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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]

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]

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]

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]

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]

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]

With the increasing proportion of renewable energy, the power system inertia decreases, and the operation uncertainty rises. It brings concerns about the system frequency and operational reliability. However, the impacts of the power system frequency performance on the reliability parameters of generation units have not been fully investigated. This paper studies the frequency performance and the operational reliability co-evaluation for power systems considering wind turbines. Firstly, a power system frequency regulation model is established considering the regulation capability of wind turbines. Then, the cluster of equivalent wind turbines is incorporated into the frequency regulation architecture of thermal power units, which accelerates the analysis of frequency performance. Then, the frequency performance of the power system with the participation of wind turbines under the operation uncertainty and the unit random faults is quantitatively analyzed. A frequency-dependent generator reliability parameter model is derived. Next, a multi-time scale co-evaluation framework is proposed to realize the co-evaluation of frequency performance and operational reliability. Case studies are carried out on the modified IEEE RTS-79 system and a provincial power system. Results show that compared with the existing research, the proposed method can obtain the frequency performance and reliability results efficiently. [ABSTRACT FROM AUTHOR]

The electric power system is rapidly transforming to address the urgent need for decarbonization and combat climate change. Integration of renewable energy sources into the power grid is accelerating, creating new challenges such as intermittency and uncertainty. To address these challenges, this paper proposes a new design of automatic generation control (AGC) ancillary service cost allocation based on the causer-pays rule. The proposed design treats reserves as inventory and aims to minimize them by allocating costs among consumers based on the causative factors for AGC operation. Two cost-allocation methods based on the causer-pays principle are introduced. The first method distributes costs according to the changes in loads causing ancillary service operation, while the second method considers opportunity costs. The case study on the IEEE 39 Bus System demonstrates that the proposed methods incentivize consumers to minimize volatility, resulting in reduced reserve requirements for system operation. In particular, the opportunity cost-based approach encourages loads and variable renewable energy (VRE) to actively reduce volatility, resulting in more efficient power system operation. In conclusion, the novel AGC ancillary service cost allocation methods offer a promising strategy for minimizing spinning reserves, increasing the power system's efficiency, and incentivizing consumers to actively participate in frequency regulation for a more sustainable and reliable electricity market. [ABSTRACT FROM AUTHOR]

In the context of the energy transition, electrical microgrids have become a key energy solution for isolated zones. For this type of application, low-voltage networks with unbalanced loads are commonly connected. Despite this, many of the hierarchical control strategies presented in the literature have been designed to operate properly only in the presence of balanced loads. For this reason, it is relevant to study how control strategies can be adapted to this scenario, especially those that reduce the dependence on communications to enhance flexibility and reliability. In this sense, this paper presents a secondary layer control strategy that does not require the use of communications to operate in isolated microgrids with unbalanced loads. The strategy guarantees proper performance in terms of power-sharing between the distributed generators of the microgrid. Simulations on Matlab/Simulink are presented to validate the response of proposal. [ABSTRACT FROM AUTHOR]

Integrating wind power with energy storage technologies is crucial for frequency regulation in modern power systems, ensuring the reliable and cost-effective operation of power systems while promoting the widespread adoption of renewable energy sources. Power systems are changing rapidly, with increased renewable energy integration and evolving system architectures. These transformations bring forth challenges like low inertia and unpredictable behavior of generation and load components. As a result, frequency regulation (FR) becomes increasingly important to ensure grid stability. Energy Storage Systems (ESS) with their adaptable capabilities offer valuable solutions to enhance the adaptability and controllability of power systems, especially within wind farms. This research provides an updated analysis of critical frequency stability challenges, examines state-of-the-art control techniques, and investigates the barriers that hinder wind power integration. Moreover, it introduces emerging ESS technologies and explores their potential applications in supporting wind power integration. Furthermore, this paper offers suggestions and future research directions for scientists exploring the utilization of storage technologies in frequency regulation within power systems characterized by significant penetration of wind power.

In the context of the energy transition, electrical microgrids have become a key energy solution for isolated zones. For this type of application, low-voltage networks with unbalanced loads are commonly connected. Despite this, many of the hierarchical control strategies presented in the literature have been designed to operate properly only in the presence of balanced loads. For this reason, it is relevant to study how control strategies can be adapted to this scenario, especially those that reduce the dependence on communications to enhance flexibility and reliability. In this sense, this paper presents a secondary layer control strategy that does not require the use of communications to operate in isolated microgrids with unbalanced loads. The strategy guarantees proper performance in terms of power-sharing between the distributed generators of the microgrid. Simulations on Matlab/Simulink are presented to validate the response of proposal.

To enhance the integration of solar power generation into the grid and harness the frequency regulation capabilities of distributed solar photovoltaics， a distributed photovoltaic cluster frequency control strategy based on EMPC （extended model predictive control） algorithm is introduced. Firstly， a fuzzy subspace clustering algorithm that takes account of cluster voltage stability and auxiliary frequency regulation performance is employed. Appropriate clustering indicators are selected to divide large-scale distributed photovoltaic units into distributed photovoltaic clusters based on these indicators. Next， based on the clustering results， a model for the distributed photovoltaic cluster is constructed. State expansion variables are introduced to obtain a dynamic predictive model for the system’s frequency response. An EMPC objective function that considers the output prediction error of the distributed photovoltaic cluster and the cluster control increment is designed to perform rolling optimization and feedback correction of the model. Finally， simulation analysis is conducted under various operating conditions. The results demonstrate that the proposed control strategy can enhance the frequency support capability of distributed photovoltaic clusters when integrated into the grid and reduce power losses in the system.

