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Purpose. To obtain analytical dependencies for the precise calculation of the stator current of a frequency-regulated three-phase shortcircuited induction motor and to estimate the components of its main electrical power losses, which are spent on the transportation magnetic power losses (to the magnetization circuit) and additional power losses (through the motor air gap), as well as with using the obtained refined dependencies to research the electromagnetic processes and energy modes of the frequency-regulated induction motor when its speed and load change. Methodology. The method of generalized vectors is used for the refined calculation of the electromagnetic processes and energy modes of the frequency-regulated induction motor. Results. Based on the catalog data and parameters of the induction motor’s equivalent replacement circuit, also the specified values of its useful rotational torque and speed, refined analytical dependencies were obtained for the calculation of the main electromagnetic power losses of the frequency-regulated induction motor, which take into account the influence of all types of power losses, which present in it, as well as – power losses spent on transporting magnetic losses (to the magnetization circuit) and additional losses (through the air gap of the motor). With the help of the obtained dependencies, the energy modes (including main power consumption and electromagnetic power losses, efficiency factor, power factor) of the frequency-regulated induction motor in the driving and generator modes of its operation in relation to the first (at speeds not higher than the nominal) and the second (at speeds above the nominal) speed control zones for the operating ranges of the motor useful rotational torque and speed changes were calculated. Originality. A refined analytical calculation dependence has been obtained for determining the active projection of the generalized stator current vector of a frequency-regulated induction motor, which takes into account the presence of additional power losses and the component of electrical losses caused by the transportation of additional power losses through the air gap of the motor; an analytical dependence is also proposed for determining the increment of the mentioned active projection, which is due to the transportation of magnetic power losses to the motor magnetization circuit. Practical value. Analytical calculation dependencies are proposed for the quantitative assessment of errors (as a percentage of mentioned values) in steady-state modes for determining the main electromagnetic power losses of the frequency-regulated induction motor, caused by the absence (in comparison with relevant studies from known publications) of taking into account additional and magnetic power losses, as well as – the influence of electrical component losses caused by the transportation of the mentioned power losses through the air gap or to the magnetization circuit of the motor, respectively. References 16, tables 5, figures 2. [ABSTRACT FROM AUTHOR]

The increasing use of renewable energies places new challenges on the balance of the electricity system between demand and supply, due to the intermittent nature of renewable energy resources. However, through frequency regulation (FR) services, owners of battery storage systems can become an essential part of the future smart grids. We propose a thorough first study on the use of batteries associated with base stations (BSs) of a cellular network, to participate in ancillary services with respect to FR services, via an auction system. Trade-offs must be made among the number of participating BSs, the degradation of their batteries and the revenues generated by FR participation. We propose a large-scale mathematical programming model to identify the best participation periods from the perspective of a cellular network operator. The objective is to maximize profit while considering the aging of the batteries following their usage to stabilize the electrical grid. Experiments are conducted with data sets from different real data sources. They not only demonstrate the effectiveness of the optimization model in terms of the selection of BSs participating in ancillary services and providing extra revenues to cellular network operators, but also show the feasibility of ancillary services being provided to cellular network operators. [ABSTRACT FROM AUTHOR]

Copyright of Power Generation Technology is the property of Power Generation Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The demand for electric vehicle supply equipment (EVSE) is increasing because of the rapid shift toward electric transport. Introducing EVSE on a large scale into the power grid can increase power demand volatility, negatively affecting frequency stability. A viable solution to this challenge is the development of smart charging technologies capable of performing frequency regulation. This paper presents an experimental proof of concept for a new frequency regulation method for EVSE utilizing a distributed control architecture. The architecture dynamically adjusts the contribution of electric vehicles (EVs) to frequency regulation response based on the charging urgency assigned by the EV users. The method is demonstrated with two Renault ZOEs responding to frequency fluctuation with a combined power range of 6 kW in the frequency range of 50.1 to 49.9 Hz. The results confirm consistent power sharing and effective frequency regulation, with the system controlling the engagement of the EVs in frequency regulation based on priority. The delay and accuracy analyses reveal a fast and accurate response, with the cross-correlation indicating an 8.48 s delay and an average undershoot of 0.17 kW. In the conclusions, the paper discusses prospective improvements and outlines future research directions for integrating EVs as service providers. [ABSTRACT FROM AUTHOR]

This paper presents a novel primary frequency regulation strategy for multi-microgrid (MMG) systems, utilizing consumer theory within a peer-to-peer (P2P) energy management framework. By coordinating photovoltaic (PV) systems and energy storage systems (ESS), the proposed method ensures a rapid and effective response to frequency deviations. Unlike conventional approaches, this strategy minimizes the curtailment of renewable energy sources by prioritizing the use of ESS, allowing excess energy to charge the ESS for later use during under-frequency events. This not only enhances energy efficiency but also maximizes renewable energy utilization. Simulations demonstrate that the proposed scheme achieves lower frequency deviations and faster stabilization compared to traditional droop and virtual inertia methods. These results highlight the potential benefits of integrating consumer theory-based models into primary frequency regulation, significantly enhancing system stability and efficiency in power systems with high levels of renewable energy penetration. [ABSTRACT FROM AUTHOR]

