Dynamic Frequency Research Articles

Comprehensive seismic loss model of Tehran, Iran in the case of Mosha fault seismic scenario using stochastic finite-fault method

This paper presents the results of a study caried out to assess probable seismic loss, in term of damage to the residential buildings and the number of fatalities, in the case of Mosha Fault seismic scenario in Tehran, Iran. Accordingly, seismic risk components (including seismic hazard, exposure model and fragility curves) are evaluated. The stochastic finite-fault method with dynamic corner frequency is applied for quantifying ground motion values. The results shows that PGA on the soil surface could range between 0.1 g to 0.45 g. Then, a reliable model of building exposure by analyzing census data from Tehran is compiled. This model included 19 different classes of buildings and is used to evaluate the potential damage to buildings from seismic scenario. The results indicate that the median of damage ratio from 100,000 iterations for the whole of the city is about 6% ± 1.54%. The study found that the central and eastern parts of Tehran are the most vulnerable areas, with an estimated 15,952 residents at risk of losing their lives in this scenario. This is equivalent to 0.2 percent of total population of Tehran. The finding from this study can be used by local authorities to provide appropriate emergency-response and preparedness plans in the case of Mosha Fault seismic scenario.

Frequent and strong cold-air pooling drives temperate forest composition.

Cold-air pooling is an important topoclimatic process that creates temperature inversions with the coldest air at the lowest elevations. Incomplete understanding of sub-canopy spatiotemporal cold-air pooling dynamics and associated ecological impacts hinders predictions and conservation actions related to climate change and cold-dependent species and functions. To determine if and how cold-air pooling influences forest composition, we characterized the frequency, strength, and temporal dynamics of cold-air pooling in the sub-canopy at local to regional scales in New England, USA. We established a network of 48 plots along elevational transects and continuously measured sub-canopy air temperatures for 6-10 months (depending on site). We then estimated overstory and understory community temperature preferences by surveying tree composition in each plot and combining these data with known species temperature preferences. We found that cold-air pooling was frequent (19-43% seasonal occurrences) and that sites with the most frequent inversions displayed inverted forest composition patterns across slopes with more cold-adapted species, namely conifers, at low instead of high elevations. We also observed both local and regional variability in cold-air pooling dynamics, revealing that while cold-air pooling is common, it is also spatially complex. Our study, which uniquely focused on broad spatial and temporal scales, has revealed some rarely reported cold-air pooling dynamics. For instance, we discovered frequent and strong temperature inversions that occurred across seasons and in some locations were most frequent during the daytime, likely affecting forest composition. Together, our results show that cold-air pooling is a fundamental ecological process that requires integration into modeling efforts predicting future forest vegetation patterns under climate change, as well as greater consideration for conservation strategies identifying potential climate refugia for cold-adapted species.

Influential Metrics Estimation and Dynamic Frequency Selection Based on Two-Dimensional Mapping for JPEG-Reversible Data Hiding

JPEG Reversible Data Hiding (RDH) is a method designed to extract hidden data from a marked image and perfectly restore the image to its original JPEG form. However, while existing RDH methods adaptively manage the visual distortion caused by embedded data, they often neglect the concurrent increase in file size. In rectifying this oversight, we have designed a new JPEG RDH scheme that addresses all influential metrics during the embedding phase and a dynamic frequency selection strategy with recoverable frequency order after data embedding. The process initiates with a pre-processing phase of blocks and the subsequent selection of frequencies. Utilizing a two-dimensional (2D) mapping strategy, we then compute the visual distortion and file size increment (FSI) for each image block by examining non-zero alternating current (AC) coefficient pairs (NZACPs) and their corresponding run lengths. Finally, we select appropriate block groups based on the influential metrics of each block group and proceed with data embedding by 2D histogram shifting (HS). Extensive experimentation demonstrates how our method’s efficiently and consistently outperformed existing techniques with a superior peak signal-to-noise Ratio (PSNR) and optimized FSI.

Layer-Number-Dependent Magnetism in the Co-Doped van der Waals Ferromagnet Fe3GaTe2.

