Stability Of System Research Articles

Assessment of the Renewable Energy Consumption Capacity of Power Systems Considering the Uncertainty of Renewables and Symmetry of Active Power

The rapid growth of renewable energy presents significant challenges for power grid operation, making the efficient integration of renewable energy crucial. This paper proposes a method to evaluate the power system’s capacity to accommodate renewable energy based on the Gaussian mixture model (GMM) from a symmetry perspective, underscoring the symmetrical interplay between load and renewable energy sources and highlighting the balance necessary for enhancing grid stability. First, a 10th-order GMM is identified as the optimal model for analyzing power system load and wind power data, balancing accuracy with computational efficiency. The Metropolis–Hastings (M-H) algorithm is used to generate sample spaces, which are integrated into power flow calculations to determine the maximum renewable energy integration capacity while ensuring system stability. Short-circuit ratio calculations and N-1 fault simulations validate system robustness under high renewable energy integration. The consistency between the results from the M-H algorithm, Gibbs sampling, and Monte Carlo simulation (MCS) confirms the approach’s accuracy.

Large‐signal stability analysis for hybridized vehicular power supply systems of rolling stocks

AbstractHybridized vehicular power supply (HVPS) are acquiring widespread adoption in various applications such as providing power for passenger or heavy‐duty electric vehicles, more‐electric ships, electrified rolling stocks, and more. Stability analysis is a critical issue for HVPS, but it presents significant challenges due to their prominent high‐dimensional and nonlinear characteristics. This paper presents a large‐signal stability analysis scheme for HVPS of rolling stocks, enabling the assessment of system stability under sudden load changes. Based on the state‐space averaging method, a mathematical model for the large‐signal behavior of the system is established. Subsequently, the small‐signal stability parameter range of the system is determined by analyzing the eigenvalues of the Jacobian matrix. To further analyze the stability of the system during large‐signal disturbances, a nonlinear decoupling transformation approach is employed to decompose the original high‐order state equations into multiple lower‐order equations. For the decoupled lower‐order subsystems, their stability is analyzed using phase portrait, and the region of attraction (ROA) is determined using the inverse trajectory method. Based on the stability analysis results, the controller is enhanced to bring the points outside the ROA back within it, thereby mitigating the transient instability phenomenon of the system. The effectiveness of the proposed method was demonstrated using two case studies.

Financial intermediation and informational efficiency: Predicting business cycles

Theory posits that financial intermediation (FI) spurs economic growth and supports financial system stability by reducing informational asymmetries and agency problems. Most of this literature focuses on bank lending and has limited success in capturing changes in macroeconomic aggregates. We consider a large set of different financial intermediaries to show that aggregate FI assets contain leading information about real GDP, investment, consumption, industrial production, and unemployment. Bank and shadow bank assets alone contain only limited information about future states of the economy. Overall, FI improves informational efficiency of the markets by providing transparent leading signals of the future economic conditions.

Plane mirror-optical path coupling noise in telescope off-axis system dimensional stability measurement

The dimensional stability of the off-axis optical system affects its optical performance significantly and may even lead to its failure. Here, we report a heterodyne interferometry technology to measure the telescope’s dimensional stability. In this method, the standard plane mirror, which reflects the measurement laser, is a critical structural component. Additionally, it is one of the primary sources of the noise. The study focuses on the impact of the standard plane mirror’s positional misalignment instability on optical path noise. A mathematical model was established to depict the effects of mirror misalignment instability on the optical path, and experiments were conducted to decouple the noise. The results of the experiment show that the standard plane mirror introduces approximately 1nm/Hz1/2 at 10 mHz of optical path noise into the off-axis system, and the dimensional stability of the off-axis system is about 6.23nm/Hz1/2 at 10 mHz.