Grid-forming (GFM) wind storage systems (WSSs) possess the capability of actively building frequency and phase, enabling faster frequency response. The frequency regulation power of GFM WSSs is provided by both the rotor of wind turbine and the battery storage (BS) in parallel with DC capacitor. However, with existing control strategies, the energy storage immediately responds to both small and large grid disturbances. The frequent responses significantly decrease the lifespan of energy storage. To address this issue, a cooperative strategy between rotor and energy storage is necessary. This paper proposes an advanced strategy of GFM WSSs for cooperative DC power support. The cooperative principle is that for small disturbances, the BS is disabled and total frequency regulation power is provided by the rotor, while for large disturbances, the BS is enabled to cooperatively provide power support with the rotor. The proposed cooperative strategy can decrease the charging and discharging times of BS with a small range of rotor speed fluctuation, and then the service life of BS can be significantly extended. Simulation results validate the effectiveness and superiority of the proposed strategy. [ABSTRACT FROM AUTHOR]

As one of the largest frequency regulation markets, the Pennsylvania-New Jersey-Maryland Interconnection (PJM) market allows extensive access of Battery Energy Storage Systems (BESSs). The designed signal regulation D (RegD) is friendly for use with BESSs with a fast ramp rate but limited energy. Designing operating strategies and optimizing the sizing of BESSs in this market are significantly influenced by the regulation signal. To represent the inherent randomness of the RegD signal and reduce the computational burden, typical frequency regulation scenarios with lower resolution are often generated. However, due to the rapid changes and energy neutrality of the RegD signal, generating accurate and representative scenarios presents challenges for the methods based on shape similarity. This paper proposes a novel probability-based method for generating typical regulation scenarios. The method relies on the joint probability distribution of two features with a 15-min resolution, extracted from the RegD signal with a 2 s resolution. The two features can effectively portray the characteristic of RegD signal and its influence on BESS operation. Multiple regulation scenarios are generated based on the joint probability distributions of these features at first, with the final typical scenarios chosen based on their probability distribution similarity to the actual distribution. Utilizing regulation data from the PJM market in 2020, this paper validates and analyzes the performance of the generated typical scenarios in comparison to existing methods, specifically K-means clustering and the forward scenarios reduction method. [ABSTRACT FROM AUTHOR]

As the proportion of renewable energy generation continues to increase, the participation of new energy stations with high-proportion energy storage in power system frequency regulation is of significant importance for stable and secure operation of the new power system. To address this issue, an energy storage control method based on quantum walks and model predictive control (MPC) has been proposed. First, historical frequency deviation signals and energy storage charge-discharge state signals are collected. Simulation data are generated through amplitude encoding and quantum walks, followed by quantum decoding. Subsequently, the decoded data are inputted into the MPC framework for real-time control, with parameters of the predictive model continuously adjusted through a feedback loop. Finally, a novel power system frequency regulation model with high-proportion new energy storage stations is constructed on the MATLAB/Simulink platform. Simulation verification is conducted with the proportional-integral-derivative (PID) and MPC methods as comparative approaches. Simulation results under step disturbances and random disturbances demonstrate that the proposed method exhibits stronger robustness and better control accuracy. [ABSTRACT FROM AUTHOR]

As the utilization of wind power systems continues to increase, reducing overall system inertia, there is a consequential negative impact on the power system's ability to regulate frequency. Consequently, this study focuses on examining the fast-frequency regulation in high penetration of wind power, especially doubly fed induction generators—the most commonly installed wind turbine type, and an energy storage system installed in the wind farm. This study proposes a coordinated control of wind turbine generators and battery energy storage systems that provides fast-frequency regulation to the system while simultaneously ensuring the safety of the battery. Firstly, the fast-frequency regulation capability of the wind turbine will be studied. Secondly, primary frequency control of the battery energy storage system considering adaptive droop control based on state of charge is proposed to prevent both over-charging and over-discharging of the battery. Finally, this study proposed a coordinated fast-frequency regulation approach for the hybrid wind-storage system, which is evaluated under various wind speed scenarios. This approach involves a detailed analysis of the operational characteristics of the wind turbine generators to ensure optimal performance. The proposed method is validated through simulation using a MATLAB model of the wind-storage system, and comparative results with alternative control methods confirm the effectiveness of the proposed approach in raising the frequency nadir and avoiding the secondary frequency dip. [ABSTRACT FROM AUTHOR]

