Robust Frequency Research Articles

Robust Distributed Load Frequency Control for Multi-Area Power Systems with Photovoltaic and Battery Energy Storage System

The intermittent power generation of renewable energy sources (RESs) interrupts the balance between power generation and demand load due to the increased frequency fluctuation, which challenges the frequency stability analysis and control synthesis of power generation systems. This paper proposes a robust distributed load frequency control (DLFC) scheme for multi-area power systems. Firstly, a multi-area power system is constructed by integrating photovoltaic (PV) and battery energy storage systems (BESSs). Then, by employing the linear matrix inequality (LMI) technique, the sufficient condition capable of ensuring that the proposed controller satisfies H∞ robust performance in the sense of asymptotic stability is derived. Finally, testing is conducted on a four-area renewable power system, and results verify the strong robustness of the proposed controller against load disturbance and intermittence of RESs.

A Field-Programmable Gate Array-Based Quasi-Cyclic Low-Density Parity-Check Decoder with High Throughput and Excellent Decoding Performance for 5G New-Radio Standards

This work presents a novel fully parallel decoder architecture designed for high-throughput decoding of Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) codes within the context of 5G New-Radio (NR) communication. The design uses the layered Min-Sum (MS) algorithm and focuses on increasing throughput to meet the strict needs of enhanced Mobile BroadBand (eMBB) applications. We incorporated a Sub-Optimal Low-Latency (SOLL) technique to enhance the critical check node processing stage inherent to the MS algorithm. This technique efficiently computes the two minimum values, rendering the architecture well-suited for specific Ultra-Reliable Low-Latency Communication (URLLC) scenarios. We design the decoder to be reconfigurable, enabling efficient operation across all expansion factors. We rigorously validate the decoder’s effectiveness through meticulous bit-error-rate (BER) performance evaluations using Hardware Description Language (HDL) co-simulation. This co-simulation utilizes a well-established suite of tools encompassing MATLAB/Simulink for system modeling and Vivado, a prominent FPGA design suite, for hardware representation. With 380,737 Look-Up Tables (LUTs) and 32,898 registers, the decoder’s implementation on a Virtex-7 XC7VX980T FPGA platform by AMD/Xilinx shows good hardware utilization. The architecture attains a robust operating frequency of 304.5 MHz and a normalized throughput of 49.5 Gbps, marking a 36% enhancement compared to the state-of-the-art. This advancement propels decoding capabilities to meet the demands of high-speed data processing.

Robust load frequency control in interval power systems via reduced-order generalized active disturbance rejection control

Abrupt load changes, structural discrepancies, and parametric uncertainties cause degraded performance of the high-order power systems. This situation creates a problematic endeavor while analyzing the performance of such high-order systems. Hence, a simple and efficient lower-order control methodology can be deployed to sort out the issues related to load frequency control (LFC) in such systems. This study resolves the LFC problem in parametric bounded power systems by developing a worst-case reduced-order generalized active disturbance rejection control (WRGADRC) method. The core concept of the proposed technique entails that a controller will perform well in nominal scenarios if it performs satisfactorily in worst-case conditions. Therefore, an interval system’s worst-case reduced-order model is first obtained from its different uncertain models; the reduced order controller is then designed using the GADRC technique. The proposed scheme is rigorously validated on various parametric bounded minimum and non-minimum phase single-area and multi-area power systems, instilling confidence in its ability to achieve minimum frequency deviation in multiple scenarios. The supremacy of the proposed scheme is highlighted over some well-established control techniques in the literature related to the LFC problem.

Uncertainty in Fourier Transforms: A Fuzzy Logic Perspective

This study explores the integration of fuzzy logic with Fourier transforms to address the challenges of uncertainty, noise, and imprecision in real-world data. Fuzzy Fourier transforms extend traditional Fourier methods by incorporating fuzzy numbers, allowing for more robust frequency analysis, signal processing, and data reconstruction, particularly in noisy or incomplete datasets. The study examines the mathematical formulation of fuzzy Fourier transforms, computational trade-offs, and their performance advantages in comparison to classical Fourier methods. Real-world applications are discussed, including signal processing, image reconstruction, and time-series forecasting. Furthermore, the research highlights the increased computational complexity associated with fuzzy methods, the challenges of interpreting fuzzy results, and the limitations of handling probabilistic uncertainty. Future directions include the development of multi-dimensional fuzzy Fourier transforms, hybrid models integrating machine learning, and quantum computing applications. These advancements have broad implications for fields such as telecommunications, medical imaging, and financial forecasting, where handling uncertainty is critical.