Distributed control and passivity‐based stability analysis for time‐delayed DC microgrids

AbstractFor cooperation among distributed generations in a DC microgrid (MG), distributed control is widely applied. However, the delay in distributed communication will result in steady‐state bias and the risk of instability. This paper proposes a novel distributed control for time‐delayed DC MGs to achieve accurate current proportional sharing and weighted average voltage regulation. Firstly, by utilizing an advanced observer based on the PI consensus algorithm, the steady‐state bias problem is addressed. Then, using the passivity theory, stability analysis is conducted to reveal the principle of system instability caused by communication delay. On this basis, to offset the adverse effects of communication delay on the system stability, scattering transformation is introduced in the observer‐based distributed control. Moreover, considering the potential delay from the measurement stage in real‐life scenarios, the sufficient condition of the system stability is concluded by constructing the Lyapunov–Krasovskii functional. Finally, the performance of the proposed control and conclusions of stability analysis are verified by hardware‐in‐loop tests.

LaCuMnOx perovskite activating persulfate for the degradation of bisphenol A: excellent tolerance to hypersaline environment

AbstractBackgroundLaCuMnOx (LCMO) perovskite was designed as an effective catalyst to activate peroxydisulfate (PDS) to remove bisphenol A (BPA) in hypersaline wastewater.ResultsIn the LCMO/PDS system, BPA (10 mg/L) was removed completely and the mineralization degree reached 74.9% in the presence of 0.12 g/L catalyst and 1.2 mM PDS. The BPA removal efficiency was still almost 100% even after five cycles. Metal ion leakage also indicated the stability of the catalytic system. •OH, SO4•−, 1O2, and O2•− all contributed to BPA removal, and O2•− accounted for the greatest contribution. The presence of oxygen vacancies (Vo··) on the surface of the catalyst was important for PDS activation and the formation of active species. In addition, the system could still maintain outstanding performance even when [Cl−] and [SO42−] were 100 g/L. CO32− and HCO3− inhibited BPA degradation greatly, even at very low concentrations. The inhibitory effect was related to changes in the pH of the solution caused by the addition of CO32− and HCO3−. This effect could be eliminated by adjusting the pH.ConclusionThe system showed excellent catalytic performance, stability, and inorganic anion tolerance, indicating its potential for application in hypersaline wastewater treatment. © 2024 Society of Chemical Industry (SCI).

Ammonia inhibition in anaerobic digestion of organic waste: a review

AbstractAnaerobic digestion (AD) has become the technology of choice for organic waste treatment as an environmentally beneficial and sustainable waste treatment technology. However, the nitrogen content of these organic waste streams is generally high. Ammonia is produced in the biodegradation of nitrogenous organic matter. Low concentrations of ammonia favour AD, but high concentrations can lead to digestive system failure. To address the issue of ammonia inhibition and ensure the stability of the digestive system, numerous physical, chemical, and biologicalmethods aimed at controlling ammonia levels and/or strengthening the biological processes have been proposedand developed. Literature evidence suggests that differences in AD reaction conditions and microbial sources result in different tolerances of the digestive system to ammonia and nitrogen. This paper summarises and compares the inhibitory effects of ammonia nitrogen under different conditions and the existing regulatory measures to alleviate ammonia nitrogen inhibition. In addition, since the core of the digestive system is microorganisms, this paper explains the mechanism of ammonia stress especially at the microbial level, and in this way, it explores the future direction of research using biofortification. This review provides a theoretical reference for solving the problem of ammonia nitrogen inhibition.

The impact of liquidity risk and credit risk on bank profitability during COVID-19.

The COVID-19 outbreak caused a massive setback to the stability of financial system due to emergence of several other risks with COVID, which significantly influenced the continuity of profitable banking operations. Therefore, this study aims to see that how differently the liquidity risk and credit risk influenced the banking profitability during Covid-19 (Q12020 to Q42021) than before COVID (Q12018 to Q42019). The study employs pooled OLS, and OLS fixed & random effects models, to analyze the panel data on a sample of 37 banks currently operating in Pakistan. The results depict that liquidity risk has a positive and significant relationship with return on assets and return on equity, but insignificant relationship with net interest margin. Credit risk has a negative and significant relationship with return on assets, return on equity, and net interest margin. The study also applies quantile regression to address the normality issue in data. The quantile regression results are consistent with pooled OLS, and OLS fixed and random effects results. The study makes valuable suggestions for regulators, policymakers, and others users of financial institutional data. The current study will help to set policies for efficient management of LR and CR.