Recently, the transition from conventional to renewable energy sources (RESs), from internal combustion engine vehicles to electric vehicles (EVs), and from the main grid to microgrids (MGs) are essential goals to both reduce greenhouse gas emissions and ensure the stability of power systems. However, the transitions cause new concerns in the grid including technical challenges and financial viability. This study examines the RES-based MG under realistic conditions considering the uncertainty in fleet size of EVs, emergency generator capacity, solar irradiation, and wind speed in island mode. The work aims to provide effective solutions including conventional methods alongside today's trend namely doubly fed electrical generators (DFIG), vehicle-to-grid mechanism (V2G), maximum power point tracking controller (MPPT), voltage source inverter (VSI) with high switching frequency for technical challenges, and virtual synchronous generator (VSG) mechanism for financial viability. The paper provides a guide for resizing the emergency generators capacity depending on system instability. The observations verify that the control mechanisms reinforce the system to remain stable by decreasing the range of frequency fluctuation from 3.1 to <0.05 Hz, the peak point of frequency from 51.8 to 50.05 Hz, and the emergency generator capacity from 0.7605 to 0.3420 MVAr at MATLAB and Simulink. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are considered to be the most promising technology upgrades in the coming years to reduce the carbon emission, since the EVs could replace the conventional combustion vehicles as well as mitigate power fluctuations in power grids. This paper focuses on addressing the frequency stability issues in isolated hybrid grids (IHGs) by introducing a fractional order proportional-integral-derivative (FOPID) control for grid-connected power converters. A particle swarm optimization (PSO) technique is adopted to optimize the parameters of the controllers. The advantages of the proposed control method over the conventional proportional-integral-derivative (PID) control, proportional-integral with proportional-derivative (PI-PD) control, and proportional-integral-derivative with filter (PIDF) control schemes are verified by simulation case studies. Besides, a modified virtual rotor concept (MVRC) is proposed in this paper to enhance the inertia of the system. Furthermore, the performance of using EVs to regulate the frequency of IHGs is compared to the superconducting magnetic energy storage (SMES) units, capacitive energy storage (CES) units, and redox flow batteries (RFB) under fixed and variable load conditions. [ABSTRACT FROM AUTHOR]

This paper proposes a variable-power-tracking-operation-based frequency regulation scheme for a wind turbine generator (WTG) that employs a frequency-excursion-based control parameter to suppress frequency excursion under various wind speeds and disturbances. To this end, an improved system frequency response model is built, and then the frequency regulation characteristics of the WTG are investigated. The frequency-excursion-based control parameter is determined. Simulations based on the Matlab/Simulink simulator verify the effectiveness of the proposed variable-power-tracking-operation-based frequency regulation strategy. The simulation results clearly indicate that the suggested scheme is beneficial for reducing the maximum frequency deviation. The proposed frequency regulation scheme could enhance the networking capacity of wind farms and improve the capacity of the power grid to absorb renewable energy. [ABSTRACT FROM AUTHOR]

Abstract 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.

In contemporary scenario, electric power companies have observed upsurge in penetration level of tidal power plants (TPPs) in the traditional electric power system framework. However, the tidal turbines offer less frequency assistance due to their lesser rotor mass. Hence, TPPs may be collaborated with conventional units like diesel engine generator (DEG) to confirm system frequency stability in multi-area micro-grid system. The DEG comprises of primary and proportional integral derivative (PID) secondary frequency controls. However, in TPPs, to advance the system frequency regulation, deloading control approach is suggested and a cascade fuzzy fractional order PID-ID with derivative filter (CFFOPID-IDF) droop controller is suggested in place of the conventional non-cascade controller droop in the deloaded region. The suggested controller gains are fetched exploiting Salps swarm algorithm. For further enhancement of the dynamic responses, a precise high voltage direct current (AHVDC) link with the inertia emulation-based control (INEC) scheme is adopted, which allows the utilization of the gathered energy from the capacitance of the HVDC interface for frequency regulation. It provides better results compared to conventional AC tie line interface having less undershoot (34 %/20.63 %/43.75 %) and settling time (20.45 %/59.09 %/16.83 %) for variation in area-1 frequency/area-2 frequency/tie line power, respectively. The recommended control scheme is evidenced superior over numerous existing control techniques and provides least cost function in contrast to other control techniques. Additionally, it offers a highly stable performance under variable load conditions. • A CFFOPID-IDN structured controller based droop is suggested for tidal turbines. • The controller is tuned via SSA to alleviate the oscillations in microgrid under step load disturbances. • The study is conducted on a two-area microgrid interconnected via HVAC and HVDC links. • The superiority of CFFOPID-IDN controller in established over PID/FPID/FOFPID controller. • HVDC link demonstrates distinction over HVAC link. [ABSTRACT FROM AUTHOR]

