Nominal Frequency Research Articles

Optimized Fractional Order Integral-Tilt Derivative Controller for Frequency Regulation of Interconnected Diverse Renewable Energy Resources

The interconnection of renewable energy systems, which are complex nonlinear systems, often results in power fluctuations in the interconnection line and high system frequency due to insufficient damping in extreme and dynamic loading situations. To solve this problem, load frequency control ensures nominal operating frequency and orderly fluctuation of grid interconnection power by delivering high-quality electric power to energy consumers through efficient and intelligent control systems. To introduce the frequency control of power systems, this paper presents a novel control technique of Fractional Order Integral-Tilt Derivative with Filter (FOI-TDN) controller optimized by the current soft computing technique of hybrid Sine-Cosine algorithm with Fitness Dependent Optimizer (hSC-FDO). For more realistic analysis, practical constraints with nonlinear features, such as controller dead band, communication time delay, boiler dynamics, and generation rate constraint are embedded in the given system model. The proposed approach outperforms some recently developed heuristic approaches such as fitness dependent optimizer, firefly algorithm, and particle swarm optimization for the interconnected power system of two areas with multiple generating units in terms of minimum undershoot, overshoot, and settling time. To improve the system performance, capacitive energy storage devices are used in each area and thyristor control phase shifter is used in the interconnection line of the power system. The potential of the hSC-FDO-based FOI-TDN is demonstrated by comparing it with conventional FOTID/FOPID/PID controllers for two areas with multiple power generators IPS. Finally, a robustness analysis is performed to determine the robustness of the presented control system by varying the system loads and system parameters.

Stable Reinforcement Learning for Optimal Frequency Control: A Distributed Averaging-Based Integral Approach

Frequency control plays a pivotal role in reliable power system operations. It is conventionally performed in a hierarchical way that first rapidly stabilizes the frequency deviations and then slowly recovers the nominal frequency. However, as the generation mix shifts from synchronous generators to renewable resources, power systems experience larger and faster frequency fluctuations due to the loss of inertia, which adversely impacts the frequency stability. This has motivated active research in algorithms that jointly address frequency degradation and economic efficiency in a fast timescale, among which the distributed averaging-based integral (DAI) control is a notable one that sets controllable power injections directly proportional to the integrals of frequency deviation and economic inefficiency signals. Nevertheless, DAI does not typically consider the transient performance of the system following power disturbances and has been restricted to quadratic operational cost functions. This paper aims to leverage nonlinear optimal controllers to simultaneously achieve optimal transient frequency control and find the most economic power dispatch for frequency restoration. To this end, we integrate reinforcement learning (RL) to the classic DAI, which results in RL-DAI control. Specifically, we use RL to learn a neural network-based control policy mapping from the integral variables of DAI to the controllable power injections which provides optimal transient frequency control, while DAI inherently ensures the frequency restoration and optimal economic dispatch. Compared to existing methods, we provide provable guarantees on the stability of the learned controllers and extend the set of allowable cost functions to a much larger class. Simulations on the 39-bus New England system illustrate our results.

Performance Analysis of PWM Based Full Wave Bridge Inverter

Abstract: An obvious device for the utilization of renewable energy sources is inverter and Pulse Width Modulation technique is widely used method for voltage source inverters. This paper deals with the generation of PWM signals by analog circuit, where the comparison of sine wave and sawtooth wave for the operation of power circuit takes place. The above mentioned technique is studied and verified by Simulating the circuit. The prototype of PWM based, single phase, full bridge inverter is developed and the results are verified for the nominal voltage and frequency with the help of simulation and hardware is designed. Keywords: Inverter, SPWM, VSI, Simulation, MATLAB

Characterizing power transformer frequency responses using bipolar pseudo-random current impulses