Recently, van der Waals (vdW) antiferromagnets have been proposed to be crucial for spintronics due to their favorable properties compared to ferromagnets, including robustness against magnetic perturbation and high frequencies of spin dynamics. High-performance and energy-efficient spin functionalities often depend on the current-driven manipulation and detection of spin states, highlighting the significance of two-dimensional metallic antiferromagnets, which have not been much explored due to the lack of suitable materials. Here, we report a new metallic vdW antiferromagnet obtained from the ferromagnet Fe3GaTe2 by cobalt (Co) doping. Through the layer-number-dependent Hall resistance and magnetoresistance measurements, an evident odd-even layer-number effect has been observed in its few-layered flakes, suggesting that it could host an A-type antiferromagnetic structure. This peculiar layer-number-dependent magnetism in Co-doped Fe3GaTe2 helps unravel the complex magnetic structures in such doped vdW magnets, and our finding will enrich material candidates and spin functionalities for spintronic applications.

LEC-MiCs: Low-Energy Checkpointing in Mixed-Criticality Multi-Core Systems

With the advent of multicore platforms in designing Mixed-Criticality Systems (MCSs), simultaneous management of reliability and energy while guaranteeing an acceptable service level for low-criticality tasks is a crucial challenge. To ensure the reliability of the MCSs against transient faults, fault-tolerant techniques are employed which will increase energy consumption. To mitigate the energy overhead, the Dynamic Voltage and Frequency Scaling (DVFS) technique will be exploited. However, this technique might lead to violating the timing constraints of high-criticality tasks. Therefore, this paper presents, for the first time, the low-energy checkpointing technique to guarantee the reliability of multiple preemptive periodic mixed-criticality tasks in a multicore platform. In contrast to the previous works in checkpointing technique which consider a specific number of faults that all the tasks in the system should tolerate, in this paper, the number of tolerable faults for each execution section of a task, and in each voltage and frequency level is determined through proposed formulas to meet the reliability target based on safety standards. Then, our proposed method determines the number of checkpoints and their non-uniform intervals for the normal and overrun sections of each task to reduce energy consumption, respectively. Moreover, the unified demand bound function (DBF) analysis is proposed for analyzing the schedulability of the task set, where each high-criticality task meets its timing and reliability constraints, and low-criticality tasks execute based on their derived guaranteed periods in each operational mode of the system. Experimental results show that our proposed scheme meets the timing and reliability constraints while at the same time, improving the QoS of low-criticality tasks, and managing energy consumption with an average of 29.49%, and 32.78%, respectively.

Multi-objective configuration and evaluation of dynamic virtual inertia from DFIG based wind farm for frequency regulation

Modern power systems are gradually evolving into low-inertia systems due to the integration of high penetration of renewable energy and power electronic equipment. For the natural inertia on the rotor, doubly-fed induction generator (DFIG) based wind farms are expected to provide inertia support for systems. The paper proposed an analytical model of DFIG with df/dt inertia control for studying frequency dynamics, and investigates the optimal design of virtual inertia from wind farms, as well as its equivalent inertia contribution to system. The inertia response differences between DFIG and synchronous generator (SG) are discussed and analyzed for the first time, and then to accurately describe the frequency response with low cost, an analytical model of DFIG with inertia control is developed considering wind turbine aerodynamic characteristics. The explicit expression of virtual inertia provided by DFIG is derived according to the kinetic energy equilibrium, and the key factors that dominate the magnitude of virtual inertia are illustrated. Based on the system frequency response model including wind farms, taking the system frequency nadir (SFN) and the time of reaching nadir (ToN) as targets, a multi-objective optimal configuration model of virtual inertia is constructed and solved through MOPSO. The time domain simulations of a generic two machine four bus system and modified IEEE 9-bus test system are both performed in MATLAB/Simulink, the accuracy and efficiency of our proposed DFIG model on system frequency dynamics research are demonstrated, the pareto frontiers of virtual inertia configuration under different working conditions are optimized and analyzed as well as the impacts of different parameters on inertia evaluation.

Hydrodynamic Responses of Heaving Motion on One Body and Two Body Point Absorber Devices with Different Wave Condition in Malaysia

Wave energy harvesters are still not as mature as other types of renewable energy harvesting devices, particularly when it comes to commercialization, mass production, and grid integration, even though ocean waves around the world are known to contain high and dense quantities of energy. However, recent studies and optimizations suggested that the point absorber wave energy harvester may be a viable option. This paper provides a comprehensive comparison hydrodynamic damping analysis of the heaving motion on one body and two body point absorber wave energy harvesters by using Computational Fluid Dynamic (CFD) software. A simulation run was proposed for the analysis performance of damping of the point absorber devices to low wave height (0.7m-2.5m) and period (0.9s-2.2s). There are two types of point absorbers: one-body point absorber and two body point absorber. Both point absorber body are examined by simulation in terms of its heaving dynamic motion frequency in calm, medium and strong wave condition. This analysis highlights the extensive research being done to bring point absorbers closer to technical maturity, paving the way for commercialization and mass production for low wave characteristics. The results showed two body point absorber Response Amplitude Operator (RAO) is improved to absorbed low wave height compared to one body by RAO efficiency 17% and device efficiency 25%. The two-body point absorber performed better in all wave condition.