Iron–nickel (Fe-Ni) batteries are renowned for their durability and resilience against overcharging and operating temperatures. However, they encounter challenges in achieving widespread adoption for energy storage applications due to their low efficiency and the need for regular maintenance and electrolyte replacement, which adds to maintenance costs. This study evaluates and demonstrates the capabilities of Fe-Ni batteries for participating in grid energy storage applications. Stable performance was observed frequency regulation (FR) testing at 100% and 50% state of charge (SOC)s, while at 50% SOC, there was a 14% increase in efficiency compared to 100% SOC. Although 25% SOC achieved higher efficiency, limited cyclability was observed due to reaching the discharge cutoff voltage. Optimal SOC selection, battery monitoring, maintenance, and appropriate charging strategies of Fe-Ni batteries seem to be crucial for their FR applications. Fe-Ni batteries exhibit stable peak shaving (PS) results, indicating their suitability and reliability under various load conditions for PS testing. Extended cycling tests confirm their potential for long-term grid-scale energy storage, enhancing their appeal for PS and FR applications. [ABSTRACT FROM AUTHOR]

This study introduced a novel control approach based on fuzzy logic control (FLC) to enhance the frequency regulation capacity of variable-speed wind turbines (VSWTs). The proposed method integrates FLC within droop and inertia control loops. Real-time measurements of the system frequency and the rate of change of frequency (ROCOF) serve as inputs to the FLC, enabling the method to improve the frequency response by VSWTs. In addition, the method employs FLC for pitch angle frequency control, optimizing reserve power for frequency regulation under varying wind speed levels. The innovative aspect of this study lies in the simultaneous application of FLC to pitch angle frequency control and droop/inertia control, leading to the enhanced frequency regulation capability of VSWTs and smoother operation across a range of wind speeds. Compared with traditional methods, the proposed approach provides a comprehensive and effective solution to the challenges associated with frequency regulation in VSWTs. Through simulations across different wind speed scenarios, the proposed control method demonstrated the best performance among various mature methods, highlighting the efficacy of the proposed method on the frequency regulation of VSWTs under different wind speeds. This study's findings highlight the potential of the proposed FLC-based method to optimize frequency regulation and contribute to more reliable and efficient wind energy systems. [ABSTRACT FROM AUTHOR]

In order to reduce the negative influence of wind speed randomness and prediction error on frequency modulation, the reliability of the wind storage system was assessed effectively. In the wind storage frequency modulation system, a state of charge (SOC) adaptive adjustment method for wind speed randomness is proposed. Firstly, through the correlation analysis between the standby capacity of frequency modulation and the output power of wind turbine, the uncertainty of its frequency modulation capacity is revealed. Secondly, in view of the uncertainty of wind turbine frequency modulation, the output power of energy storage frequency modulation is optimized with the goal of minimizing the frequency modulation power deviation of the wind storage front under the framework of model predictive control, and the improved whale optimization algorithm (WOA) is used to solve the problem. Finally, the simulation results show that, under the given 5 min continuous disturbance, the root mean square of frequency regulation of the proposed restoration method is reduced by 56.65% compared to the SOC recovery base point set to 0.5. Under continuous large perturbations, the maximum frequency deviation is reduced by 0.0455 Hz. This effectively shows that this method can not only improve the frequency modulation reliability of wind power system but also improve the continuous frequency modulation capability of energy storage system. [ABSTRACT FROM AUTHOR]

This paper aims to properly manage the frequency within the Mexican interconnected system (MIS), composed of 158 generators, 2022 buses, 3025 lines, and a system composed of seven control areas working together to satisfy an operating condition with a demand of 20 GW. An extension of the conventional load frequency control formulation is used to execute studies for assessing the frequency behaviour in the different control areas of the MIS under sudden load increments. Likewise, to estimate the impact that variations in inertia in the different control areas may have on frequency stability. Energy storage elements are proposed by observing frequency excursions, which can provide fast support and avoid frequency nadir values below 0.025 Hz. In addition, they help to restore the nominal frequency. An optimisation formulation quantifies the storage required for the different control areas. The results exhibit an improvement in the transient frequency behaviour. On the other hand, when acquiring the energy storage elements, it is also considered prudent to use them for the ancillary services' benefit. With this purpose, a methodology is utilised to estimate the emission changes in the control regions based on the percentage reduction in displaced fossil fuel plants. Functions to determine the global emissions of different technologies for generating electricity were investigated hinged on actual historical data; through this, the diminution in polluting emissions is quantified. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In recent years, the development of hydrogen energy has been widely discussed, particularly in combination with renewable energy sources, enabling the production of "green" hydrogen. With the significant increase in wind power generation, a promising solution for obtaining green hydrogen is the development of wind-to-hydrogen (W2H) systems. However, the high proportion of wind power and electrolyzers in a large-scale W2H system will bring about the problem of renewable energy consumption and frequency stability reduction. This paper analyzes the operational characteristics and economic feasibility of mainstream electrolyzers, leading to the proposal of a coordinated hydrogen production scheme involving both a proton exchange membrane (PEM) electrolyzer and an alkaline (ALK) electrolyzer. Subsequently, a coordinated control based on Model Predictive Control (MPC) is proposed for system frequency regulation in a large-scale W2H islanded microgrid. Finally, simulation results demonstrate that the system under PEM/ALK electrolyzers coordinated control not only flexibly accommodates fluctuating wind power but also maintains frequency stability in the face of large disturbances. Compared with the traditional system with all ALK electrolyzers, the frequency deviation of this system is reduced by 25%, the regulation time is shortened by 80%, and the demand for an energy storage system (ESS) is reduced. The result validates the effectiveness of MPC and the benefits of the PEM/ALK electrolyzers coordinated hydrogen production scheme. [ABSTRACT FROM AUTHOR]

