Stability Of System Research Articles

Optimized design and comparative analysis of double-glazed photovoltaic windows for enhanced light harvesting and energy efficiency in cold regions of China

This study investigates the daylighting performance and energy efficiency optimization strategies of double-glazed photovoltaic windows (DS-STPV) in cold regions of China. By conducting a comprehensive comparative analysis with traditional and energy-efficient window systems, this research aims to identify high-efficiency building solutions tailored to extreme climatic conditions. Amidst the escalating global energy demand and the pressing need for energy conservation and emission reduction, Building-Integrated Photovoltaic (BIPV) technology is increasingly recognized for its potential and value as a critical method for harnessing green energy. However, the widespread adoption of BIPV technology faces several challenges, including cost-effectiveness, conversion efficiency, system stability, and architectural aesthetic integration. Utilizing the T&A House from the 3rd International Solar Decathlon as an empirical case study, this research employs Ecotect and DesignBuilder simulation software to systematically evaluate the daylighting effect and energy performance of DS-STPV. The analysis considers various key design parameters, including photovoltaic cell coverage, window orientation, and window-to-wall ratio. Through refined modeling and multi-dimensional analysis, this study aims to identify the optimal design configurations of DS-STPV windows in cold regions, with the goal of simultaneously achieving superior natural lighting quality and significant building energy efficiency. The findings indicate that a south-facing DS-STPV window design with approximately 30% photovoltaic cell coverage and a window-to-wall ratio of 30% effectively balances daylighting requirements and energy efficiency in cold regions of China. This design strategy not only ensures an abundance of natural light in the room, but also significantly reduces the building’s energy consumption, proving the superior performance of DS-STPV windows in cold climates. In addition, the unique optical properties of DS-STPV windows reduce glare, further improving the overall quality of the indoor environment. In summary, this study provides a robust scientific foundation for the application of DS-STPV windows in cold regions, offering practical guidance and reference for optimizing energy efficiency and facilitating green transformation in future building design.

Techno-Economic Optimization of Microgrid Operation with Integration of Renewable Energy, Hydrogen Storage, and Micro Gas Turbine

Microgrids are integral to modern energy systems, yet they face substantial challenges in integrating diverse components, managing complex dynamics, and ensuring stability amid renewable energy variability. This study investigates the integration of wind turbines, an electrolyzer, and a hydrogen-compatible micro gas turbine (MGT), with a focus on enhancing operational efficiency and maintaining dynamic equilibrium within the microgrid. The synergy between the electrolyzer and MGT provides a robust energy storage solution, improving both system stability and performance.Using advanced machine learning and real operational data, this research generates highly accurate, rapid models with greater precision and detail than conventional methods. The intelligent management system developed combines real-time optimization and adaptive fine-tuning, using forecasts of weather, electricity prices, and energy demand to devise optimized operational strategies. The study systematically analyzes various configurations, including grid-connected and island modes, and evaluates the impact of hydrogen storage in each scenario.The results demonstrate that the optimization approach substantially enhances economic returns. However, this can also lead to increased natural gas consumption and emissions, revealing a trade-off between financial gains and environmental sustainability. This highlights the necessity for strategies that reconcile economic incentives with sustainability objectives, offering valuable insights for improved microgrid management.