Making a day out of records: Phonographic pedagogies of the Afro-sonic diaspora

This article develops the concept of “low-end phonographic pedagogies” through a life-long engagement with vinyl records and the Afro-diasporic music practices of reggae, dub, and dancehall. Approaching my record collection as a counter-archive of vibrational feeling and learning, I explore everyday practices of playing and listening to records as a field of inquiry into the pedagogical potentials of phonographic technologies. Focusing on the dub styles of record production and bass-heavy sound systems that have spread globally from Jamaica since the 1970s, the article engages scholarship in decolonial sound studies and process philosophy to explore the vibratory, affective, and social dynamics of sub-bass frequencies and polyrhythms. This leads to a conceptualization of low-end phonographic pedagogies as situated within a wider continuum of vibratory learning events that stretch from the sub-atomic to the cosmic.

Multi-agent deep reinforcement learning for joint dynamic conservation voltage reduction and Q-sharing in inverter-based autonomous microgrids

Conservation voltage reduction (CVR) is implemented in power systems to mitigate power consumption in steady-state time scales. We propose dynamic-scale CVR (DCVR) as a potent solution to provide cost-effective frequency support in inverter-interfaced (micro) grids. The proposed DCVR reduces the voltage profile in dynamics and consequently power reduction helps to maintain instant production-consumption balance for dynamic frequency support. However, DCVR implementation in autonomous MGs (AMGs) faces critical control and stability problems. DCVR is implemented by controlling the voltage, which is a local variable, and makes it difficult to be realized through a decentralized structure. Besides, preserving accurate reactive power sharing (Q-sharing) through conventional droop controllers while employing the DCVR is another critical concern. In this light, this paper proposes a novel artificial intelligence (AI)-based decentralized control structure to implement the DCVR in AMGs for tackling the existing issues. The multi-agent deep reinforcement learning (DRL) model, with a deep Q-network (DQN) algorithm, is adopted to address the grid instabilities and inaccurate Q-sharing issues that arise due to incorporating the DCVR. The proposed method is able to handle the nonlinearity and complexity of the system while maintaining proper dynamic performance and AMG stability. Simulation results in MATLAB/Simulink prove the effectiveness of the proposed control method.

Multichannel multimodal piezoelectric middle ear implant concept based on MEMS technology for next-generation fully implantable cochlear implant applications

This paper introduces a unique multimode, multichannel piezoelectric vibration sensor for the next-generation fully implantable cochlear implant (FICI) systems. The sensor, which can be implanted on the middle ear chain to collect and filter the ambient sound in eight frequency bands, comprises an array of 4 M-shape multimode and 11 single cantilevers. Finite element (FE) analysis indicates a 2.05-fold improvement in capturing frequency information for the multimodal sensor compared to its single-mode counterpart. Under an acoustic excitation at 100 dB SPL, the sensor, mounted on an artificial tympanic membrane, yielded a peak output voltage of 546.16 mVpp and a peak sensitivity of 285.28 mVpp/Pa at 1613 Hz. The extrapolated acoustic results indicated a dynamic frequency range between 300 Hz and 6 kHz, even at 30 dB SPL. Furthermore, a lightweight titanium coupler, employing a two-sided clipping structure with a maximum wall thickness of 70 μm, is micromachined for surgical attachment of the transducer to the middle ear chain. A commercial accelerometer, implanted on the incus short process (SP) of a cadaver using the titanium coupler, successfully recorded 0.1 g for 100 dB SPL at 500 Hz, revealing the potential feasibility of the coupler for vibration sensor implantation. Moreover, the presented anatomically accurate FE model of the middle ear, exhibiting a high correlation coefficient (R2) of 0.97 with the cadaveric experiment, suggests an efficient numerical approach for evaluating the implantation of middle ear prostheses. In this regard, the study holds great promise for clinical application in the field of implantable hearing aids.