Comparison of acoustic, optical, and heat release rate based flame transfer functions for a lean-burn injector under engine-like conditions

Determining the flame transfer function plays a crucial role during the development phase of lean-burn injectors to predict the overall stability of the combustion system. This study develops an enhanced acoustic post-processing strategy using acoustic network modeling and compressible large-eddy simulation for a lean-burn aero-engine injector in a realistic test rig. Results show that optical flame transfer functions experimentally obtained align with those derived from large-eddy simulation based on heat release rate. However, discrepancies, especially in gain, are observed when using the standard acoustic post-processing method. By employing an acoustic network model, it is shown that comparable flame transfer functions can be achieved through refined post-processing strategies. This study highlights the limitations of conventional acoustic post-processing and underscores the necessity of explicit acoustic modeling in complex setups to accurately obtain the flame response. A generalized formulation applicable to a broader range of setups, extending beyond simple configurations, is presented as an alternative to the conventional acoustic post-processing method.

Countering hegemonism in the Indo-Pacific

The global COVID-19 pandemic has exposed and accentuated the irreconcilable differences among Indo-Pacific states concerning ideology, governance, and understandings of the legitimate uses of power. The Communist Party of China is employing great power statecraft that is best described by the Chinese concept of 霸权主义 Bàquán zhŭyì (hegemonism or aggression aimed at weaker states). This ideologically driven behavior threatens the stability of the global system and may hinder the political and economic gains achieved over decades through the collective cooperation and constraint of aggressive great power statecraft. This article describes a transformation in the People's Republic of China's (PRC) approach towards Australia. It suggests that unless there's an internal upheaval in the PRC's statecraft, the global system might need to temporarily rely on mercantilist blocs to maintain human security, primarily within the democratic states of the Indo-Pacific. This survival strategy would involve resisting hegemonism.

Dynamic Characteristics Analysis of the DI-SO Cylindrical Spur Gear System Based on Meshing Conditions

The dual-input single-output (DI-SO) cylindrical spur gear system possesses advantages such as high load-carrying capacity, precise transmission, and low energy loss. It is increasingly becoming a core component of power transmission systems in maritime vessels, aerospace, marine engineering, and construction machinery. In practical operation, the stability of the DI-SO cylindrical spur gear system is influenced by complex excitations. These excitations lead to nonlinear vibration, meshing instability, and noise, which affect the performance and reliability of the entire equipment. Hence, the dynamic performance of the DI-SO cylindrical spur gear system is thoroughly investigated in this research. The impact of excitations and nonlinear factors on the dynamic characteristics was investigated comprehensively. A comparative analysis of the gear system was conducted by establishing a bending–torsional coupling vibration analysis model under synchronous and asynchronous meshing conditions. Nonlinear factors such as periodic time-varying meshing stiffness, meshing damping, friction coefficient, friction arms, load sharing ratio, comprehensive transmission error, and backlash were considered in the proposed model. Then, the effect laws of excitations and nonlinear factors such as meshing frequency, driving load fluctuation, backlash, and comprehensive transmission error were analyzed. The results indicate that the dynamic characteristics exhibited staged stable and unstable states under different meshing frequencies and meshing conditions. At the medium-frequency meshing stage (0.96 × 104~1.78 × 104 Hz), alternating phenomena of multi-periodic, quasi-periodic, and chaotic motion states were observed. Moreover, the root mean square value (RMS) of the dynamic transmission error (DTE) in the asynchronized gear system was generally higher than that in the synchronized gear system. It was found that selecting the appropriate meshing condition could effectively reduce the amplitude of the DTE. Additionally, the dynamic performance could be significantly improved by adjusting control parameters such as driving load fluctuation (0~179 N), backlash (0.8 × 10−4~0.9 × 10−4 m), and comprehensive transmission error (7.9 × 10−4~9.4 × 10−4 m). The research results provide a theoretical guidance for the design and optimization of the DI-SO cylindrical spur gear system.