Parameters of Performance: A Deep Dive into Liquid-to-Air CDU Assessment

The rapid growth in data center workloads and the increasing complexity of modern applications have led to significant contradictions between computational performance and thermal management. Traditional air-cooling systems, while widely adopted, are reaching their limits in handling the rising thermal footprints and higher rack power densities of next-generation servers, often resulting in thermal throttling and decreased efficiency, emphasizing the need for more efficient cooling solutions. Direct-to-chip liquid cooling with cold plates has emerged as a promising solution, providing efficient heat dissipation for high-performance servers. However, challenges remain, such as ensuring system stability under varying thermal loads and optimizing integration with existing infrastructure. This comprehensive study digs into the area of data center liquid cooling, providing a novel, comprehensive experimental investigation of the critical steps and tests necessary for commissioning coolant distribution units (CDUs) in direct-to-chip liquid-cooled data centers. It carefully investigates the hydraulic, thermal, and energy aspects, establishing the groundwork for Liquid-to-Air (L2A) CDU data centers. A CDU’s performance was evaluated under different conditions. First, the CDU’s maximum cooling capacity was evaluated and found to be as high as 89.9 kW at an approach temperature difference (ATD) of 18.3 °C with a 0.83 heat exchanger effectiveness. Then, to assess the cooling performance and stability of the CDU, a low-power test and a transient thermohydraulic test were conducted. The results showed instability in the supply fluid temperature (SFT) caused by the oscillation in fan speed at low thermal loads. Despite this, heat removal rates remained constant across varying supply air temperatures (SATs), and a partial power usage effectiveness (PPUE) of 1.042 was achieved at 100% heat load (86 kW) under different SATs. This research sets a foundation for improving L2A CDU performance and offers practical insights for overcoming current cooling limitations in data centers.

Hydrodynamic performance study of floating photovoltaic arrays with multiple floating bodies

In the context of the global transition to renewable energy, floating photovoltaic systems have garnered significant attention as an innovative method of energy utilization. To investigate the impact of different arrangements of floating photovoltaic (FPV) systems on hydrodynamic performance, fully coupled numerical simulations of wind, wave and current were conducted in ANSYS-AQWA for three arrangements: rectangular array, linear array, and honeycomb-like array. The analysis focused on the six degrees of freedom motions and maximum mooring force under operational and survival conditions. It can be found that the rectangular array exhibits the strongest system stability, effectively reducing the mooring force and showing insensitivity to variations in load incident angles. These findings provide a theoretical foundation and engineering guidance for the design of FPV systems, offering substantial practical application value.

Optimal energy management of MG for cost-effective operations and battery scheduling using BWO

The rapid growth of renewable standalone systems, with their inherent uncertainties and intermittency, poses a huge challenge to system stability. In this paper, an intelligent microgrid is proposed that fully utilizes the complementarity characteristics in PV and battery storage system (BESS), and is capable of maintaining an economic, reliable, and environmental equilibrium in daily generation scheduling. A black widow optimization (BWO) based controller is designed to determine the best possible solution under different scheduling scenarios. In addition, an exponential cost function based on the battery’s degree of discharge (DOD) is introduced to calculate the battery generation cost. It will include the battery lifetime cost in the overall power generation cost. Furthermore, the cost of the diesel generator includes the CO2 emission cost which is inversely proportional to the generator efficiency. The BWO algorithm optimized the generation cost based on these functions and increase the reliability of the grid using reliability index. The BWO algorithm finds the optimal global solution in less than 30 iterations and avoid the local optima problem. The effectiveness and convergence speed of BWO is far better than other algorithms and is validated by simulation results.

Temporal asynchrony analysis for dynamic operation of hydraulic-thermal-electricity multiple energy networks based on holomorphic embedding method

Analyzing the operational states of multiple energy networks (MEN) in multi-energy systems is crucial for ensuring system stability. The dynamic operational characteristics of different energy flows pose challenges for computational analysis. Traditional steady-state methods are inadequate for addressing the dynamics of MEN, especially when dealing with temporal discrepancies between hydraulic and thermal flows in thermal networks (TN) and the heterogeneity between TN and electrical networks. Therefore, this paper proposes a novel holomorphic embedding method (HEM) based on multi-stage decomposition method. The developed HEM constructs a time coefficient matrix and utilize inner-outer loop recursion to handle the time lag between thermal flow and hydraulic flow in the TN. Additionally, we reconstruct a holomorphic matrix, integrating hydraulic flow to bridge thermal and electric power flows, thereby improving the operational heterogeneity among different networks. Real-case simulations show that when the Taylor expansion order in HEM is equal to 4, the proposed method achieves a mere 1% discrepancy from actual operational data, enhancing computational efficiency by 60% compared to the Newton-Raphson method. Moreover, in this real-case, the TN exhibits a maximum delay response time of 180s compared to electrical networks. Exploiting this delay time effectively increases renewable energy generation within multi-energy systems by 961.58kW per day.

