochemical characteristic assessment of PEMFC-supercapacitor hybridization via railway profile

Electric trains equipped with efficient electric motors and powered by high-capacity hydrogen fuel cells are a choice of the global transportation industry to accelerate the global transition to a low-carbon transportation system. The operation of distinct vehicle types in varying geographical regions is characterized by unique features. Concurrently, the continually fluctuating demand for electricity necessitates the utilization of fuel cells in conjunction with energy storage devices. Thus, this study centers on examining the role of the PEMFC-supercapacitor direct hybridization system within the authentic driving profile of the subway in the Bangkok metropolitan region. The supercapacitor within the hybridization system serves as an energy management device, enhancing the durability of fuel cells when subjected to diverse load demands associated with train propulsion. In order to validate this hypothesis, an MRT (Mass Rapid Transit) protocol was formulated to emulate and serve as the load demand for the investigation, and then the PEMFC-supercapacitor direct hybridization system was operated using the created profile. Subsequently, the hybridization system undergoes electrochemical characterizations and fuel cell performance tests for diagnostic purposes. Empirical findings validated that the supercapacitor operates as a filter, generating a stable voltage response to varying load requirements, and possesses the capability to assimilate energy originating from regenerative braking. The integration of supercapacitors in stabilizing the operational parameters of proton exchange membrane fuel cells (PEMFCs) has markedly prolonged their operational lifespan. This assertion is substantiated by voltage signal analysis, which demonstrated a negligible increase in surface resistance of merely 0.23%, as depicted by Nyquist plots. Furthermore, cyclic voltammetry revealed that the system attained a peak electrochemical surface area (ECSA) of 0.0089 (106 cm2/mg of Pt). The information presented in this article constitutes data that has been minimally explored in existing research. Specifically, the study concentrates on the practical driving pattern of electric trains. Consequently, experimental results were deemed advantageous for the advancement of heavy-duty electric vehicles.

Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studies

AbstractElectric distribution networks increasingly host distributed energy resources based on power electronic converter (PEC) toward active distribution networks (ADN). Despite advances in computational capabilities, electromagnetic transient models are limited in scalability because of their reliance on exact data about the distribution system and each of its components. Similarly, the use of the DER_A model, which is intended to examine the combined dynamic behavior of many DERs, is limited by the difficulty in parameterization. There is a need for improved dynamic models of DERs for use in large power system simulations for stability analysis. This paper proposes an aggregate model‐free, data‐driven approach for deriving a dynamic partitioned model (DPM) of ADNs. Detailed residential distribution feeders were first developed, including PEC‐based DERs and composite load models (CMLDs), from which the aggregated DPM was derived. The performance was evaluated through various case studies and validated against the detailed ADN model and state‐of‐the‐art DER_A model with CMLD. The data‐driven DPM achieved a of over 90%, accurately representing the aggregated dynamic behavior of ADNs. Furthermore, the DPM significantly accelerated the simulation process with a computational speedup of 68 times compared to the detailed ADN and a 3.5 times speedup compared to the DER_A CMLD model.

Enhancing Economic Operation and Planning of Power Systems through Artificial Intelligence: Implementation of Optimal Power Flow in Chennai Utility Bus System

The aim of this paper is to integrate Artificial Intelligence (AI) into Economic Operation and Planning (EOP) methodologies of power systems, specifically by implementing an Optimal Power Flow (OPF) optimization method in the Chennai Utility Bus System. Many traditional approaches to optimize power generation and planning are inherently limited and many of these limitations can be overcome by the use of Artificial Intelligence (AI) techniques. Herein, we have used the AI powered optimization algorithms such as Multi Objective Particle Swarm Optimization (MOPSO) and Multi Objective Genetic Algorithm (MOGA) to increase the efficiency in economical ranking and also grid planning. Implementation of AI techniques in Chennai utility bus system and also evaluating it in real time using Multi Objective Particle Swarm Optimization, Multi Objective Genetic Algorithm, Newton Raphson method and their results are compared. These AI-based methods aim to reduce operation costs, minimize power loss and improve voltage stability as well as minimizing deviation of voltages in order to increase the efficiency. Future work will expand the use of these techniques to more intricate systems, such as the Indian utility 146-bus system to validate their effectiveness, in real world applications.