Design and Control of DVR Based on Adaptive Bateman Polynomial for Power Quality Improvement

ABSTRACTPower quality issues encompass a spectrum of disturbances that affect the stability and reliability of the power supply. This study explores voltage‐related anomalies, including sags, surges, flickers, unbalances, harmonics, interruptions, and swells, examining their origins, characteristics, and repercussions. These issues arise from a myriad of sources, such as load fluctuations, equipment malfunctions, and grid dynamics. The ramifications of these disturbances extend to equipment malfunctions, reduced operational efficiency, and financial losses. Dynamic voltage restorer (DVRs) are series custom power devices for mitigating these voltage‐related anomalies and use real‐time monitoring and control to quickly inject exact voltages into the grid during disruptions, restoring voltage levels to acceptable levels. This study demonstrates the capacity of DVRs to successfully alleviate power quality concerns, hence improving equipment dependability and system stability by analyzing case studies and simulation findings. The control system used to supply switching signals to the voltage source converter (VSC) of the DVR is based on adaptive Bateman polynomial (ABMP). Traditional DVR control techniques often rely on fixed or linear control strategies, which may not adequately handle varying load conditions and disturbances. ABMP offers an adaptive approach where the control parameters can adjust dynamically based on real‐time system conditions. This adaptive capability enhances the accuracy of voltage restoration, ensuring that the DVR responds optimally to varying loads and disturbances. During voltage sag and swell conditions at the grid side, the VSC injects the compensating voltage in series with the feeder with a constant switching frequency. A battery energy‐supported system (BESS) based DVR is considered for the proposed system. The supply is connected to the critical and sensitive loads. The proposed control scheme is validated through extensive simulation and experimental results.

High-speed magnetically levitated centrifugal hydrogen recirculation pump in proton exchange membrane fuel cells

This paper presents a novel magnetically levitated centrifugal hydrogen recirculation pump (MLCHRP) designed for proton exchange membrane fuel cells (PEMFCs). Compared to traditional hydrogen recirculation pump, the MLCHRP offers significant advantages, including no lubrication, no mechanical friction, and active vibration suppression. However, the compact design of the pump imposes constraints on the load capacity of the active magnetic bearings (AMBs). As a result, the rotor is more susceptible to instability when subjected to unbalanced disturbance forces. This paper details the structure of the MLCHRP and provides an analysis of the basic model for unbalanced disturbance forces. A method for suppressing these unbalanced disturbances is proposed, utilizing a Linear Extended State Observer (LESO) combined with Parallel Peak Filters (PPF). The impact of this approach on system stability is thoroughly examined, and the effectiveness of the proposed method for unbalanced disturbance suppression is experimentally validated. The experimental results show that the peak-to-peak displacement of the rotor decreased by 80%. Additionally, the synchronous component in the rotor's displacement FFT was reduced by 6 dB (from -19.2 dB), and the second harmonic component decreased by 23.8 dB (from -23.7 dB). Finally, aerodynamic performance tests confirm that the MLCHRP meets the application requirements of actual PEMFCs system.

Effect of financial contagion between real and financial sectors on asset bubbles: A two‐layer network game approach

AbstractUnderstanding the mechanism of asset bubble formation is important for maintaining financial stability and healthy functioning of the economic system. With gradual emphasis on the complex characteristics of financial markets, a new perspective for analyzing the emergence of asset bubbles is emerging: how to integrate the real economy with financial markets composed of heterogeneous individuals. In this study, we propose a two‐layer network game to investigate the impact of financial contagion between the real and financial sectors on asset bubbles. Among their interactions, shadow banking activities in both sectors increase the contagion risk across financial markets and construct a broader financial system. Both credit interactions and peer learning effects are captured in the network framework. Simulating relevant regulation policies, our experiments indicate that regulators should closely monitor returns on assets by setting an upper threshold. Financialization in the real sector significantly exacerbates the formation of asset bubbles, with medium‐level borrowing constraints minimizing bubble dynamics most effectively. The financialization practices of mature industries should be strictly regulated, while innovative industries should be allowed moderately flexible financing practices. The degree of friction within the financial market should be flexibly calibrated for financial institutions and genuine enterprises, aiming to mitigate systemic risks in the financial market while fostering robust growth in the real economy.

