Compromising System Stability Research Articles

Adaptive Resilience in API Polling Frameworks: A Hybrid Approach with Retry Strategies, Timeout Policies, Fallback Mechanisms, and Event-Driven Strategies

The growing reliance on distributed systems and microservices architecture necessitates resilient API polling frameworks capable of handling transient failures without compromising system stability. This research introduces a hybrid framework that integrates adaptive retry strategies with exponential backoff and jitter, dynamically tuned timeout policies, robust fallback mechanisms, and event-driven strategies. These components collectively enhance the ability of API polling frameworks to handle transient failures by reducing response times, conserving resources, and enabling more intelligent recovery mechanisms. By incorporating event-driven approaches, the framework optimizes communication flow and reduces unnecessary polling. This paper establishes a high-level blueprint for scalable, fault-tolerant API polling frameworks, laying the foundation for future innovation in resilient distributed systems. Keywords Resilient Systems, API Polling, Event-Driven Strategies, Transient Failures, Adaptive Retry Strategies, Timeout Policies, Fallback Mechanisms, Distributed Systems, Fault Tolerance, Scalability, Microservices

Global Event-Triggered Funnel Control of Switched Nonlinear Systems via Switching Multiple Lyapunov Functions.

In this article, the global event-triggered (ET) funnel tracking control problem is studied for a class of switched nonlinear systems with structural uncertainties, where the solvability of the control problem for each subsystem is not needed. A switching multiple Lyapunov functions (MLFs) method is established, where MLFs are designed to handle switched inverse dynamics, and a switching barrier Lyapunov function is constructed to address switched sampled errors that may compromise system stability. This is achieved alongside a new switching dynamic event-triggering mechanism (DETM). By combining this method with backstepping, a dwell-time state-dependent switching law and an ET funnel controller of each subsystem are constructed, effectively eliminating the issue of the "explosion of complexity" encountered in traditional backstepping without using dynamic surface control or command filters. Additionally, the designed switching DETM ensures that the tracking error always evolves within a performance funnel in any consecutive triggering interval, excluding Zeno behavior, and guaranteeing positive constant lower bounds for two consecutive triggering intervals and any switching interval, respectively. Finally, an example is provided to show the validity of the theoretical results.

Implementing Crowbar Protection To Maintain System Stability In Doubly Fed Induction Generator Wind Turbines

Doubly fed induction generator (DFIG) wind turbines play a crucial role in wind energy production. However, system stability during symmetrical voltage dips remains a significant challenge. This research area focuses on enhancing protection and regulation strategies to ensure that DFIG wind turbines operate stably and efficiently even when the electrical grid experiences disturbances. In-depth simulations and behavioral analyses are utilized to propose effective control solutions, minimizing the impact of voltage dips without compromising system stability. The findings from these studies are essential for wind turbine manufacturers and operators, contributing to the overall improvement of wind energy systems.

Implementation of ANFIS-based UPQC for Power Quality and Thermal Management Enhancement in the Distribution System

Conventional distribution systems generally operate with voltage and current waveforms being sinusoidal, though they slightly deviate from the ideal sinusoidal waveform, which is measured as distortion. The increase in power demand has led to the local generation and storage of power (Micro Grid systems). For its adoption, we need to implement smart grid architecture. Power electronics is a technologically sound way to limit different kinds of power quality (PQ) disturbances. It can also be used to control power flow, boost energy transmission capacity, enhance dynamic behavior and voltage stability, and ensure better power quality at distribution within established bounds. Unified Power Quality Conditioners (UPQC), one of the well-known Flexible AC Transmission System (FACTS) devices, are typically used to address problems in distribution systems such as voltage surges, flickers, neutral current reduction, and PQ. Additionally, thermal management is crucial for maintaining system stability and preventing overheating. While dealing with sensitive loads, a UPQC injects harmonics into the system, which can compromise system stability. This article describes an artificial neural network with harmonics elimination techniques for a modified UPQC connected with a Smart Grid. The performance of the proposed system is evaluated using MATLAB/Simulink software.