Power system stability and control: a comprehensive review focusing on the rotor angle case

Power system stability and control: a comprehensive review focusing on the rotor angle case

Activation of Algicidal Bacteria and Nitrogen-Phosphorus Removal Bacteria During Controlling Cyanobacteria Bloom in Taihu Lake by Artemisinin Algaecide

Cyanobacterial harmful algal blooms (CyanoHABs) in Taihu Lake pose a persistent environmental challenge. This study investigated the inhibitory effects of artemisinin algaecide (AMA) on cyanobacteria in Taihu Lake and assessed its impact on nutrients, as well as the structures of particle-attached (PA) and free-living (FL) bacterial communities and potential ecological mechanisms. The results indicated that A-3 (0.8g artemisinin/L) effectively inhibited CyanoHABs (inhibition rate = 93%) and significantly increased the alpha diversity of PA and FL bacterial communities during the stationary phase， thereby promoting the proliferation of algicidal bacteria (AB) (e.g., Acinetobacter, Stenotrophomonas, and Exiguobacterium) and heterotrophic nitrification-aerobic denitrification (HN-AD) bacteria (e.g., Acinetobacter, Stenotrophomonas, and Bacillus) through the utilization of dissolved organic carbon (DOC) from the dead cyanobacteria. This proliferation enhanced nitrogen metabolism and increased the abundance of nitrogen-cycling functional genes, improving nutrient cycling and enhancing system stability. The increased abundance of AB continuously suppressed cyanobacteria, while the proliferation of HN-AD bacteria removed nitrogen and phosphorus from the water, thus limiting nutrients available for cyanobacterial growth. Our findings demonstrate that AMA effectively inhibits CyanoHABs and prevents secondary blooms, providing a scientific foundation for the widespread application in cyanobacterial management, enhancing the effectiveness and sustainability of CyanoHAB control efforts.

Assessment of Flexible Coal Power and Battery Energy Storage System in Supporting Renewable Energy

The use of renewable energy sources (RES) is expected to increase, potentially leading to volatility in the power system. Therefore, flexible power is essential to address this challenge. In China, two viable options for providing flexible power are battery energy storage systems (BESS) and flexibility modification of coal power units. This study introduces a framework to evaluate the costs of power system flexibility under varying RES shares on an hourly basis, comparing flexible coal power and BESS across several scenarios. In the short term, flexible coal power proves to be more advantageous than BESS, but BESS shows greater promise in the long run. The study suggests that while coal power will continue to play a critical role in the near future, it should gradually be phased out by reducing its utilization hours. Meanwhile, BESS should receive greater focus for long-term energy strategy. This study underscores the importance of maintaining power system stability throughout the low-carbon transition and highlights the need to balance short-term and long-term strategies for flexible power.

A novel PWM plus phase shift modulation strategy for three‐level isolated dual‐active‐bridge DC–DC converters

AbstractA hybrid‐three‐level isolated dual‐active‐bridge (HTDAB) DC–DC converter is widely used for grid‐interactive power converters. However, a traditional extended‐phase‐shift (EPS) modulation scheme would cause voltage‐level‐disorder (VLD) problems in HDAB DC–DC converter system because the output voltage of HTDAB would be clamped at a high‐ or low‐level during power transmission when the inductor current changes directions. Thus, the zero voltage sequence of the HTDAB cannot be stably maintained under EPS control, which not only leads to a significant difference between the actual transmission power and the target output power but also seriously affects the stability of the system control. To address this limitation, the reasons leading to VLD are analysed in detail, that is, an inappropriate PWM switching sequence at the output zero voltage level would occur under EPS control. Then, a novel PWM plus phase shift (PPS) modulation strategy is proposed, which can eliminate VLD completely. Finally, an experimental prototype is built to verify the effectiveness of the proposed PPS modulation scheme. The experimental results demonstrate that the PPS modulation method proposed in this article can effectively eliminate level disturbances and improve system stability.