Architectural and Technological Approaches for Efficient Energy Management in Multicore Processors

Benchmarks play an essential role in the performance evaluation of novel research concepts. Their effectiveness diminishes if they fail to exploit the available hardware of the evaluated microprocessor or, more broadly, if they are not consistent in comparing various systems. An empirical analysis of the consecrated Splash-2 benchmarks suite vs. the latest version Splash-4 was performed. It was shown that on a 64-core configuration, half of the simulated benchmarks reach temperatures well beyond the critical threshold of 105 °C, emphasizing the necessity of a multi-objective evaluation from at least the following perspectives: energy consumption, performance, chip temperature, and integration area. During the analysis, it was observed that the cores spend a large amount of time in the idle state, around 45% on average in some configurations. This can be exploited by implementing a predictive dynamic voltage and frequency scaling (DVFS) technique called the Simple Core State Predictor (SCSP) to enhance the Intel Nehalem architecture and to simulate it using Sniper. The aim was to decrease the overall energy consumption by reducing power consumption at core level while maintaining the same performance. More than that, the SCSP technique, which operates with core-level abstract information, was applied in parallel with a Value Predictor (VP) or a Dynamic Instruction Reuse (DIR) technique, which rely on instruction-level information. Using the SCSP alone, a 9.95% reduction in power consumption and an energy reduction of 10.54% were achieved, maintaining the performance. By combining the SCSP with the VP technique, a performance increase of 8.87% was obtained while reducing power and energy consumption by 3.13% and 8.48%, respectively.

Parent-child emotion dynamics in families presenting for behavioral parent training: Is there a link with child behavior, parenting, and treatment outcome?

Behavioral parent training (BPT) is the standard of care for early onset behavior disorders (BDs), however, not all families benefit. Emotion regulation (ER) is one potential mechanism underlying BPT outcomes, yet there are challenges in capturing intra- and interpersonal aspects of emotion regulation within parent-child interactions that are central to BPT. This study examined how vocally encoded emotional arousal unfolds during parent-child interactions and how parents and children influence each other's arousal (Aim 1), the links between these emotion dynamics, child behavior, and parenting at baseline (Aim 2), and BPT outcome (Aim 3). Families of children with BDs (N = 45) completed two interaction tasks and measures of parenting and child behavior. Parent-child dynamics of vocal fundamental frequency (f₀) were modeled using actor-partner interdependence models (APIMs) and coupled linear oscillators (CLOs). When considering relative levels of f₀ from one talk turn to the next (APIMs), parents and children showed intrapersonal regulation and synchronizing reactivity to each other's f₀. When considering the shape of oscillations (CLOs), parents and children showed intrapersonal regulation but no reactivity. Intrapersonal regulation of f₀ during the interaction was slowed for parents with more maladaptive parenting and children with more behavior problems at baseline. This preliminary characterization of f0 in families presenting for BPT provides insights into the emotion dynamics potentially underlying parenting behavior and child behavior. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The population genetics of partial diapause, with applications to the aestivating malaria mosquito Anopheles coluzzii.

Diapause, a form of dormancy to delay or halt the reproductive development during unfavourable seasons, has evolved in many insect species. One example is aestivation, an adult-stage diapause enhancing malaria vectors' survival during the dry season (DS) and their re-establishment in the next rainy season (RS). This work develops a novel genetic approach to estimate the number or proportion of individuals undergoing diapause, as well as the breeding sizes of the two seasons, using signals from temporal allele frequency dynamics. Our modelling shows the magnitude of drift is dampened at early RS when previously aestivating individuals reappear. Aestivation severely biases the temporal effective population size ( ), leading to overestimation of the DS breeding size by across 1 year, where is the aestivating proportion. We find sampling breeding individuals in three consecutive seasons starting from an RS is sufficient for parameter estimation, and perform extensive simulations to verify our derivations. This method does not require sampling individuals in the dormant state, the biggest challenge in most studies. We illustrate the method by applying it to a published data set for Anopheles coluzzii mosquitoes from Thierola, Mali. Our method and the expected evolutionary implications are applicable to any species in which a fraction of the population diapauses for more than one generation, and are difficult or impossible to sample during that stage.

Analyzing Vocal Fold Frequency Dynamics Using High-Speed 3D Laser Video Endoscopy.