Multi-objective parameter design and economic analysis of VSG-controlled hybrid energy systems in islanded grids

Photovoltaic (PV) systems offer cost-effective power solutions for outlying islands but often compromise system stability due to reduced inertia. This study introduces a Virtual Synchronous Generator (VSG) control strategy, integrated with Energy Storage Systems (ESS) and PV, to enhance system inertia. By optimizing coordination between these energy sources, the proposed method mitigates oscillations and improves grid stability. However, PV-VSG systems are generally not favored by energy providers due to the requirement for pre-curtailment of power output. To address this, the paper proposes a parameter design method for VSG control of ESS and PV, utilizing multi-objective genetic algorithm (MOGA) optimization to simultaneously increase the frequency nadir and minimize the settling time after disturbances. Additionally, an adaptive curtailment decision and parameter design method based on artificial neural networks is introduced to enhance the feasibility of PV-VSG systems by reducing PV pre-curtailment and prioritizing PV power release and ESS charging during frequency oscillations. Real data from the Penghu Archipelago in Taiwan are used to build a dynamic model in DIgSILENT, enabling interaction with MOGA. The Value at Risk (VaR) method with dual stochastic variables is employed to assess the allowable PV installed capacity. The results show that when VaR is set at 1%, the proposed PV-VSG method can increase PV penetration by 57.5% compared to scenarios without VSG. Furthermore, compared to traditional PV-VSG methods, the proposed approach achieves a 16.8% increase in PV penetration and reduces annual PV curtailment by 25 MWh. This study also evaluates the economic impact of planners choosing different risk levels, offering valuable insights for grid development in remote or island regions.

Enhancing Renewable Energy-Grid Integration by Optimally Placed FACTS Devices: The Nigeria Case Study

Integrating renewable energy sources into existing power grids presents considerable challenges, especially with the intermittency of wind and solar power. This issue is particularly acute in developing countries like Nigeria, where grid infrastructure is often weak, significantly limiting the potential for RE penetration. This study explores strategies to enhance RE integration in Nigeria by employing Flexible Alternating Current Transmission System (FACTS) devices. By leveraging the reactive-power sensitivity index through modal analysis, the optimal location for the FACTS device can be determined. Analysis of the Nigerian power grid demonstrates that the deployment of FACTS devices, specifically Static Synchronous Compensators (STATCOMs), can increase the penetration limit of RE by 40%. This enhancement allows for the integration of an additional 152 MW of wind energy without compromising system stability. The findings underscore the potential of FACTS devices to improve voltage profiles and overall grid stability, thereby facilitating a higher integration of renewable energy sources into weak grids without necessitating substantial changes to the existing power system architecture. This solution can help Nigeria and other countries with similar infrastructure challenges to overcome their renewable energy integration hurdles and transition towards a more sustainable, reliable, and resilient energy mix, paving the way for a cleaner and greener future.

Optimal demand response scheduling and voltage reinforcement in distribution grids incorporating uncertainties of energy resources, placement of energy storages, and aggregated flexible loads

Instead of expanding power plant capacities, which is an extremely expensive investment option, demand response offers an economical solution to the challenges arising from the variability and intermittency of the renewable energy resources and demand variations, particularly during demand peak periods. This paper proposes a multi-objective optimization framework for the optimal power flow problem that integrates a stepwise demand response involving flexible and aggregated loads. The process includes short-term demand forecasting using long short-term memory (LSTM) networks in a smart distribution grid, followed by the optimal allocation of energy storage systems, and load aggregators. By determining the optimal solution point of the multi-objective problem analytically, significant system costs and peak demand can be reduced without compromising system stability. Through numerical studies for a sample study case, a reduction of 22% in system costs, 2% in total voltage variation, and 10% in peak demand is observed for a negligible impact on customers’ convenience.