The behaviour of a power transformer is complex and difficult to predict during transient conditions or during operation at frequencies below or above its nominal frequency, a phenomenon common in renewable energy plants due to harmonic distortion. Furthermore, the accuracy of a power system simulation depends on the models of critical subsystems such as the power transformers. This paper presents the use of a unique excitation waveform comprising of pseudo-random current impulses to accurately identify the wideband characteristics of a power transformer. By injecting the excitation waveform to the relevant transformer terminals, frequency responses are determined by cross-correlation of the perturbation signal, and the measured response. Compared to the traditional transformer identification methods, the pseudo-random current impulses offer a wideband excitation with a higher degree of controllability such that its spectral energy can be focused in the frequency band of interest. The proposed method was investigated on a 16 kVA, 22 kV/240 V single-phase transformer. The obtained wideband frequency responses provide useful information in harmonic penetration and over-voltage studies and are also used to estimate, with a high degree of accuracy, the lumped parameters of the equivalent transformer broadband circuit model.

A new approach to three-phase asynchronous motor model for electric power system analysis

In this paper, a new steady-state model of a three-phase asynchronous motor is proposed to be used in the studies of electrical power systems. The model allows for obtaining the response of the demand for active and reactive power as a function of voltage and frequency. The contribution of the model is the integration of the characteristics of the mechanical load that can drive motors, either constant or variable load. The model was evaluated on a 2500 kW and 6000 V motor, for the two types of mechanical load, in a wide range of voltage and frequency, as well as four load factors. As a result of the evaluation, it was possible to verify that, for the nominal frequency and voltage variation, the type of load does not influence the behavior of the powers and that the reactive power is very sensitive to the voltage variation. In the nominal voltage and frequency deviation scenario, it was found that the type of load influences the behavior of the active and reactive power, especially in the variable load. The results demonstrate the importance of considering the model proposed in the simulation software of electrical power systems.

Dynamic Harmonic Phasor Estimator Considering Frequency Deviation

The fundamental frequency of power system may deviate from the nominal value due to various reasons, such as load variation, subsynchronous resonance and fault occurrence. The maximum frequency deviation considered by the latest IEEE standard is 5 Hz. This paper proposes a dynamic harmonic synchrophasor estimator, which can accurately estimate the dynamic harmonic parameters even if the frequency deviation reaches 5 Hz. Multiple discrete frequencies are generated at a fixed frequency interval on both sides of the nominal frequency, and multiple dynamic harmonic filters are generated offline based on those frequencies. The windowed interpolation discrete Fourier transform is adopted for online monitoring of the fundamental frequency. According to the detected frequency, a harmonic filter, which is generated with the discrete frequency that is closest to the detected frequency, can be selected to analyze the dynamic harmonic synchrophasor, frequency and rate of change of frequency. The performances of the proposed estimator are verified through tests under various frequency deviation conditions, and the test results show that the proposed estimator can accurately estimate the dynamic harmonic parameters when the frequency deviation is within 5 Hz.

CHOOSING THE OPTIMUM FREQUENCY ESTIMATOR UNDER SYSTEM FREQUENCY DEVIATIONS IN POWER SYSTEMS

Parameter estimation in particular the frequency estimation of sinusoidal signals contaminated with noise is of great importance due to its broad applications in many fields such as communications, instrumentation, medicine and radar. In today’s power systems, frequency deviations in the nominal system frequency would cause spurious or so-called ghost frequency components in the spectrum. Those types of frequency components complicate the real-time tracking of harmonics and interharmonics present in the system. In this study, in order to minimize the side effects of system frequency deviations the performances of various frequency estimators are evaluated against varying fundamental frequency and noise conditions and the optimum estimator is chosen.

Distributed frequency restoration and SoC balancing control for AC microgrids

This paper develops an improved distributed finite-time control algorithm for multiagent-based ac microgrids with battery energy storage systems (BESSs) utilizing a low-width communication network. The proposed control algorithm can simultaneously coordinate BESSs to eliminate any deviation from the nominal frequency as well as solving state of charge (SoC) balancing problem. The stability of the proposed control algorithm is established using Lyapunov method and homogeneous approximation theory, which guarantees an accelerated convergence within a settling time that does not dependent on initial conditions. Based on this, to significantly reduce the communication burdens, an event-triggered communication mechanism is designed which can also avoid Zeno behavior. Then sufficient conditions on the event-triggered boundary are derived to guarantee the stability and reliability of the whole systems. Practical local constraints are imposed to implement the control protocol, and the theoretical results are applied to a test system consisting of five DGs and five BESSs, which verifies the effectiveness of the proposed strategy.