Appraising the Determinants and Outcomes of Islamic Financial Literacy through the Lens of a Systematic Literature Review

This research illuminates the determinants and outcomes of Islamic financial literacy as scrutinized in prior investigations. A systematic literature review unfolded across the Scopus database from 2016 to 2023. This investigation encompasses 22 articles from the 40 scholarly works extracted from the Scopus database. The Journal of Islamic Accounting and Business Research emerges as the most prolific disseminator of insights into the determinants and outcomes of Islamic financial literacy, credited to its robust publication frequency throughout the year. The autonomous and reliant facets of Islamic financial literacy were predominantly studied, with emphasis not only on individual dynamics but also on business perspectives. The determinants instigating Islamic financial literacy congregate within the affective, conative, family influence, self-controlled, and demographic predictors. Conversely, the ramifications stemming from Islamic financial literacy manifest in cognitive, affective, and conative dimensions, leaving an indelible imprint on the business realm. Geographic focus reveals a concentration of prior investigation within Muslim-majority nations, predominantly Indonesia. Furthermore, the investigation discovers that past studies were mainly conducted in the context of Islamic banking. The evidence from the present study provides input to researchers in conducting further research on Islamic financial literacy.

Optimal and Robust Load Frequency Control for Hybrid Power System Integrated with Energy Storage Device by Sine Cosine Algorithm

Optimal and Robust Load Frequency Control for Hybrid Power System Integrated with Energy Storage Device by Sine Cosine Algorithm

Achieving high energy storage density and charge-discharge performance via high-energy ball milling combined with two-step sintering

In this study, the microstructure, ferroelectricity, energy storage density, and charge-discharge characteristics of 0.95(K0.5Na0.5)NbO3-0.05Ba(Zn1/3Nb2/3) (0.95KNN-0.05BZN) ceramic, fabricated by combining two-step sintering with high-energy ball milling, were investigated. The two-step sintering technique enabled a wide sintering temperature range of 1020–1120 °C for the ceramic. Accordingly, under optimal sintering conditions, the ceramic exhibited high relative density (98.1 %) and nanoscale grain size (<90 nm). The samples also displayed excellent pulse power performance at room temperature with a high recoverable energy storage density (Wrec) of 3.1 J/cm3, along with the following charge-discharge parameters: current density (CD), power density (PD), and discharge time (t0.9) reached 1821.7 cm−3, 227.7 MW/cm3, and 36.8 ns, respectively. The ceramic also obtained robust frequency stability (10–1000 Hz), good temperature stability (30–130 °C), and outstanding fatigue resistance (105 cycles), indicating its potential application in improved pulse capacitor materials.

Robust fractional-order load frequency control for hybrid power system concerning high wind penetration

Hybrid power systems concerning wind farms have witnessed significant dynamic characteristic changes due to unpredicted generation output and integration mode conversion between frequency-sensitive wind plants and non-scheduled ones. This work presents a robust fractional-order load frequency control (LFC) method for a multi-area hybrid power system in the presence of wind penetration uncertainties. To characterize the injection effect of wind farms, the power system is described by a model with an uncertain wind penetration factor in a pre-estimated range. Then, an enhancement of Levy’s identification method is developed to convert this model into a fractional-order reduced structure to design the load frequency controller, which is in a form of fractional-order PID with a filter for ease of engineering implementation. The closed-loop stability is analyzed by the stability boundary locus (SBL) method under different wind penetration levels. It is shown that superior frequency response performance and system robustness can be obtained if the controller is designed in terms of the model with the worse-case wind penetration. Illustrative examples including a three-area hybrid power system under a variety of wind penetration variations are given to show the effectiveness of the proposed method.

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.

Robust post-processing time frequency technology and its application to mechanical fault diagnosis

Post-processing synchrosqueezing transform and synchroextracting transform methods can improve TFR resolution for fault diagnosis. The normal and fault signal can be described by infinite variance process, and 1 < α ≤ 2, even the background noise belongs to the process under complex conditions. The effect of traditional SST and SET methods is greatly reduced and even lost in infinite variance process environment. Several robust post-processing methods are proposed including FSET, FSSET, FSOSET and FMSST technology employing infinite variance process statistical model and FLOS, and their mathematical derivation are completed in this paper. The proposed methods are compared with the conventional methods, and the results show that the proposed methods achieve better results than the existing methods. In addition, the new methods are applied to diagnose the bearing outer race DE signals polluted by infinite variance process, the result demonstrates that they have performance advantages. Finally, the characteristics, shortcomings and application scenarios of the improved algorithms are summarized.