Fungal, but not bacterial, diversity and network complexity promote network stability during roadside slope restoration

To restore degraded roadside ecosystems, conventional methods such as revegetation and soil amendment are frequently employed. However, our understanding of the long-term effects of these restoration approaches on soil microbial diversity and network complexity across different vegetation types remains poor, which contributes to poor restoration outcomes. In this study, we explored the effects of roadside slope restoration on microbial communities across different vegetation types at varying stages of restoration. We found that restoration time had a more pronounced impact on microbial diversity than specific vegetation type. As restoration progressed, microbial network complexity and fungal diversity increased, but bacterial diversity declined, suggesting that keystone taxa may contribute to network complexity. Interestingly, bacterial network complexity increased concomitant with decreasing network modularity and robustness, which may compromise system stability. Distinct vegetation types were associated with restoration-sensitive microbial communities at different restoration stages. Leguminouse and nitrogen-fixing plants, such as Albiziak alkora, Ginkgo biloba, Rhus chinensis, Rhapis excels, and Rubia cordifolia exhibited such associations after five years of restoration. These keystone taxa included Proteobacteria, Actinobacteria, Chloroflexi, Gemmatimonadota, and Myxococcota. We also found that bacterial alpha diversity was significantly correlated with restoration time, soil pH, moisture, available phosphate, nitrate nitrogen, and plant height, while fungal diversity was primarily shaped by restoration time. Together, our findings suggest that soil properties, environmental factors, vegetation type, and dominant species can be manipulated to guide the trajectory of ecological recovery by regulating the abundance of certain microbial taxa.

Diagnosing grid’s service quality issues: the virtual microgrid and the digitization and innovations in the power distribution grid.

Power quality issues from small and medium-sized grid-integrated solar photovoltaic systems (PMGD), whose plant capacity is less than or equal to 9 MW, challenge electric power distribution companies like ENEL Distribución S.A. in Chile. To tackle these challenges, leveraging rapidly configurable, scalable, and easily deployable distributed energy resources (DER) through a virtual power plant (VPP) is crucial. This paper introduces a "virtual microgrid," a specific VPP design and functional specification that swiftly diagnoses and resolves power quality issues. Virtual power plants use renewable energy sources, energy storage, and smart energy management to provide ancillary services to the grid. With the expanding PMGD market in Chile and globally, there is an urgent need for deployable DER to energize feeder sub-sections during reliability events and create grid pathways between DER and loads. Thus, DER are essential for enhancing grid flexibility, reliability, and maintaining the stability and integrity of electric supply quality standards. VPPs can reduce high costs associated with utility grid power capacity deficiencies in areas with unstable power supply, enhancing resilience and flexibility without compromising system stability. This study presents a novel approach—currently at the conceptual development stage—for diagnosing service quality issues related to grid supply through the rapid deployment of a configurable and fully scalable virtual microgrid. This solution is particularly relevant for zones in Santiago, Chile, where ENEL Chile faces challenges due to the increasing presence of PMGD—independent solar farms injecting all their production into the grid for profit, as permitted by current Chilean electric law (N°88/2019 of Ministry of Energy). Such practices negatively impact grid service quality standards, which can be mitigated through the deployment of virtual microgrids. The concept of a "virtual microgrid" emphasizes rapid configurability, scalability, and ease of deployment, tailored to address specific grid quality issues. Unlike previous efforts, this approach focuses on seamlessly integrating DER with existing grid infrastructure to quickly address and mitigate power quality issues caused by PMGD.