PID control algorithm based on multistrategy enhanced dung beetle optimizer and back propagation neural network for DC motor control.

Traditional Proportional-Integral-Derivative (PID) control systems often encounter challenges related to nonlinearity and time-variability. Original dung beetle optimizer (DBO) offers fast convergence and strong local exploitation capabilities. However, they are limited by poor exploration capabilities, imbalance between exploration and exploitation phases, and insufficient precision in global search. This paper proposes a novel adaptive PID control algorithm based on enhanced dung beetle optimizer (EDBO) and back propagation neural network (BPNN). Firstly, the diversity of exploration is increased by incorporating a merit-oriented mechanism into the rolling behavior. Then, a sine learning factor is introduced to balance the global exploration and local exploitation capabilities. Additionally, a dynamic spiral search strategy and adaptive [Formula: see text]-distribution disturbance are presented to enhance search precision and global search capability. The BPNN is employed to fine-tune both PID and network parameters, leveraging its powerful generalization and learning ability to model nonlinear system dynamics. In the simplified motor experiments, the proposed controller achieved the lowest overshoot (0.5%) and the shortest response time (0.012s), with a settling time of 0.02s and a steady-state error of just 0.0010. In another set of experiments, the proposed controller recorded an overshoot and response time of 0.7% and 0.0010s, across five DC motor tests. These results demonstrate the proposed adaptive PID control algorithm has superior performance in optimizing control system parameters, as well as improving system robustness and stability.

Dual-Sliding-Surface Robust Control for the PEMFC Air-Feeding System Based on Terminal Sliding Mode Algorithm

The proton exchange membrane fuel cell (PEMFC) is the most widely used fuel cell, but it also has some limitations. One of the research pain points is controlling the oxygen content in PEMFCs. A moderate excess of oxygen boosts electrochemical reaction efficiency, while an appropriate oxygen content ensures system stability. In this paper, a fourth-order nonlinear mathematical model of a PEMFC stack air supply system is established to solve the problem of optimal oxygen excess ratio (OER) control under dynamic load conditions. Based on the model, a nonsingular terminal sliding mode controller (NTSMC) based on a sliding mode observer (SMO) is proposed. The NTSM exhibits superior robustness and performance compared to other sliding mode structures. Meanwhile, the SMO accurately predicts system states, facilitating precise control actions. Additionally, the dual sliding mode surfaces enhance system stability against parameter uncertainties and external disturbances. Our results demonstrate that the proposed controller outperforms traditional ones in terms of robustness and performance, which significantly enhances PEMFC system efficiency and stability.

An active queue management method for multiple bottleneck networks based on distributed average tracking

The active queue management (AQM) is a key technology for the information infrastructure and the Internet. The AQM for multiple bottleneck networks is especially challenging than that for single-bottleneck networks because the stability analysis of multiple bottleneck networks is more complex. In this paper, the active queue management problem for multiple bottleneck networks is considered. A novel random early detection algorithm is designed based on distributed average tracking technology, which is used to estimate the global queue length and improve the network's performance. Sufficient conditions for global asymptotic stability of the closed-loop active queue management system are presented, and some simulation results with NS-2 are given. Compared with the RED algorithm, simulation results show that the presented algorithm has smaller oscillations at routers, which highlights its effectiveness.

Turnover intention among healthcare workers in Shenzhen, China: the mediating effect of job satisfaction and work engagement.