Improving islanded distribution system stability with adaptive decision-making framework

Abstract In an integrated distribution system incorporating distributed generation (DG), various technical challenges must be addressed when the grid becomes disconnected and transforms into an islanded system. The main focus in such circumstances revolves around ensuring the stability of the islanded network. This study presents an advanced decision-making framework for supporting islanded networks by integrating metaheuristic Black Widow Optimization (BWO) and the rate of change of the voltage stability index (RoCVSI). The Rate of Change of the Voltage Stability Index (RoCVSI) detects instability in islanded networks by continuously monitoring rapid changes in the voltage stability margin. Upon identifying potential instability, an advanced decision-making strategy utilizing the Black Widow Optimization (BWO) algorithm is deployed. BWO generates multiple load-shedding scenarios and evaluates their impact on system stability, iteratively refining the solutions through processes similar to selection and cannibalism in black widow spiders. The optimal load-shedding strategy is then implemented to selectively shed specific loads, thereby reducing demand and enhancing island stability. The proposed scheme’s effectiveness for islanded network stability is assessed by extensively analyzing the IEEE 33-bus system. The efficiency of the proposed approach is confirmed through a comparative analysis, with results indicating the better efficiency of the proposed method in the islanded network.

Solution-processed 10 nm thick ferroelectric polymer film on a TiO2 nanolayer for flexible nonvolatile memories

Poly(vinylidene fluoride)-based ferroelectric polymers, known for their exceptional flexibility, cost-effectiveness, and ease of processing, have garnered significant attention in the field of nonvolatile data storage. However, a persistent challenge lies in their elevated driving voltage and subpar thermal stability, leading to excessive power consumption and restricted operational conditions. Herein, we propose a flexible ferroelectric random access memory (FeRAM) based on a ceramic/polymer bilayer consisting of a solution-processed ferroelectric poly(vinylidene fluoride-trifluoroethylene) [P(VDF-TrFE)] nanofilm on top of a TiO2 nanolayer. The polarized Fourier transform infrared spectroscopy spectra and piezoresponse force microscopy phase signals demonstrate that the surface effect of the underlying TiO2 induces a consistent dipole orientation along the out-of-plane direction in the P(VDF-TrFE) nanofilm. These aligned dipoles in the P(VDF-TrFE) can be efficiently switched by a low driving voltage of 5 V while maintaining a high thermal stability exceeding 100 °C. Furthermore, the FeRAM based on the TiO2/P(VDF-TrFE) bilayer exhibits a remarkable storage density of approximately 60 GB in.–2, coupled with exceptional flexibility, high transparency, and superior read/write durability. These outstanding performances indicate that the TiO2/P(VDF-TrFE) bilayer holds significant potential for applications in high-density information storage within flexible electronics.

Gel polymer electrolytes based on compound cationic additives for environmentally adaptive flexible zinc-air batteries with a stable electrolyte/zinc anode interface

With the rapid development of flexible wearable technology, there is an urgent need for the exploitation of flexible and sustainable energy storage devices. Flexible zinc-air battery (ZABs) have attracted extensive attention from researchers due to their high theoretical energy density, abundant raw material and environmental friendliness. However, there is no more effective strategy to solve the problems of dendrite growth and by-products formation on the zinc anode surface of flexible ZABs in a strong alkaline environment. Herein, the PMA-HLx hydrogels based on chitosan quaternary ammonium salt (HACC) and La3+ as compound cationic additives are prepared as gel polymer electrolytes (GPEs) for flexible ZABs. The optimal PMA-HL0.02 GPE shows admirable interfacial adhesion and favorable ionic conductivity of 130.43 mS cm−1. Meanwhile, the assembled flexible ZAB exhibits excellent electrochemical performance and long cycle life, as well as a stable charge-discharge voltage gap at different bending angles, and still has favorable power densities of 113.2 mW cm−2 and 93.65 mW cm−2 at -20°C and 80°C, respectively. Therefore, this synthesis strategy of GPEs based on compound cationic additives provides a useful reference for the development of flexible ZABs with environmental adaptability and interfacial stability in alkaline electrolyte environment.