This paper proposes a hybrid technique for load frequency control (LFC) in an inter‐connected deregulated power‐system. The proposed method is the combination of a gannet optimization algorithm (GOA) and spiking neural network (SNN), hence, it is named as GOA‐SNN technique. The objective of the proposed method is to minimize frequency deviations within the power system (PS). By lessening the frequency‐deviation and tie‐line power variation, this approach ensures system frequency‐control under the effect of load disturbances. The GOA method is utilized to generate the set of control signals of the controller. The SNN method is used to predict the optimum gain parameter of the controller. By then the proposed method is run in MATLAB software and evaluated their performance with various existing approaches. The proposed method shows better results than other existing methods, such as Ant Lion Optimization (ALO), particle swarm optimization (PSO), and Salp Swarm Algorithm (SSA). The GOA‐SNN approach shows a low Area control error is 0.48% and a high efficiency is 96% compared with other existing approaches. [ABSTRACT FROM AUTHOR]

The question of how to simultaneously perform frequency regulation and integrated economic scheduling for microgrids with low-inertia islanding operation under communication constraints is a difficult problem that needs to be solved for many current applications. To this end, this paper establishes a microgrid scheduling control model containing a virtual synchronous generator (VSG) with multiple types of power sources and proposes a distributed optimization algorithm that integrates frequency regulation and comprehensive economic scheduling to simultaneously realize frequency regulation and economic scheduling in a microgrid. Firstly, a distributed economic dispatch problem is proposed based on a comprehensive consideration of the costs and benefits of various types of power VSGs, as well as the overall inertia and standby capacity requirements of the microgrid, which minimizes the integrated costs incurred by the participation of each type of VSG in the frequency regulation and improves the stable operation of the microgrid in terms of frequency under perturbation. Then, the optimal scheduling problem is solved by reconstructing the optimization problem based on considering the dynamic characteristics of microgrid inverters and using event-triggered communication to sense and compensate for the supply-demand imbalance online. The proposed method can avoid inter-layer coordination across time scales, improve the inertia, frequency regulation capability, and economy of the system, and enhance its robustness to short-term communication failures. Finally, simulation results are used to verify the effectiveness of the method. [ABSTRACT FROM AUTHOR]

The widespread global adoption of wind energy sources has established a significant presence in the existing power grid. However, the massive integration of intermittent wind energy poses forecasting errors, prompting the need for supplementary reserves from conventional energy sources with increased operational expenses and carbon emissions. Hence, to facilitate the seamless operation of large-scale wind-integrated power grids, it is imperative to harness the potential of renewable energy sources and leverage flexible loads to deliver power-balancing services. In this research, dynamic real-time power dispatch strategies have been developed for the Automatic Generation Control (AGC) system to integrate the reserve capacities of conventional generation units and wind power plants and utilize the demand response capabilities of flexible loads for power balancing services. A comprehensive power system grid model was developed in DigSilent PowerFactory software, consisting of coal-based energy systems, wind energy systems, gas turbines, and cold storage units as flexible loads. The study is divided into different case studies to assess the impact of each scenario on system operation in mitigating the forecasting errors of wind power plants. Further, a comparative analysis was performed to illustrate the effectiveness of each case study. The analysis showed that Case Study III, where reserves are provided by coal energy systems and cold storage units, yielded the highest reduction in Positive Regulation (PR) and Negative Regulation (NR) errors, at 89.0% and 94.15%, respectively. Conversely, Case Study IV demonstrated the least reduction in errors, with 67.82% in PR and 78.41% in NR. However, it indicates that reserves can be supplied from wind energy systems and flexible loads without the support of conventional power plants.