To examine changes in lateral and vertical vibratory motion along the anterior, middle, and posterior sections of the vocal folds, as a function of vocal frequency variations. Absolute measurements of vocal fold surface dynamics from high-speed videoendoscopy with custom laser endoscope were made on 23 vocally healthy adults during sustained /i:/ production at 10%, 20%, and 80% of pitch range. The 3D parameters of amplitude (mm), maximum velocity opening/closing (mm/s), and mean velocity opening/closing (mm/s) were computed for the lateral and vertical vibratory motion along the anterior, middle, and posterior sections of the vocal folds. Linear mixed model analysis was conducted to evaluate the differences in (a) vocal frequency levels (high vs. normal vs. low pitch), (b) axis level (vertical vs. lateral), (c) position level (anterior vs. middle vs. posterior), and (d) gender differences (male vs. female). Overall, the superior surface vertical motion of the vocal fold is greater compared with the lateral motion, especially in males. Along the superior surface, the mean and maximum closing velocities are greater posteriorly for low pitch. The location (anterior, middle, and posterior) along the superior surface is relevant only for vocal fold closing rather than opening, as the dynamics are different along the various locations. The study highlights the significance of assessing the vertical motion of the superior surface of the vocal fold to understand the complex dynamics of voice production. NA Laryngoscope, 2024.

Thermal and electrical switchable wide-angle multi-band terahertz absorber.

Multi-band terahertz (THz) absorbers have recently gained attention due to their favorable application prospects in communication, imaging, detection, and other fields. However, many multi-band THz absorbers are tuned by a single method, which limits their tuning effect. To address this issue, we propose a multi-band THz absorber that can be co-modulated by thermal and electrical methods. Our proposed absorber uses vanadium dioxide (VO2) to achieve this co-modulation. When VO2 is insulating, the frequency of the absorbing peaks originating from the lateral Fabry-Pérot resonance mode can be changed by adjusting the VO2 width. When VO2 is a conductor, the quality factor of the absorbing peak based on the inductor-capacitor resonance mode can be tuned by adjusting the width of VO2. By varying the top dielectric layer thickness, the frequency of the absorbing peaks can be tuned over a wide range. For devices with two or three layers of graphene nanoribbons-dielectric stacks, a modulation effect similar to that of varying dielectric layer thickness in a single-layer graphene device can be achieved simply by applying a 1 eV Fermi energy to graphene nanoribbons in different layers. By combining thermal and electrical modulation, the two or three-layer stacked device can be dynamically switched between four or six absorbing states, and a wider range of dynamic peak frequency modulation can be realized. Furthermore, the performance of the absorber does not deteriorate significantly at an incident angle of up to 70°. Our proposed thermal-electrical switchable wide-angle multi-band THz absorber provides a reference for the design, fabrication, and application of high-performance THz absorbers in different fields.

FineMon: An Innovative Adaptive Network Telemetry Scheme for Fine-Grained, Multi-Metric Data Monitoring with Dynamic Frequency Adjustment and Enhanced Data Recovery

Network telemetry, characterized by its efficient push model and high-performance communication protocol (gRPC), offers a new avenue for collecting fine-grained real-time data. Despite its advantages, existing network telemetry systems lack a theoretical basis for setting measurement frequency, struggle to capture informative samples, and face challenges in setting a uniform frequency for multi-metric monitoring. We introduce FineMon, an innovative adaptive network telemetry scheme for precise, fine-grained, multi-metric data monitoring. FineMon leverages a novel Two-sided Frequency Adjustment (TFA) to dynamically adjust the measurement frequency on the Network Management System (NMS) and infrastructure sides. On the NMS side, we provide a theoretical basis for frequency determination, drawing on changes in the rank of multi-metric data to minimize monitoring overhead. On the infrastructure side, we adjust the frequency in real-time to capture significant data fluctuations. We propose a robust Enhanced-Subspace-based Tensor Completion (ESTC) to ensure accurate recovery of fine-grained data, even with noise or outliers. Through extensive experimentation with three real datasets, we demonstrate FineMon's superiority over existing schemes in reduced measurement overhead, enhanced accuracy, and effective capture of intricate temporal features.

Frequency prediction of a post-disturbance power system using a hybrid ARIMA and DBN model

The online prediction of power system dynamic frequency helps to guide the choice of control measures quickly and accurately after a disturbance, and this then ensures the reliable and stable operations of a power system. However, the prediction performance of the traditional single model is not accurate enough, and the prediction method cannot reflect the dynamic mechanism of the power system. To address these challenges, based on the analysis of the mechanism of the dynamic operation of a power system, a dynamic frequency online prediction method using the autoregressive integrated moving average (ARIMA) model and the deep belief network (DBN) is proposed in this paper. First, according to the mechanism of the dynamic operation of a power system, the dynamic frequency can be regarded as having two stages after the disturbance occurs. In the first stage, the frequency changes monotonously in the short term, which is predicted by the ARIMA model. Furthermore, the second stage is an oscillation phase with changing amplitude, which is predicted by the DBN. The calibration process is used to combine the two predicted results. Second, the three metrics including the frequency nadir (fnadir), the quasi-steady state frequency (fss), and the frequency curve obtained through the prediction are analyzed to measure the accuracy of the prediction results. Finally, to verify the accuracy of the proposed model, the IEEE 10-generator 39-bus benchmark system is used for verification.