GPI observer-based active disturbance rejection control for a morphing quadrotor

Quadrotors are widely used in transportation, aerial photography, agricultural protection, and other important fields. Nevertheless, quadrotors with a fixed structure will face great challenges when crossing through or entering narrow spaces for operations. To improve quadrotor crossing ability in different environments, a morphing quadrotor is designed in this paper, and four servo motors are added to independently change four arm rotation angles. Meanwhile, the dynamic model and dynamic control allocation matrix are established. In addition, considering that the internal dynamic variation caused by morphologic changes and external disturbances may compromise system stability, a control method based on the generalized proportional integral (GPI) observer is proposed to increase the system robustness, and the corresponding stability analysis is provided. Finally, simulation results demonstrate the effectiveness of the proposed GPI observer-based active disturbance rejection control method.

High-Damped Complex Vector Current Regulator for PMSM Based on Active Damping Function

The complex vector current regulator (CVCR) has been widely used in high-performance PMSM drives because of its simple structure and excellent decoupling property. However, the CVCR's disturbance rejection ability is insufficient due to the plant's low-dynamic and poorly damped pole. To address such problem, an active resistance compensation is requisite. This article proposes a high-damped complex vector (HDCV) current regulator. By reconstructing the damping structure, it improves the characteristic of the conventional active resistance complex vector (ARCV) regulator. The eigenvalues of disturbance rejection function of HDCV achieve the higher natural angular frequency and damping ratio. The frequency response demonstrates that HDCV outperforms ARCV in disturbance rejection under similar noise suppression conditions. It also achieves the extended damping coefficient range without compromising system stability. To broaden HDCV's applications, an improved current predictor based on extended state observer is introduced in the damping function, ensuring superior regulation performance even at low sampling frequencies. The experimental results validate the correctness of damping compensation method and demonstrate the superiority of the proposed scheme over conventional methods.

Grid-forming control of doubly-fed induction generators based on the rotor flux orientation

The increasing penetration of renewable energies in power systems demands new services from renewable generation plants. System operators are concerned about system stability since renewable generators behave as constant power sources. Therefore, new requirements have been imposed to grid-following generators to improve their contribution to system stability acting as grid-supporting generators. Nevertheless, grid-supporting control can still compromise system stability for high penetration of renewables, and grid-forming control has arised to ensure proper operation. This paper proposes a novel grid-forming control scheme for doubly-fed induction generators, so they behave as real voltage sources. The proposed grid-forming control is based on the rotor flux orientation to a reference axis obtained from the emulation of the synchronous generator swing equation. The rotor flux is oriented to the reference axis by means of a flux controller that also controls the flux magnitude. The flux orientation in turn allows to control the doubly-fed induction generator torque, while the flux magnitude control allows to regulate the generator reactive power or terminal voltage. The proposed control system has been validated through a comprehensive real-time simulation with hardware in the loop, assessing its grid-forming capability. Moreover, small signal analysis has also been performed to assess system stability.

Passivity-Based Design of a Fractional-Order Virtual Capacitor for Active Damping of Multiparalleled Grid-Connected Current-Source Inverters

Current-source inverters (CSIs) have advantages, such as voltage boosting capability and direct current controllability, in high-power conversion applications with low switching frequency. However, inadequate damping of the passive <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$CL$</tex-math></inline-formula> filter gives rise to low-order harmonic resonance. The recent research regarding active damping techniques generally focuses on resonance mitigation of single grid-connected inverters. However, multiple resonances that arise from dynamic interactions among paralleled grid-connected inverters compromise system stability and power quality. This article presents the delay-dependent passivity-based analysis and design of a lossless fractional-order virtual capacitor for resonance damping of multiparalleled grid-connected CSI-based systems. Fractional-order capacitors provide a higher degree of freedom that enhances the frequency behavior and robustness of the control. Simulation and experimental results demonstrate the effectiveness of the proposed active damping control even with variations in the grid impedance and the number of paralleled CSIs.