A new optimal 3° of freedom fractional order proportion integral derivative controller with model predictive controller for frequency regulation in high penetrated renewable based interconnected system

The increasing use of renewable energy sources (RESs) in conventional power systems is making them more complex. RES, such as solar and wind energy, reduce system inertia, affecting power system (PS) stability and frequency aberrations. Thus, the modern PS faces new concerns that arise from integrating RESs and struggles to manage frequency and stability, which can cause power outages and blackouts and lower industry production. The intelligent control mechanism is critical to the PS's operation to ensure frequency under its complicated structure. This study suggests a new best 3-DoF fractional order proportional integral derivative-model predictive controller (3DoF-FOPIDN-MPC) for controlling frequency when there is a lot of load going on quickly. The 3DoF-FOPID controls the outer loop using the area control error (ACE) signal, while MPC controls the inner loop using the output signal from the 3DoF-FOPIDN and the area's total power output response. For optimal controller functionality, the salp swarm algorithm (SSA) extracts optimized controller settings. To validate the suggested controller, it is tested under various load-changing scenarios and compared to state-of-the-art controllers. For 1 % and 3 % load changes, the suggested controller settles in 1.1 s and 1.78 s, respectively.

Transforming Mexico’s Electric Load Infrastructure: A Quantile Transformer Network Deep Learning Approach, 2019-2020

To transform Mexico's electric load infrastructure, accurate electric load forecasts are required that are crucial to efficiently allocate resources, maintain system stability, and manage energy. The purpose of this study is to use the Quantile Transformer Network (QTN) as a novel approach for a deep learning framework for load forecasting, emphasizing its potential and practical consequences in enhancing the accuracy of load forecasting in real-world energy systems. Moreover, it is shown that QTN efficiently captures complex patterns, temporal relationships and interconnections among factors that influence electric load. The dataset utilized consists of past records of energy consumption in the Baja California System in Mexico. It includes several factors such as electricity demand, marginal prices, temporal characteristics, temperature-related variables, seasonal patterns, and holidays. Additionally, QTN is combined with the Rainbow Technique (RT) to manage categorical variables, resulting in the creation of a unified feature called category. In this case, RT examines the connections between descriptive phrases that reflect distinct combinations of categorical factors depending on the load values. Moreover, this research shows that the common Quantile Regression (QR) outperforms QTN in capturing dependencies in sequential data. Finally, several recommendations for promoting Mexico's Electric Load Infrastructure are provided.

Dynamics and adaptive backstepping control of rotor-hybrid foil-magnetic bearings system

The hybrid foil-magnetic bearing (HFMB) is a contactless-type bearing composed of a foil bearing (FB) in the inner side and an active magnetic bearing (AMB) in the outer side. It has the advantages of low drag torque, high DN value (bearing inner diameter times rotating speed), and high supporting efficiency. However, significant subsynchronous vibration will degrade the stability of the rotor-HFMBs system, which is an obstacle to the industrial implementation of HFMBs. To control the rotor vibration, this paper presents a dynamic model of the rotor-HFMBs system with unknown parameters and the design of an adaptive backstepping controller (ABC) for it. The stability of the closed-loop system is established. Simulation results of the rotor-HFMBs system controlled by ABC are compared with the proportional-integral-derivative controller (PID), illustrating that the ABC is capable of eliminating rotor vibration, and it is more effective than the PID.

Continuous-time robust frequency regulation in isolated microgrids with decentralized fixed structure μ-synthesis and comparative analysis with PID and FOPID controllers