To ensure workforce stability in China's healthcare system and maintain high-quality care, it is essential to comprehensively understand the interplay of factors contributing to turnover intention of healthcare workers. This study aims to examine the associations between potential factors and turnover intention in healthcare workers and explore the mediating effect of job satisfaction and work engagement in the association between them. In this cross-sectional study, a random sample of 1060 healthcare workers working in 98 public medical institutions were recruited to rate their turnover intention in 2018 in Shenzhen, China. Information on socio-demographic characteristics, job-related factors, turnover intention, job satisfaction, work engagement, work stress and doctor-patient relationship of participants were collected. Pearson's chi-squared tests and binary logistic regression analyses were performed to explore the association between these factor and turnover intention. Mediation analysis was used to explore the roles of potential mediators and moderators. The results showed that age (OR: 0.35, 95%CI: 0.16 to 0.72), tenure (OR: 0.98, 95%CI: 0.96 to 0.99), administrative positions (OR: 0.33, 95%CI: 0.16 to 0.63), and night shift frequency (OR: 1.84, 95%CI: 1.26 to 2.67) were significantly associated with turnover intention. We identified the mediating effect of job satisfaction and work engagement in the relationship between administrative positions and turnover intention, while the suppressing effect in the relationship between professional titles and turnover intention. Additionally, we found that monthly income plays a moderating role in the relationship between work engagement and turnover intention, and in the association between professional titles and turnover intention. Greater job satisfaction and engagement, along with reasonable remuneration, were found to be associated with lower turnover intention among healthcare workers. Employers should proactively monitor the dynamic interactions among these factors and then develop more tailored interventions in order to alleviate the ongoing loss of healthcare workers.

Lipase pretreatment enhances biochar‐assisted anaerobic digestion of food waste

AbstractAnaerobic digestion is a promising technology for the treatment of food waste (FW) but it requires optimization to improve its performance. This study investigated whether combining the addition of biochar with lipase pretreatment could improve the anaerobic digestion of FW. The results showed that biochar stimulated the release of soluble substances, resulting in an increase in the methane yield of groups with added biochar by 16.24% to 19.36% in comparison with the group without biochar. Lipase pretreatment substantially shortened the fermentation time required to complete the anaerobic digestion, from 15 to 9 days. Lipase pretreatment further improved microbial abundance and promoted the enrichment of functional microbes in the anaerobic digestion of FW mediated by biochar. It also changed the methane production pathway from acetotrophic to hydrogenotrophic, thereby ensuring the stability of the anaerobic digestion system in the presence of a high ammonia nitrogen concentration.

Experiment and Simulation Study on the Adsorption Interaction between a Fluorescent Tracer and a Montmorillonite Crystal in Drilling Fluid.

The adsorption interaction of oil field tracer in drilling fluid plays a significant role in tracer monitoring (TM) technology in the petroleum industry. In this work, the adsorption performances of Rhodamine B (RhB+) and fluorescein sodium (Fln-) tracers with montmorillonite (MMT) crystal in drilling fluid were investigated by both experimental and simulation methods. For the experimental aspect, the macroscopic results indicate thermodynamic monolayer adsorption by the Langmuir model and kinetic chemical adsorption by the pseudo-second-order (PSO) model. As a result, MMT shows a larger adsorption capacity (qm) for RhB+ than for Fln- with but stronger adsorption spontaneity (ΔrGmθ) for Fln- than for RhB+ with kJ mol-1 < kJ mol-1. Meanwhile, the interaction rate (k2) of Fln- was shown to be faster than that of RhB+ with . For simulation insight, MMT shows much higher system stability (E) for Fln- than for RhB+ with and . Meanwhile, the microscopic simulation results reveal configuration changes and site distinctions for RhB+ and Fln- interactions with the MMT crystal. The different adsorption responses were explained by proposing an interaction mechanism of force dominance and position orientation. Specifically, Fln- was deduced to interact with metal (Al, Ca) and metalloid (Si) elements in the MMT crystal interlayer by "upright-insertion" orientation while RhB+ was deduced to interact with oxygen atoms on the MMT crystal surface by a "flat-lying" orientation. Hydrogen bonds, the electrostatic interaction, and the coordination effect were revealed to dominate for the interaction of tracer adsorption. This work provides both performance and mechanism investigation of fluorescent tracer adsorption interaction with the MMT crystal in drilling fluid, which is of great significance in reservoir exploitation.