An Automated Approach for Electric Network Frequency Estimation in Static and Non-Static Digital Video Recordings.

Electric Network Frequency (ENF) is embedded in multimedia recordings if the recordings are captured with a device connected to power mains or placed near the power mains. It is exploited as a tool for multimedia authentication. ENF fluctuates stochastically around its nominal frequency at Hz. In indoor environments, luminance variations captured by video recordings can also be exploited for ENF estimation. However, the various textures and different levels of shadow and luminance hinder ENF estimation in static and non-static video, making it a non-trivial problem. To address this problem, a novel automated approach is proposed for ENF estimation in static and non-static digital video recordings. The proposed approach is based on the exploitation of areas with similar characteristics in each video frame. These areas, called superpixels, have a mean intensity that exceeds a specific threshold. The performance of the proposed approach is tested on various videos of real-life scenarios that resemble surveillance from security cameras. These videos are of escalating difficulty and span recordings from static ones to recordings, which exhibit continuous motion. The maximum correlation coefficient is employed to measure the accuracy of ENF estimation against the ground truth signal. Experimental results show that the proposed approach improves ENF estimation against the state-of-the-art, yielding statistically significant accuracy improvements.

Development of a Novel Ultrasonic Spectroscopy Method for Estimation of Viscosity Change during Milk Clotting.

Ultrasonic testing is an emerging non-destructive testing technology with high repeatability and precision. Milk is a very complex liquid and the change of its viscosity is a highly relevant property throughout conversion into other dairy products. In the following paper, we propose a novel method for the monitoring of viscosity during enzymatic milk clotting by ultrasonic spectroscopy. An ultrasonic transducer–receiver couple with a 250 kHz nominal frequency was submerged in the samples and an enveloped sweep (“chirp”) signal was applied in a through-transmission mode. Simultaneously, the change in viscosity was measured with a rotational viscometer at a constant shearing speed. The data were analyzed with an algorithm developed by the authors for spectral ultrasonic testing. Estimations yielded a high adjusted R2 (0.963–0.998) and low cross-validated estimation error (RPD: 4.38–14.22), suggesting that the method is suitable for industrial use given the right instrumentation.

Tinzaparin inhibits VL30 retrotransposition induced by oxidative stress and/or VEGF in HC11 mouse progenitor mammary cells: Association between inhibition of cancer stem cell proliferation and mammosphere disaggregation.

Tinzaparin is an anticoagulant and antiangiogenic drug with inhibitory properties against tumor growth. VEGF stimulates angiogenesis, while an association between reactive oxygen species (ROS) and angiogenesis is involved in tumor progression. The present study aimed to investigate the effect of tinzaparin on VL30 retrotransposition-positive mouse HC11 mammary stem-like epithelial cells, previously reported to be associated with induced mammosphere/cancer stem cell (CSC) generation and tumorigenesis. Under 24 h serum starvation, 15.2% nominal retrotransposition frequency was increased to 29%. Additionally, while treatment with 3–12 ng/ml VEGF further induced retrotransposition frequency in a dose-dependent manner (up to 40.3%), pre-incubation with tinzaparin (2 IU/ml) for 0.5–4 h reduced this frequency to 18.3% in a time-dependent manner, confirmed by analogous results in NIH3T3 fibroblasts. Treatment with 10–40 pg/ml glucose oxidase (GO) for 24 h induced HC11 cell retrotransposition in a dose-dependent manner (up to 82.5%), while a 3 h pre-incubation with tinzaparin (1 or 2 IU/ml) elicited a 13.5 or 25.5% reduction in retrotransposition, respectively. Regarding tumorigenic VL30 retrotransposition-positive HC11 cells, treatment with 2 IU/ml tinzaparin for 5 days reduced proliferation rate in a time-dependent manner (up to ~55%), and after 3 weeks, disaggregated soft agar-formed foci, as well as low-adherent mammospheres, producing single mesenchymal-like cells with a ~50% reduced retrotransposition. With respect to the VL30 retrotransposition mechanism: While 12 ng/ml VEGF increased the level of VL30 and endogenous reverse transcriptase (enRT) transcripts ~1.41- and ~1.16-fold, respectively, subsequent tinzaparin treatment reduced both endogenous/ROS- and VEGF-induced levels 1.15- and 0.40-fold (VL30) and 0.60- and 0.52-fold (enRT), respectively. To the best of our knowledge, these data demonstrate for the first time, the novel inhibition activity of tinzaparin against ROS- and VEGF-induced VL30 retrotransposition, and the proliferation and/or aggregation of mouse HC11 mammosphere/tumor-initiating CSCs, thus contributing to the inhibition of VL30 retrotransposition-induced primary tumor growth.