Traditionally, virtual inertia is used as the control strategy for wind turbines when participating in frequency regulation. However, it has inherent defects in measurement error amplification due to the frequency differential. Also, when control delay of wind turbines is taken into consideration, virtual inertia is essentially a fast power response, just the same as droop control. Hence, considering the adaptability of droop control, it is valuable to explore a novel droop control method without virtual inertia, as the frequency response model of wind turbines. For this reason, a multi-segment droop control strategy is proposed to provide a reliable frequency regulation model for wind turbines that can be broadly applied to other inverter-based power sources. Firstly, based on the extended system frequency response model, a differential equation including piecewise time-varying coefficients is established, and the analytical expression of the frequency response is obtained using the impulse function balancing principle and the integration by parts algorithm. Subsequently, based on analytical expression, the performance of the presented strategy is theoretically analyzed via comparison with virtual inertia control, and the conclusion that the presented multi-segment droop control has better frequency regulation performance can be got. Furthermore, to achieve optimal frequency regulation performance, a Lagrangian function is established to determine the optimal parameters of the proposed control strategy. Finally, the performance of the proposed strategy was verified in a two-area system model constructed on MATLAB/Simulink. Results show that the proposed multi-segment droop control has better frequency regulation performance.

The capability of a neuro-fuzzy control approach for frequency fluctuation damping in an isolated hybrid microgrid (IHMG) system (DEG/WTG /PV/FC/ESSs) is investigated in this paper. Due to the intermittent behavior of renewable energy sources (RESs) like wind turbines and photovoltaic arrays and the time-varying nature of demands, frequency fluctuation is more likely, specifically in the grid-connected mode. Model parametric uncertainties as well as load changes, wind power, and solar irradiation variations are the main uncertainty sources of the IHMG system. In the suggested approach, a neuro-fuzzy output feedback controller with three inputs that are inspired by PID control is designed considering the power balance between demands and generations, by optimizing fuzzy membership functions’ locations. The proposed controller is compared with two popular other methods on the investigated IHMG system in terms of time-domain characteristics. The outcome illustrates remarkable merit compared to the state-of-the-art methods in the presence of simultaneous disturbances and the model parametric uncertainties.

Frequency stability and security have been a vital challenge as large-scale renewable energy is integrated into power systems. In contrast, the proportion of traditional thermal power units decreases during the decarbonization transformation process, resulting in poor frequency support. This paper aims to explore the potential of frequency regulation support, dynamic assessment, and capacity promotion of thermal power plants in the transition period. Considering the dynamic characteristics of the main steam working fluid under different working conditions, a nonlinear observer is constructed by extracting the main steam pressure and valve opening degree parameters. The real-time frequency modulation capacity of thermal power units can provide a dynamic state for the power grid. A dynamic adaptive modification for primary frequency control (PFC) of power systems, including wind power and thermal power, is proposed and improved. The power dynamic allocation factor is adaptively optimized by predicting the speed droop ratio, and the frequency modulation capability of the system is improved by more than 11% under extreme conditions. Finally, through the Monte Carlo simulation of unit states of the system under various working conditions, the promotion of the frequency regulation capacity with high wind power penetration (WPP) is verified.

With the increasing proliferation of photovoltaic (PV) and wind power globally, frequency regulation by balancing generation and load in power systems is becoming increasingly difficult owing to reductions in dispatchable power and inertia. One countermeasure is autonomous load control, in which thermostatic loads and electric vehicle chargers quickly adjust the power consumption based on the grid frequency monitored by themselves without communication. However, testing the impact of such load controls on the frequency in actual power systems is too expensive. Therefore, a laboratory-scale isolated power system was prepared as a test bed to examine autonomous load control based on the rate of change of frequency (RoCoF) and the frequency deviation to cope with steep frequency fluctuations. Moreover, the experimental system was simulated numerically using MATLAB/Simulink. The experimental and simulation results are comparable, indicating that the simulation can be used to determine the total capacity and threshold when planning the introduction of autonomous control loads. The experimental and simulation results also show that frequency fluctuations can be mitigated by introducing autonomous control loads to the grid, and the response time can be improved by approximately 1 s by controlling the load based on the RoCoF.

Proton exchange membrane electrolyzers (PEMEL) installed with renewable energy resources can be used for power system ancillary services such as frequency regulation and virtual inertia emulation. However, the performance of PEMEL-based frequency ancillary services is threatened by cyberattacks that compromise the communication control. Considering denial-of-service (DoS) attacks on PEMEL communication, this paper proposes an enhanced resilient model predictive control (ER-MPC) for a PEMEL controller. The proposed ER-MPC consists of two procedures. First, the combination of autoregressive (AR) model-based prediction method and hold signal method is used to reconstruct attacked signals during severe DoS attacks. Then a model predictive control (MPC) is used to compute the control signal for PEMEL stack. The objective of ER-MPC-based controlling of PEMEL is to regulate the frequency deviation during contingency and normal operation under severe DoS attack. The effectiveness of the proposed ER-MPC was compared with that of AR-based resilient MPC and resilient MPC methods. The simulation results revealed that the proposed ER-MPC successfully improved microgrid frequency regulations under severe DoS attacks. In addition, the proposed ER-MPC-based PEMEL has a performance effect over other techniques in terms of the reduction in frequency deviation and the rate of change of frequency during severe DoS attacks, disconnection, and successful connection of wind turbine generation.