Modified Second Order Generalized Integrator-frequency Locked Loop Grid Synchronization for Single Phase Grid tied System Tuning and Experimentation Assessment

The phase-locked loop (PLL) is applied in grid-tied systems to synchronise converter operation with grid voltage, affecting converter stability and performance. Synchronous reference frame PLL (SRF-PLL) is a popular grid synchronisation method due to its simplicity and reliability. Normal SRF-PLL cannot suppress DC offset, causing basic frequency and phase oscillations.When a grid is irregular, its bandwidth should be reduced to ensure acceptable disturbance rejection without sacrificing detection speed. To enhance the phase-angle estimation speed and accuracy, the researchers modified structure by adding the pre/in-loop filter in advanced PLLs.The capacity to deliver improved dynamic response and reduced settling time without compromising system stability or the ability to eliminate disturbances is a major issue for PLLs. Among different control methods, SOGI-FLL (second-order generalised integrator-based frequency locked loop) had the best performance. It tracks grid voltage frequency precisely even when there is harmonics,voltage variations, frequency fluctuations, etc. In the event of a dc offset, the calculated frequency incorporates low frequency oscillations. A modified second-order generalised integrator frequency-locked loop (MSOGI-FLL) is presented in this work to address grid voltage anomalies of all types, including dc offset. Using the Waijung Block-set of MATLAB/Simulink, a Modified SOGI-FLL is realized and evaluated by applying abnormal grid voltage situations using a low-cost DSP-based STM32F407VGT microcontroller. The results demonstrate MSOGI-better FLL's performance in harsh circumstances.

Ancillary services in Great Britain during the COVID-19 lockdown: A glimpse of the carbon-free future

The COVID-19 pandemic led to partial or total lockdowns in several countries during the first half of 2020, which in turn caused a depressed electricity demand. In Great Britain (GB), this low demand combined with large renewable output at times, created conditions that were not expected until renewable capacity increases to meet emissions targets in coming years. The GB system experienced periods of very high instantaneous penetration of non-synchronous renewables, compromising system stability due to the lack of inertia in the grid. In this paper, a detailed analysis of the consequences of the lockdown on the GB electricity system is provided, focusing on the ancillary services procured to guarantee stability. Ancillary-services costs increased by £200m in the months of May to July 2020 compared to the same period in 2019 (a threefold increase), highlighting the importance of ancillary services in low-carbon systems. Furthermore, a frequency-secured scheduling model is used in the present paper to showcase the future trends that GB is expected to experience, as penetration of renewables increases on the road to net-zero emissions by 2050. Several sensitivities are considered, demonstrating that the share of total operating costs represented by ancillary services could reach 35%.

Autonomous reactive power support for smart photovoltaic inverter based on real-time grid-impedance measurements of a weak grid

A large share of renewable energy production is connected to a weak grid with significant grid impedance. The transmission impedance causes unintended flow of reactive power to grid, coupling the grid reactive power to the active power fed from the inverter. The reactive power causes transmission losses, strains the grid with reactive power requirements, and can even compromise system stability. Requirements on reactive power support were recently imposed on new photovoltaic inverters, which are often implemented with proportional power factor control or droop control for local voltage regulation. The present work proposes a method for real-time compensation of the unintended reactive power, which decouples the reactive power from the active power of a photovoltaic inverter. Based on real-time measurement of the grid impedance, the unintended reactive power is estimated and autonomously compensated in the inverter. The method removes the fluctuating reactive power component, while still permitting unrestricted manual control of the reactive power. Unlike conventional methods, the proposed method requires no prior knowledge on grid impedance values or delicate tuning. The method outperforms conventional power factor control even when the conventional method is tuned optimally with known grid inductance. The method is validated with simulations and experiments on three-phase photovoltaic inverter connected to a weak grid.