Intelligent Transition Mechanisms in 5G DSA: A Logistic Regression Approach to Reuse Factor Adaptation

This research work use Dynamic Spectrum Allocation (DSA) embedded in 5G technology and logistic regression as Machine learning tool to alter the reuse factor of assigned telecommunication frequency to a more robust and reliable frequency. The switch from a frequency reuse of 3 (FR3) to a frequency reuse of 7 (FR7) was considered. Historical data generated from a Telecommunications Company in Nigeria was utilised. This data consist of User throughput and the number of user equipment to assess traffic load and congestion from user equipment (UE).The ideal was meant to determine the probability at which a switch or transition between reuse factors will occur. With a resolution threshold of 50 users which was set to commence the shift from reuse factor of 3 when the number of users have reached its threshold of 50 to reuse factor of 7 when the number of users exceeds 50 and above. The objective of this combination is to increase spectrum utilisation efficiency and network flexibility, by optimising spectrum resources in densely populated urban areas. This study explains the mechanisms and also demonstrate how logistic regression with DSA will enhance network capacity of wireless communication systems. The logistic regression model proved effective in making intelligent decisions regarding the transition from reuse factor 3 to reuse factor 7 as it was able to accommodate up to 79 users as against the threshold value of 50 users when running under the reuse factor of 3. With a high accuracy of 91.9% and balanced precision-recall values, it showcased its ability to optimize spectral efficiency.

Textile Bandwidth-Enhanced Half-Mode Substrate-Integrated Cavity Antenna Based on Embroidered Shorting Vias.

A textile bandwidth-enhanced half-mode substrate-integrated cavity (HMSIC) antenna based on embroidered shorting vias is designed. Based on the simulated results of the basic HMSIC antenna, two embroidered hollow posts with square cross-sections are added as shorting vias at the intersections of the zero-E traces of the TM210HM and TM020HM modes to shift the TM010HM-mode band to merge with the bands of the higher-order modes for bandwidth enhancement. A prototype is practically fabricated based on computerized embroidery techniques. Measurement results show that the prototype is of an expanded -10 dB impedance band of 4.87~6.17 GHz (23.5% fractional bandwidth), which fully covers the 5 GHz wireless local area network (WLAN) band. The simulated radiation efficiency and maximum gain of the proposed antenna are above 97% and 7.6 dBi, respectively. Furthermore, simulations and measurements prove its robust frequency response characteristic in the proximity of the human tissues or in bending conditions, and the simulations of the specific absorption rate (SAR) prove its electromagnetic safety on the human body.

Resilient robust model predictive load frequency control for smart grids with air conditioning loads

AbstractThis paper investigates the robust model predictive load frequency control problem for smart grids with wind power under cyber attacks. To accommodate intermittent power generation, the demand response of the system is considered by involving the air conditioning loads in the frequency regulation. In addition, the system uncertainties produced by the air conditioning load users and wind turbines when replacing traditional generator sets are considered. By using the cone complementary linearization algorithm and the linear matrix inequality technique, a resilience robust model predictive control strategy with mixed performance indexes is proposed. Furthermore, a rigorous derivation of the recursive feasibility of robust model predictive control is given. Finally, the simulation results of the two‐area load frequency control scheme show that the proposed model predictive control strategy is capable of realizing the load frequency control of the multi‐area smart grid and is robust to the parameter uncertainties and frequency regulation of the system. The results also show that the proposed model predictive control strategy has some resistance to cyber attacks and external disturbances.

Robust Symbol and Frequency Synchronization Method for Burst OFDM Systems in UAV Communication

This paper introduces a robust synchronization method for orthogonal frequency division multiplexing (OFDM) in multi-unmanned aerial vehicle (UAV) communication systems, focusing on minimizing overhead while achieving reliable synchronization. The proposed synchronization scheme enhances both frame efficiency and implementation simplicity. Initially, a high-efficiency frame structure is designed without a guard time interval, utilizing a preamble sequence to simultaneously achieve both symbol synchronization and automatic gain control (AGC) before demodulation. Subsequently, a novel 2-bit non-uniform quantization method for the Zadoff–Chu sequences is developed, enabling the correlation operations in the traditional symbol synchronization algorithm to be implemented via bitwise exclusive OR (XOR) and addition operations. The complexity of hardware implementation and the energy consumption for symbol synchronization can be reduced significantly. Furthermore, the impact of AGC on frequency synchronization performance is examined, and an improved frequency synchronization method based on AGC gain compensation is proposed. Finally, the performance of the proposed method is rigorously analyzed and compared with that of the traditional method through computer simulations, demonstrating the effectiveness and superiority of the proposed approach.