In modern power systems, the increasing penetration of renewable energy resources has reduced frequency stability. Consequently, wind turbines (WTs) are expected to participate in frequency regulation. By integrating the electrostatic energy stored in the DC capacitor with the kinetic energy stored in the rotating mass of the WT, an advanced control method is implemented to facilitate frequency regulation. However, previous studies have mainly concentrated on frequency control using WTs but ignored the rotor speed recovery of WT. Therefore, this work proposes a novel control strategy that separates the operating mode of a WT into two distinct states: the frequency support and the recovery of rotation speed stages. The proposed method improves the recovery process for rotor speeds after a WT participates in frequency support, returning the WT quickly to its normal operation to reduce wind energy loss. Furthermore, a new adaptive DC virtual inertia (DVIC) coefficient that utilizes real-time DC voltage to adjust the DVIC’s output smoothly is proposed. The proposed strategy is compared with other mature control strategies and implemented in PSCAD/EMTDC to verify their effectiveness and robustness. The simulation results demonstrate that the proposed method outperforms other mature methods because it reduces wind energy loss by at least 15 % when WTs participate in the frequency support process.

The high renewable penetrated power system has severe frequency regulation problems. Distributed resources can provide frequency regulation services but are limited by communication time delay. This paper proposes a communication resources allocation model to reduce communication time delay in frequency regulation service. Communication device resources and wireless spectrum resources are allocated to distributed resources when they participate in frequency regulation. We reveal impact of communication resources allocation on time delay reduction and frequency regulation performance. Besides, we study communication resources allocation solution in high renewable energy penetrated power systems. We provide a case study based on the HRP-38 system. Results show communication time delay decreases distributed resources' ability to provide frequency regulation service. On the other hand, allocating more communication resources to distributed resources' communication services improves their frequency regulation performance. For power systems with renewable energy penetration above 70%, required communications resources are about five times as many as 30% renewable energy penetrated power systems to keep frequency performance the same.

Power inverter adopting virtual synchronous generator (VSG) control can provide inertia support for distributed generation systems. However, it cannot take into account the dynamic regulation characteristics of frequency. Thus, when the system encounters a sudden change in load or disturbance, the dynamic process of frequency regulation will be greatly influenced. In view of this issue, an improved VSG control strategy based on a coordinated self-adaptive (CSA) method is proposed. The time domain analysis method is used to study the influences of virtual inertia and damping parameter perturbation on the system steady and dynamic performances. Furthermore, in order to make the control strategy suitable for large load changes and suppress frequency variations beyond the limit, the secondary frequency modulation is introduced into the control loop. Through the coordinated adaptive control of virtual inertia, virtual damping and frequency modulation, the dynamic performance of VSG frequency regulation can be obviously improved. Simulation and experiment results have verified the effectiveness of the proposed CSA control strategy.

To reduce the difficulty and enhance the enthusiasm of private-owned electric vehicles (EVs) to participate in frequency regulation ancillary service market (FRASM), a decision aid model (DAM) is proposed. This paper presents three options for EV participating in FRASM, i. e., the base mode (BM), unidirectional charging mode (UCM), and bidirectional charging/discharging mode (BCDM), based on a reasonable simplification of users' participating willingness. In BM, individual EVs will not be involved in FRASM, and DAM will assist users to set the optimal charging schemes based on travel plans under the time-of-use (TOU) price. UCM and BCDM are two modes in which EVs can take part in FRASM. DAM can assist EV users to create their quotation plan, which includes hourly upper and lower reserve capabilities and regulation market mileage prices. In UCM and BCDM, the difference is that only the charging rate can be adjusted in the UCM, and the EVs in BCDM can not only charge but also discharge if necessary. DAM can estimate the expected revenue of all three modes, and EV users can make the final decision based on their preferences. Simulation results indicate that all the three modes of DAM can reduce the cost, while BCDM can get the maximum expected revenue.