The rate of change of frequency (ROCOF) has become a key parameter to be monitored under high penetration of renewable energy. Any significant ROCOF should be mitigated immediately to avoid any shutdown of power plants and hence power interruptions to the customers. However, ROCOF is found to be significant and often in a region near to equatorial line because the power output of PV is highly intermittent due to a large number of passing clouds. Demand response (DR) is one of the most cost-effective means for mitigating any high ROCOF through controlling heating elements, refrigerators, and air-conditioners. However, most of the DR controllers use pre-determined conditions, also known as the condition-based approach, to switch the loads for reducing frequency changes. This approach may not be effective enough to respond to a new load condition. Furthermore, many DR controllers, including those accompanied by machine learning, are mainly developed to mitigate frequency changes with little focus on the mitigation of high ROCOF. Hence, an artificial neural network (ANN)-based controller is proposed in this article for frequency regulation with auto corrective efforts on high ROCOF under high intermittency of PV systems. The proposed controller is designed to manage several controllable loads on a grid emulator with PV systems at Universiti Tunku Abdul Rahman, Malaysia. It is shown that the proposed controller can reduce the frequency deviation by 23% and improve ROCOF by 19.7% as compared to that without any controller.

Electric power systems foresee challenges in stability, especially at low inertia, due to the strong penetration of various renewable power sources. The value of energy storage system (ESS) to provide fast frequency response has been more and more recognized. In this paper, we comprehensively evaluate the ESS candidates for inertial provisioning. Firstly, it provides the derivation of the formulae related to inertia emulation for various ESSs, and presents the feasibility analysis of the inertia delivery capabilities for various ESSs. Secondly, it presents a comprehensive comparison of the technological economics of various ESSs for inertia emulation, followed by a novel weighted metric to evaluate the suitability of each ESS for inertia provision. Moreover, this paper sheds light on the major heuristic optimization approaches for economic sizing and placement of ESS for optimal inertia allocation. Finally, this paper reviews future market and policy designs for the implementation of ESS for power system inertia provision.

Grid frequency regulation is essential for a reliable power grid. Whilst in distributed energy sources, (DERs) power fluctuations arise from the imbalance of frequency. There are multiple conventional and recent advanced frequency regulation techniques to dissolve this issue. The existing techniques using conventional controllers in microgrid control are well suited for voltage regulation, but the frequency cannot be adequately controlled using conventional and linear controllers. Most of the advanced control methods use algorithms to manage the grid frequency stability. This review comprehensively discusses the advanced control techniques for frequency regulation in micro-grids namely model predictive control, adaptive control, sliding mode control, h-infinity control, back-stepping control, (Disturbance estimation technique) kalman state estimator-based strategies, and intelligent control methods. Each control method is briefly explained along with recent advancements and corresponding governing equations. At glace, these control techniques are comparatively studied by elaborating future requirements.

As the penetration rate of wind turbines gradually increases, the fluctuation of system voltage and frequency significantly increases under power grid fault. In severe cases, wind turbines will disconnect from the grid, leading to large-scale power outages. In order to improve the stability of wind turbine grid connection, a large number of literature has studied the frequency and voltage regulation strategies. However, the existing fault ride through control methods mainly solve the problem of reactive power support during faults, while frequency regulation schemes focus on the frequency changes caused by load fluctuations. There is little research on methods that simultaneously consider voltage ride through and frequency regulation under power grid fault. This paper proposes a voltage and frequency regulation control strategy of wind turbines based on supercapacitors to address the above issues. By switching the functional modes of the energy storage device at different stages, wind turbines achieve the fault through and frequency recovery, thereby enhancing the fault tolerance ability. In the strategy, control process is divided into power grid fault period and fault recovery stage, and it adjusts the auxiliary priority level of energy storage devices based on the electrical response degree of different stages. During the fault, energy storage device is in voltage regulation stage because the voltage drop degree is greater than the frequency fluctuation, and it can ensure the wind turbine does not run off the grid by providing dynamic reactive power support to power grid. In the fault recovery stage, energy storage device is in the frequency regulation stage because of the large frequency deviation, it output active power to accelerate the system frequency recovery rating. Finally, the effectiveness of the control strategy proposed in this paper is verified through simulation.

The ever-growing proportion of renewable energy results in the decrease of frequency regulation capability of the multi-power system. Hence, to ensure the stability of the multi-power system with a high proportion of renewable energy, a novel day-ahead scheduling approach is proposed considering the frequency security constraint. Firstly, the dynamic changing process of frequency due to the power disturbance is analyzed. Secondly, a frequency security constraint considering the dynamic process is modeled and incorporated into the scheduling model of the multi-power system. The proposed scheduling model ensures that the maximal frequency deviation of the dynamic process is kept within the permitted range. Next, to ensure the stable operation of the system and make full use of renewable energy, the proposed scheduling model aims at minimizing the net load fluctuation and intermittent new energy curtailment. Finally, simulation results show that the proposed optimal scheduling model considering dynamic frequency security constraint can maintain the stability and frequency security of the multi-power system under power disturbance.

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.

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.

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.

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