Dynamic simulation and experimental validation of a 35 MW heat pump based on a transcritical CO2 cycle

Replacing the baseload providers on the energy market with decarbonized renewable solutions increases frequency dynamics on the grid. In order to handle the concomitant risks and chances linked with this change of paradigm between energy producers and consumers, complex dynamic models are required to optimize energy management strategies. Industrial transcritical carbon dioxide (CO2) heat pumps, such as the one developed by MAN Energy Solutions Schweiz AG (MAN ES), offer a proven solution for the decarbonization of the district heating sector. Furthermore, they are associated with pathways to increase the usage of this solution for sector coupling applications. This work presents a detailed Modelica model of the high-temperature CO2 heat pump, focusing on the thermodynamic states of the refrigerant during load variations of the system. In a consecutive step, the model is validated against testbed data of a heat pump from MAN ES with over 35 MW heat supply and a lift from 40 to 100 K. The model results match the testbed data with an accuracy of over 95 % and demonstrate a full coverage of the performance map minimum to maximum speed, providing water-side supply temperatures of 50–109 °C. Realistic dynamics in fast load balancing operation are demonstrated where power consumption was varied by 80 % compared to maximum power within 30 s. Models of this kind are essential for an accurate prediction how decarbonized energy networks react by linking electricity and heat supply together. These predictions are ultimately useful to upgrade or optimize complex control strategies.

Design of an Enhanced Dynamic Regulation Controller Considering the State of Charge of Battery Energy Storage Systems

In recent years, the escalating electricity demand in Taiwan has heightened the prominence and discourse surrounding the issue of power supply. With the enactment of the European climate law, global commitment to achieving net-zero emissions has gained momentum. Concurrently, the Taiwanese government has articulated the Taiwan 2050 net-zero emissions policy. To realize this objective, Taiwan has vigorously promoted renewable energy in recent years, increasing the proportion of renewable energy in its energy mix. However, confronted with the intermittent and unpredictable nature of renewable energy generation, challenges arise concerning the stability and quality of power supply. In response to the impact of integrating renewable energy into the grid, the Taiwan Power Company (Taipower) has introduced the day-ahead ancillary service market. Through this platform, power generation and battery energy storage systems (BESSs) engage in competitive bidding, fostering the integration of diverse distributed energy resources into the system. These resources serve as dispatchable assets for Taipower, contributing to grid stability by providing ancillary services. This study has developed an advanced dynamic regulation reserve controller by employing an industrial PC (IPC) in conjunction with a multifunctional power meter. Through real-time measurement of the power grid frequency by the multifunctional power meter, a sophisticated dynamic frequency reserve control strategy has been devised, taking into account the charging state of energy storage systems. This strategy exhibits high operational quality, effectively regulating the charging and discharging of energy storage systems. In addition to swiftly adjusting the current grid frequency, it encompasses the capability to facilitate the transfer of peak electrical energy. This effectively stabilizes the power grid, alleviating supply pressures during nighttime peaks and enhancing the overall supply stability of the power system.

Energy Management of Distribution-Level Integrated Electric-Gas Systems With Fast Frequency Reserve

This paper studies the energy management of distribution-level integrated electric-gas systems (D-IEGSs), considering their frequency support capability via providing the fast frequency reserve (FFR) service. The dynamics of the main grid frequency as well as frequency regulation behaviors of gas-fired turbines (GTs), power-to-gas (P2G) units, wind turbines (WTs) and Photovoltaic (PV) units in the D-IEGS are formulated, including the dead zone, limiting ranges, and the time constant of the governors. The impacts of frequency regulation behaviors of GTs and P2G units on the operation constraints of the D-IEGS are examined through a feasibility check sub-problem. Thus, the overall problem becomes a two-stage one, which is solved by the column-and-constraint generation (C&CG) algorithm. The variable-step difference and the binary variable reduction schemes are devised to decrease the computation burden. Simulation results on the IEGS with a 13-bus power network and a 6-node gas network verify the value of FFR provided by the D-IEGS and the necessity of modeling the operation constraints of the gas network.