Isolated microgrids, which are crucial for supplying electricity to remote areas using local energy sources, have garnered increased attention due to the escalating integration of renewable energy sources in modern microgrids. This integration poses technical challenges, notably in mitigating frequency deviations caused by non-dispatchable renewables, which threaten overall system stability. Therefore, this paper introduces decentralized fixed structure robust μ-synthesis controllers for continuous-time applications, surpassing the limitations of conventional centralized controllers. Motivated by the increasing importance of microgrids, this work contributes to the vital area of frequency regulation. The research challenge involves developing a controller that not only addresses the identified technical issues but also surpasses the limitations of conventional centralized controllers. In contrast to their centralized counterparts, the proposed decentralized controllers prove more reliable, demonstrating enhanced disturbance rejection capabilities amidst substantial uncertainties, represented through normalized co-prime factorization. The proposed controllers are designed using the D-K iteration technique, incorporating performance weight filters on control actions to maintain low control sensitivity and ensure specific frequency band operation for each sub-system. Importantly, the design considers unstructured uncertainty up to 40%, addressing real-world uncertainties comprehensively. Rigorous robust stability and performance tests underscore the controller's superiority, demonstrating its robustness against elevated uncertainty levels. Robust stability is verified for all controllers, with the proposed controller showing robust stability against up to 171% of the modeled uncertainty. Notably, the controller boasts a fixed structure with lower order compared to other H-infinity controllers, enhancing its practical implementation. Comparative analyses against Coronavirus Herd Immunity Optimizer tuned Proportional-Integral-Derivative (CHIO-PID) controller and CHIO tuned Fractional-Order Proportional-Integral-Derivative (CHIO-FOPID) controller further validate the superior performance of the proposed solution, offering a significant step towards ensuring the stability and reliability of microgrid systems in the face of evolving energy landscapes.

Modified guanidine gel fracturing fluid system and performance optimization for ultra-deep and ultra-high temperature oil and gas reservoirs

The development of deep high-temperature oil and gas reservoirs gives rise to a rise in reservoir temperature along with the depth of the oil reservoir, thereby imposing higher requirements on the heat resistance of fracturing fluid. Guar gum fracturing fluid has difficulty tolerating temperatures exceeding 160 °C, thereby demanding the development of corresponding cross-linking agents, temperature stabilizers, and other additives to enhance the thermal stability of the fracturing system. Considering the distinctive characteristics of deep and ultra-deep reservoirs, such as extreme burial depth (exceeding 6000 m), ultra-high temperature (higher than 160 °C), and high fracturing pressure, an experimental modification of a guar gum fracturing fluid system was carried out, specifically tailored for ultra-high temperatures. The experiment identified and selected individual agents for ultra-high temperature fracturing fluids, including crosslinking agents, thermal stabilizers, flowback aids, and clay inhibitors. Through rigorous experimentation, these key agents for an ultra-high temperature fracturing fluid system have been successfully developed, including the optimal thickener GBA1-2, crosslinking agent BA1-1, anti-swelling agent FB-1, and gel breaker TS-1. The evaluation of diverse additive dosages has facilitated the development of an optimal guar fracturing fluid system, which exhibits outstanding high-temperature resistance while minimizing damage and friction. The outcomes of our experiments indicate that even after subjecting our ultra-high temperature fracturing fluid to 2 h of shearing at 170 s−1 at 180 °C, its viscosity remained above 200 mPa s—a distinct proof of its superior performance in withstanding high temperatures. This achievement represents a substantial progress in providing a suitable fracturing fluid system for the transformation and stimulation of ultra-deep and ultra-high temperature reservoirs, and also lays a solid foundation for further exploration and application in related fields in the future.

Hybrid feedback control of PMSG-based WECS with multilevel flying-capacitor inverter enhanced by fractional order extremum seeking

This paper proposes an original hybrid control strategy for a three-phase multilevel flying capacitor inverter (FCI) used in wind energy conversion system (WECS). A state feedback law, computed using a Lyapunov function and an invariance principle, is designed to manage grid current control and capacitor voltage balancing, guaranteeing the asymptotic stability of the closed-loop system. Additionally, a fractional-order extremum seeking control (FOESC) algorithm for Maximum Power Point Tracking (MPPT) is introduced, which optimizes power capture by adjusting turbine speed from the DC side without requiring a detailed system model (model-free approach). The use of fractional-order calculus leads to improved convergence and more seamless performance while preserving the robust characteristics of the system. The proposed control strategies are validated through simulation, demonstrating improved transient response and stability under varying wind conditions and parameter uncertainties. These results highlight the potential of advanced control algorithms to enhance the efficiency and reliability of wind energy systems, contributing to global efforts to achieve sustainable energy goals.