Transient Analysis and Mitigation of Resonant Faults on Half-Wavelength Transmission Lines

This paper presents an analysis of resonant faults and their transient responses on half-wavelength lines. This type of transmission line has been studied for many years in countries that need alternatives for bulk power transmission over very long distances. An important issue for this technology is the occurrence of critical faults, which produce peculiar behavior in the main electrical entities and can jeopardize line insulation and compromise system stability. Here, the main factors influencing the severity of faults are analyzed: the type of fault and fault location. This paper shows that faults involving positive and negative sequences are the most critical when applied at specific regions and produce high voltage and power with a high rate of rise. The necessity for a mitigation method that removes this severe resonant fault condition until the operation of a protection system is discussed, and such a method is established. A method using two spark gaps with a new and improved location criterion is proposed, tested and evaluated, providing promising results for controlling voltage and power at terminal substations. Digital simulations are performed with PSCAD/EMTDC.

Detection and measurement of radio frequency feedback for an on‐frequency repeater

SummaryThe radio frequency feedback (RFF) occurs when the insulation is insufficient between the antennas of an on‐frequency repeater, increasing digital transmission errors. In addition, a strong RFF could compromise system stability of the on‐frequency repeater because of the growing power in the closed‐loop. Automatic gain control is widely used by the on‐frequency repeater to regulate the power, this solution being generally used with echo cancellation processes. Most of echo cancellation techniques are based on digital processing such as adaptive filters whose the effectiveness and the algorithm speed are depending on the signal frequency, the bandwidth and the closed‐loop parameters. This paper describes a solution of RFF estimation and detection regardless of the receiving signal modulation. By using the frequency scanning and the analysis of the power spectral density peaks in the system, this solution is reliable whatever are the values of the gain‐margin and the loop‐delay. Simulations and experimental implementation using field‐programmable gate array validate the solution. In addition, an example of applications is given in the context of the interference cancellation.

&lt;italic&gt;LCL&lt;/italic&gt;-Filter Design for Robust Active Damping in Grid-Connected Converters

Grid-connected converters employ LCL-filters, instead of simple inductors, because they allow lower inductances while reducing cost and size. Active damping, without dissipative elements, is preferred to passive damping for solving the associated stability problems. However, large variations in the grid inductance may compromise system stability, and this problem is more severe for parallel converters. This situation, typical of rural areas with solar and wind resources, calls for robust LCL-filter design. This paper proposes a design procedure with remarkable results under severe grid inductance variation. The procedure considers active damping using lead-lag network and capacitor current feedback. Passive damping is also discussed. The design flow, with little iteration and no complex algorithms, selects the proper ratios between the switching and resonance frequency, the grid and converter inductance, and the filter capacitance and total inductance. An estimation for the grid current total harmonic distortion (THD) is also proposed. Simulation and experiments validate the proposals.

Fay

Fay is a flexible platform for the efficient collection, processing, and analysis of software execution traces. Fay provides dynamic tracing through use of runtime instrumentation and distributed aggregation within machines and across clusters. At the lowest level, Fay can be safely extended with new tracing primitives, including even untrusted, fully optimized machine code, and Fay can be applied to running user-mode or kernel-mode software without compromising system stability. At the highest level, Fay provides a unified, declarative means of specifying what events to trace, as well as the aggregation, processing, and analysis of those events. We have implemented the Fay tracing platform for Windows and integrated it with two powerful, expressive systems for distributed programming. Our implementation is easy to use, can be applied to unmodified production systems, and provides primitives that allow the overhead of tracing to be greatly reduced, compared to previous dynamic tracing platforms. To show the generality of Fay tracing, we reimplement, in experiments, a range of tracing strategies and several custom mechanisms from existing tracing frameworks. Fay shows that modern techniques for high-level querying and data-parallel processing of disagreggated data streams are well suited to comprehensive monitoring of software execution in distributed systems. Revisiting a lesson from the late 1960s [Deutsch and Grant 1971], Fay also demonstrates the efficiency and extensibility benefits of using safe, statically verified machine code as the basis for low-level execution tracing. Finally, Fay establishes that, by automatically deriving optimized query plans and code for safe extensions, the expressiveness and performance of high-level tracing queries can equal or even surpass that of specialized monitoring tools.