Stability Improvement of Multimachine System Using Back-To-Back Converters

As the penetration level of inverter-based generators continues to increase, it becomes crucial to reduce power oscillations between inverters and synchronous generators (SG) to improve system stability. This paper uses a multimachine system as the research platform and proposes a grid separation method employing a multi-terminal back-to-back converter. The converter is designed to be placed at the point of common coupling (PCC) in the original multimachine system and can divide the original grid into multiple microgrid regions while retaining the ability to transmit power between different regions. Each microgrid or region contains a self-regulated power source such as grid-forming (GFM) inverter or synchronous generator, which controls key power characteristics such as frequency and voltage within its region. The back-to-back converter facilitates power transmission between different regions. The AC-DC-AC conversion process ensures isolation and simplification of control over each microgrid’s power characteristics. The performance of inverters with different control strategies in each microgrid has been investigated, and the characteristics of various inverters are compared and demonstrated. Additionally, it was found that the battery storage requirements in each inverter-based microgrid are reduced using this method. The results are verified through MATLAB/SIMULINK simulations.

Extreme learning machine‐based super‐twisting integral terminal sliding mode speed control of permanent magnet synchronous motors

AbstractThis article proposes an extreme learning machine (ELM)‐based super‐twisting integral terminal sliding mode control (STITSMC) for speed regulation of a permanent magnet synchronous motor (PMSM). First, the PMSM is modeled in a non‐cascade control structure for fast system response and uncertainty compensation in the speed and torque loops. Second, the STITSMC is designed with integral actions in both the sliding surface and the reaching law to reduce chattering. Third, the ELM is constructed to compensate for the system lumped disturbance, and relax the disturbance upper bound required by the controller which further reduces the chattering. Fourth, the stability of the whole control system is proved based on the Lyapunov method and the finite time convergence regions are derived for both the reaching and the sliding phases. Finally, the comparative simulations and experiments are conducted to show the superiority of the proposed control.

Stability of discrete-time system employing quantization and overflow nonlinearities

An investigation of exponential stability for externally interfered discrete-time systems under various concatenations of quantization and overflow nonlinearities is conducted in this article. A new criterion is proposed based on the passivity approach such that the interfered nonlinear discrete-time systems ensure passivity performance in terms of its storage function. The derived criterion not only considers the effects of overflow nonlinearity but also the consequences of quantization nonlinearity. Furthermore, the proposed criterion guarantees the passivity performance of the discrete-time system in the presence of external disturbance and exponential stability for zero disturbance. The reported conditions are defined in terms of linear matrix inequality, for easy tractability. Suitable examples are given to demonstrate the usefulness of the proposed work.

ELLIPSOIDAL DESIGN OF SLIDING MODE CONTROL FOR CAR ACTIVE SUSPENSION SYSTEM

The issue of state feedback sliding mode control (SMC) for a particular kind of active quarter-car suspension system is discussed in this work. The suspension systems' dynamic system is built with the three control objectives of maximal actuator control force, suspension deflection, and ride comfort in mind. The next step is to build the state-feedback controller with the disturbance (vibration) attenuation level in mind to guarantee the asymptotic stability of the closed-loop system. The algorithm for SMC design is introduced. It is predicated on choosing the sliding surface correctly using the invariant ellipsoid approach. The system motion in the sliding mode is guaranteed to be little affected by mismatched disturbances according to the control architecture. Furthermore, the presence of admissible controllers is articulated in terms of LMIs through the use of Lyapunov theory and the linear matrix inequality (LMI) technique. The objective is to create a desired dynamic state-feedback controller when these requirements are met. Lastly, a quarter-car model is used to illustrate how successful a suggested approach is.