Automatic Generation Control of Multi-Source Interconnected Power System Using FOI-TD Controller

Automatic Generation Control (AGC) delivers a high quality electrical energy to energy consumers using efficient and intelligent control systems ensuring nominal operating frequency and organized tie-line power deviation. Subsequently, for the AGC analysis of a two-area interconnected hydro-gas-thermal-wind generating unit, a novel Fractional Order Integral-Tilt Derivative (FOI-TD) controller is proposed that is fine-tuned by a powerful meta-heuristic optimization technique referred as Improved-Fitness Dependent Optimizer (I-FDO) algorithm. For more realistic analysis, various constraints, such as Boiler Dynamics (BD), Time Delay (TD), Generation Rate Constraint (GRC), and Governor Dead Zone (GDZ) having non-linear features are incorporated in the specified system model. Moreover, a comparative analysis of I-FDO algorithm is performed with state-of-the-art approaches, such as FDO, teaching learning based optimization, and particle swarm optimization algorithms. Further, the proposed I-FDO tuned controller is compared with Fractional Order Tilt Integral Derivative (FOTID), PID, and Integral-Tilt Derivative (I-TD) controllers. The performance analysis demonstrates that proposed FOI-TD controller provides better performance and show strong robustness by changing system parameters and load condition in the range of  ± 50%, compared to other controllers.

Experimental investigation of the permanent deformation and void ratio attenuation of porous asphalt mixtures with hydraulic effects

To investigate the quantitative influence of the material gradation characteristics, saturation degree and loading frequency on the permanent deformation of porous asphalt (PA) mixtures under temperature, loading, and hydraulic coupling conditions, a hydraulic coupling repeated loading test is conducted for five types of PA mixtures with different nominal maximum aggregate sizes, void ratios, saturation degrees and load frequency inputs. The test results indicate that the PA-20 mixture has better anti-deformation performance than the PA-13 and PA-16 mixtures. A larger void ratio corresponds to weaker anti-permanent deformation performance. When the initial void ratio is 24%, the flow number prominently decreases to approximately less than 11% of the initial void ratio of 16%. The results of the loading test with water storage show that the saturation state has a more significant impact on the permanent deformation of PA-13 mixtures than PA-16 and PA-20. When the frequency increases, the cumulative microstrain of the mixture greatly decreases, and the influence degree of frequency on the deformation becomes increasingly obvious when the void ratio increases due to the effect of hydraulic coupling. To easily evaluate the void ratio attenuation of PA, a uniform expression is proposed to characterize the three-stage strain growth, which shows that the permanent deformation curve exhibits nonlinear growth in the second stage of deformation. Then, the minimum permanent deformation growth rate is presented to quantitatively evaluate the deformation resistance performance. Overall, a higher saturation degree of the lower loading frequency corresponds to a smaller PDGRmin. A formula is presented to analyse the effect of permanent deformation on the change in void ratio: the loading frequency, saturation degree and initial void ratio significantly affect the attenuation of the AV ratio. Specifically, the coupling of frequency and water storage slows the decrease in air void ratio.