An improved particle swarm optimisation algorithm for optimum placement and sizing of biogas-fuelled distributed generators for seasonal loads in a radial distribution network

Optimal allocation is critical for effective planning and operation of grid connected distributed generator(s) (DGs) subject to efficient optimisation approach(es). In this paper, an improved particle swarm optimisation (IPSO) algorithm based on weighted randomised acceleration coefficients and adaptive inertia weight for dynamic movement of the particles towards an optimal solution is proposed. The technique is expected to determine optimal placement, sizing and power factor of biogas-fuelled distributed generators (B-DGs such as internal combustion engine (ICE) and fuel cells (FC)) in a radial distribution network. The proposed IPSO is applied to simultaneously optimise three technical objectives namely total active power loss (TAPL), voltage deviation (VD) and voltage stability index (VSI) considering load growth and seasonal voltage dependence. The proposed IPSO is validated using an IEEE 33 bus radial distribution network to evaluate its effectiveness through various combinations of B-DGs for different scenarios and cases with a maximum of 3 B-DGs. Some of the key findings indicate that operating 3 ICEs at optimal power factor reduces TAPL by 93.52 %, reduces VD by 99.62 % and improves VSI by 23.32 % compared to 61.80 % TAPL reduction, 94.77 % VD reduction and 17.89 % VSI improvement for 3 FCs operating at unity power factor. The proposed IPSO gives better results than the standard PSO in terms of solution quality, convergence speed and statistical results. It is also perceived to be better compared to most of the recent state-of-the-art optimization algorithms found in literature.

Effects of Co3O4 modified with MoS2 on microbial fuel cells performance

In this study, Co3O4@MoS2 is prepared as anodic catalytic material for microbial fuel cells (MFCs). As the mass fraction of MoS2 is 20%, the best performance of Co3O4@MoS2 composite catalytic material is achieved, and the addition of MoS2 enhances both the electrical conductivity and catalytic performance of the composite catalyst. Through the structural characterization of Co3O4@MoS2 composite catalytic material, nanorod-like Co3O4 and lamellar MoS2 interweaved and stacked each other, and the agglomeration of Co3O4 is weakened. Among the four groups of single-chamber MFCs constructed, the Co3O4@MoS2-MFC shows the best power production performance with a maximum stable output voltage of to 539 mV and a maximum power density of up to 2221 mW/m2. Additionally, the ammonia nitrogen removal rate of the MFCs loaded with catalysts is enhanced by about 10% compared with the blank carbon cloth MFC. Overall, the findings suggest that Co3O4@MoS2 composite catalysts can significantly improve the performance of MFCs, making them more effective for both energy production and wastewater treatment.

Can Aqueous Na2SO4-Based Neutral Electrolyte Increase Energy Density of Monolithic Wood Biochar Electrode Supercapacitor?

The performance of supercapacitors is significantly influenced by both the nature and the concentration of the electrolyte employed. This study investigates the impact of a neutral electrolyte on the electrochemical properties of the maple-derived monolithic wood biochar (MWB)–sodium sulfate (Na2SO4) supercapacitor. The goal is to determine if a neutral electrolyte, in this case Na2SO4, can increase the supercapacitor energy density compared to a previous study employing a KOH electrolyte. Starting from examining the ion sizes and conductivities of salt species in KOH and Na2SO4 electrolytes, the difference in voltage window, measured specific capacitance, and resistance are discussed. By switching the electrolyte from 4 M KOH to 0.5/1 M Na2SO4, the voltage stability window was extended from 0.8 V to 1.4 V. For 1 M Na2SO4, the supercapacitor attains a specific capacitance of 46 F/g at 5 mA/g, accompanied by an energy density of 12.5 Wh/kg and a maximum power density of 300 W/kg. The MWB electrode, derived from naturally abundant wood, when combined with the non-toxic Na2SO4 electrolyte, offers an environmentally friendly and cost-effective energy storage solution. With a prolonged lifetime and minimal maintenance requirements, MWB-Na2SO4 supercapacitors emerge as a promising choice for diverse applications.