Frequency regulation controller for multi‐area interconnected power system

AbstractBy increasing the number of electric vehicles (EVs) to achieve a less carbon environment, not only they consume power from the grid to be charged, but also do they deliver power to the grid, and this can play a significant role in load frequency control. However, EVs take part in frequency regulation based on their state of charge (SoC) which will cause uncertainties. In order to manage these uncertainties, EV aggregator (EVA) concept has been introduced. The EV owner participates in the demand response program provided by the EVA arbitrarily considering her/his requirements. Accordingly, EVA calculates the up and down power reserve for the power system operator. Following any frequency deviation, EVA sends the proper commands to each EV to consume or to inject power to the system. There are also communication delays between different parts, uncertainties, and non‐linearities that existed in the power system. To overcome these issues, this study proposes a new robust load frequency controller based on feedback theory and artificial neural network which is designed through the non‐linear multi‐machine power system. Simulation results on IEEE 39‐bus power system show that the proposed controller regulates frequency more desirably in comparison with other methods.

Robust textile-based spoof plasmonic frequency scanning antenna for on-body IoT applications

Robust textile-based spoof plasmonic frequency scanning antenna for on-body IoT applications

Robust finite frequency control for MRF damper-based semi-active suspension systems subject to time delay and hysteresis nonlinearity

Robust finite frequency control for MRF damper-based semi-active suspension systems subject to time delay and hysteresis nonlinearity

Robust frequency control based on sliding mode control with LMI in an island microgrid

Robust frequency control based on sliding mode control with LMI in an island microgrid

GFRENet: An Efficient Network for Underwater Image Enhancement with Gated Linear Units and Fast Fourier Convolution

Underwater image enhancement is critical for a variety of marine applications such as exploration, navigation, and biological research. However, underwater images often suffer from quality degradation due to factors such as light absorption, scattering, and color distortion. Although current deep learning methods have achieved better performance, it is difficult to balance the enhancement performance and computational efficiency in practical applications, and some methods tend to cause performance degradation on high-resolution large-size input images. To alleviate the above points, this paper proposes an efficient network GFRENet for underwater image enhancement utilizing gated linear units (GLUs) and fast Fourier convolution (FFC). GLUs help to selectively retain the most relevant features, thus improving the overall enhancement performance. FFC enables efficient and robust frequency domain processing to effectively address the unique challenges posed by the underwater environment. Extensive experiments on benchmark datasets show that our approach significantly outperforms existing state-of-the-art techniques in both qualitative and quantitative metrics. The proposed network provides a promising solution for real-time underwater image enhancement, making it suitable for practical deployment in various underwater applications.

Frequency security-constrained unit commitment with fast frequency support of DFIG-based wind power plants

The integration of inverter-based renewable energy sources into power grids presents a unique challenge: a reduction in grid inertia, leading to potential frequency stability issues. This paper introduces an innovative approach to address this challenge, focusing on the dynamic role of wind power plants equipped with dual-fed induction generators (DFIG). Unlike traditional methods that rely on fixed inertia control strategies and wind power droop coefficients, our method offers a dynamic solution tailored to the fluctuating nature of grid frequency dynamics. We propose a novel variable inertia support mechanism, coupled with an optimized power point tracking control and strategic reserve, to maximize the effective use of wind power reserves without waste. Additionally, we account for the inherent uncertainties in wind power generation, enhancing the frequency support capabilities of wind turbines through a fast frequency response strategy. A key feature of our approach is the application of an advanced piecewise linearization fitting method to establish a robust frequency nadir constraint. This is integrated into a two-stage robust frequency security-constrained unit commitment model, enabling optimal real-time decision making for frequency stability in wind power plants. The efficacy and practicality of our proposed method are verified through a detailed case study on a modified IEEE 39-bus system and a hardware-in-the-loop experiment. Compared with the traditional fixed parameter control method, the cost is reduced by approximately 0.42%, while the linearization error at frequency nadirs remains within the range of -4% to 1.5%.