Load frequency control of a diverse energy source integrated hybrid power system with a novel hybridized harmony search-random search algorithm designed Fuzzy-3D controller

ABSTRACT The manuscript addresses a robust three-dimensional fuzzy-PID controller (Fuzzy-3D PID) to control frequency of a diverse energy source integrated hybrid power system under various loadings. In order to obtain stability over system frequency under any disturbances, a secondary control loop called load frequency control (LFC) loop is required in the system. LFC tries to monitor power generation irrespective of load demand. Further, a novel hybridized harmony search and random search (hyHS-RS) algorithm is proposed to optimally design the suggested Fuzzy-3D PID controller. The proposed hybrid network is incorporated with integration of different diverse energy sources such as wind-plant (WP), solar-plant (SP), diesel-generator (DEG), and micro-turbine (MT) along with conventional power-generating sources like thermal system, hydro system, and nuclear power plant. The wind-plant and solar-plant exhibit large dynamics and low inertia which degrades the system frequency seriously. The proposed Fuzzy-3D PID controller makes necessary control actions over disturbed frequency and trying to amend steady nominal frequency in the system. It has been observed the percentage improvement in ITAE with proposed hyHS-RS over basic harmony search (HS) and random search (RS) are 54.5% and 201.6% respectively. Finally, proposed hyHS-RS designed Fuzzy-3D PID controller justifies its superiority through different comparative studies.

Evolution of the optimum ultrasonic testing frequency of alkali-activated soil–ash

Monitoring the curing process of mixtures produced by soil, fly ash and alkaline solution can be effectively performed by ultrasonic measurements of compression and shear wave velocities. These measurements detect the evolution of stiffness with time, as a result of alkali-activated ash reactions. Conventionally, ultrasonic testing relies on the use of a fixed input frequency, corresponding to the nominal frequency of the transducer, for which a maximum response is expected from the transducers. This procedure, however, has shown some limitations especially when applied to materials under curing, in which stiffness is changing with time. To overcome these limitations, a wide range of frequencies, from 24 to 200 kHz, was used at each of the selected curing periods for determining wave travel time, instead of a single frequency reading. The results show a clear increase in the optimum frequency with curing time, indicating that the ultrasound testing frequency should be adjusted to account for the stiffness increase due to curing. Additionally, the use of frequencies other than the nominal frequency of the ultrasonic transducers generated clearer signals, particularly at early curing periods.

재생에너지 기반 Hybrid 전력망의 주파수 추정

The frequency is one of the very important factors in power grid. It is essential that the frequency of a power grid should be maintained close to its nominal frequency. Recently, under the leadership of the government, interest in the expansion and distribution of renewable energy sources (RES) is increasing. Therefore, technology for stable operation in preparation for grid connection variability of RES is required. There is growing interest in the rapid measurement and accurate estimation of grid frequency for renewable energy monitoring and stability, using GPS based time-synchronous PMU (Phasor Measurement Unit) for wide area blackout prevention. In this paper, FRDWT (Fast Recursive Discrete Wavelet Transform), GCDFT (Gain Compensator Discrete Fourier Transform) and PAD (Phase Angle Difference) are selected as optimal frequency measurement methods for frequency estimation of hybrid power grid based on renewable energy. This study is to evaluate the performance of the proposed technique using domestic 345kV power grid model data by EMTP-RV S/W.