Frequency regulation of voltage source converter-based multi-terminal high-voltage direct current (VSC-MTDC) system with offshore wind farms enhances the frequency stability by compensating the power for a disturbed AC system. However, it is difficult to reasonably allocate frequency-regulation resources due to a lack of coordination mechanisms between wind farms and the MTDC system. Moreover, it is difficult for the frequency control of the wind farms to manage changes in wind speed; and the risk of wind-turbine stalls is high. Thus, based on the kinetic energy of wind turbines and the power margin of the converters, the frequency-regulation capability of wind turbines is evaluated, and a dynamic frequency-support scheme considering the real-time frequency-support capability of the wind turbines and system frequency evolution is proposed to improve the frequency-support performance. A power adaptation technique at variable wind speeds is developed; the active power in the frequency-support stage and restoration stage is switched according to the wind speed. A hierarchical zoning frequency-regulation scheme is designed to use the frequency-regulation resources of different links in the MTDC system with wind farms. The simulation results show that the novel frequency-regulation strategy maintains frequency stability with wind-speed changes and avoids multiple frequency dips.

The growing integration of renewable energy sources, especially offshore wind (OSW), is introducing frequency stability challenges to electric power grids. This paper presents a novel hybrid deloading control strategy that enables modular multilevel converter (MMC)-based wind energy conversion systems (WECSs) to actively contribute to grid frequency regulation. This research investigates a permanent-magnet synchronous generator (PMSG)-based direct-drive configuration, sourced from the International Energy Agency's (IEA's) 15 MW reference turbine model. Specifically, phase-locked loop (PLL)-free grid-forming (GFM) control is employed via the grid-side converter (GSC), and DC-link voltage control is realized through the machine-side converter (MSC), both of which boost the energy support for the integrated AC grid's frequency stability. This control strategy combines the benefits of over-speeding and pitch control modes, facilitating smooth transitions between different modes based on real-time wind speed measurements. In addition, the practical challenges of MMCs, such as circulating currents and capacitor voltage imbalances, are addressed. Numerical simulations under varying wind speeds and loading conditions validate the enhanced frequency regulation capability of the proposed approach. [ABSTRACT FROM AUTHOR]

In a renewable energy-based islanded microgrid system, frequency control is one of the major challenges. In general, frequency oscillations occur in islanded microgrids due to the stochastic nature of load and variable output power of distributed generating units (DGUs). In the presented research proposal, frequency oscillations are suppressed by implementing the proportional integral derivative (PID) controller-based control design strategy for an islanded microgrid. The modeling of the islanded microgrid is firstly presented in the form of a linearized transfer function. Further, the derived transfer function is approximated into its equivalent first-order plus dead time (FOPDT) form. The approximated FOPDT transfer function is obtained by employing the reaction curve method to calculate the parameters of the FOPDT transfer function. Furthermore, the desired frequency regulation is achieved for the manifested FOPDT transfer function by incorporating PID control design. For PID controller tuning, different rule-based methods are implemented. Additionally, comparative analysis is also performed to ensure the applicability of the comparatively better rule-based tuning method. The Wang–Chan–Juang (WCJ) method is found effective over other rule-based tuning methods. The efficacy of the WCJ method is proved in terms of transient response and frequency deviation. The tabulated data of tuning parameters, time domain specifications, and error indices along with responses are provided in support of the presented control strategy. [ABSTRACT FROM AUTHOR]

In this study, a frequency regulation is proposed that adjusts the release of rotational kinetic energy to ensure that a wind turbine remains near the maximum power point in the event of persistent under-frequency. The proposed scheme calculates wind turbine power by multiplying the frequency deviation with the variable control gain and then adding the resulting value to the torque controller power. Considering the operational characteristics of the wind turbine, separate control gains are applied in both the over-frequency section (OFS) and the under-frequency section (UFS). When the rotor speed approaches the maximum power point (MPP), the UFS control gain decreases, causing the wind turbine to gradually transition to maximum power point tracking (MPPT). This overcomes the limitations of conventional frequency regulation, enhancing both the power output of the wind turbine and the average grid frequency. To validate the proposed scheme, an IEEE 14 bus system, including a wind power plant and a photovoltaic plant, was simulated using the EMTP-RV simulator. The simulation results demonstrate that the proposed scheme effectively performs frequency regulation in the power grid regardless of the wind penetration. [ABSTRACT FROM AUTHOR]

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Controlling the collective behavior of micro/nanomotors with ultrasound may enable new functionality in robotics, medicine, and other engineering disciplines. Currently, various collective behaviors of nanomotors, such as assembly, reconfiguration, and disassembly, have been explored by using acoustic fields with a fixed frequency, while regulating their collective behaviors by varying the ultrasound frequency still remains challenging. In this work, we designed an ultrasound manipulation methodology that allows nanomotors to exhibit different collective behaviors by regulating the applied ultrasound frequency. The experimental results and FEM simulations demonstrate that the secondary ultrasonic waves produced from the edge of the sample cell lead to the formation of complex acoustic pressure fields and microfluidic patterns, which causes these collective behaviors. This work has important implications for the design of artificial actuated nanomotors and optimize their performances. [ABSTRACT FROM AUTHOR]