BCL6 controls contact-dependent help delivery during follicular T-B cell interactions

SummaryBCL6 is required for development of follicular T helper (Tfh) cells to support germinal center (GC) formation. However, it is not clear what unique functions programmed by BCL6 can explain its absolute essentiality in T cells for GC formation. We found that ablation of one Bcl6 allele did not appreciably alter early T cell activation and follicular localization but inhibited GC formation and Tfh cell maintenance. BCL6 impinged on Tfh calcium signaling and also controlled Tfh entanglement with and CD40L delivery to B cells. Amounts of BCL6 protein and nominal frequencies of Tfh cells markedly changed within hours after strengths of T-B cell interactions were altered in vivo, while CD40L overexpression rectified both defective GC formation and Tfh cell maintenance because of the BCL6 haploinsufficiency. Our results reveal BCL6 functions in Tfh cells that are essential for GC formation and suggest that BCL6 helps maintain Tfh cell phenotypes in a T cell non-autonomous manner.

Nonlinear Loads Compensation Using a Shunt Active Power Filter Controlled by Feedforward Neural Networks

The shunt active power filter (SAPF) is a widely used tool for compensation of disturbances in three-phase electric power systems. A high number of control methods have been successfully developed, including strategies based on artificial neural networks. However, the typical feedforward neural network, the multilayer perceptron, which has provided effective solutions to many nonlinear problems, has not yet been employed with satisfactory performance in the implementation of the SAPF control for obtaining the reference currents. In order to prove the capabilities of this simple neural topology, this work describes a suitable strategy of use, based on the accurate estimation of the Fourier coefficients corresponding to the fundamental harmonic of any distorted voltage or current. An effective training method has been developed, consisting of the use of many distorted patterns. The new generation procedure uses random combinations of multiple harmonics, including the possible nominal frequency deviations occurring in real power systems. The design of the generation of reference signals through computations based on the Fourier coefficients is presented. The objectives were the harmonic mitigation and power factor correction. Practical cases were tested through simulation and also by using an experimental platform, showing the feasibility of the proposal.

Multi-VSM based fuzzy adaptive cooperative control strategy for MVDC traction power supply system

This paper studies the control of a medium-voltage DC (MVDC) traction power supply system for rail transit (RT). In order to optimize the ability of DC voltage fluctuation and frequency regulation of rail trains, a fuzzy adaptive cooperative secondary control strategy based on improved virtual synchronous machine (VSM) is proposed. Firstly, the improved VSM control strategy is adopted in the traction substations (TSSs), which makes the RT trains have the external characteristics of synchronous generator and have certain inertia and damping support capacity, so as to improve the ability of the RT traction system to cope with traction network transient changes. Secondly, the virtual inertia and virtual damping can be dynamically adjusted by the system frequency deviating from the nominal steady-state frequency, and the dynamic fuzzy adjustment can be carried out by the fuzzy logic system to slow down the frequency fluctuation. Then, due to the different power supply distances and parameter settings between multiple TSSs, cooperative control is used to coordinate local TSS perceptions of information between adjacent TSS to achieve consistency of frequency response of multiple TSSs under different parameters. Besides, a time-varying switching topology handoff method is considered to select the optimal communication topology between adjacent base stations. Finally, simulation results verify the effectiveness of the proposed control strategy.

Resonant metamaterial designs for a broadband mitigation of flow-induced vibrations

Resonant metamaterials have recently emerged as lightweight and performant noise and vibration solutions for the hard-to-address low-frequency ranges. These engineered materials are made by an assembly of resonant elements onto a host structure. Their interaction leads to tuneable frequency ranges, known as stop bands, in which they can outperform classical noise control measures. However, these stop bands have a limited frequency range effect. To broaden the noise and vibration performance also outside the stop band, this paper presents a design approach for a finite resonant metamaterial plate. Two regularly spaced grids of resonant elements are both added to a plate. In the first grid, the resonant elements are tuned to the same nominal frequency and stop band behaviour is achieved. In the second grid, the tuned frequency of each resonant element is found through an optimisation procedure, with the goal of minimising the dynamic response of the plate outside the stop band. To speed up the optimisation, model order reduction and a dynamic sub-structuring method are employed. The performance of this finite resonant metamaterial plate design is validated by evaluating its vibration response due to a broadband grazing flow excitation and comparing it to a plate with equivalent mass additions.