Frequency Regulation Performance Research Articles

Research on Frequency Regulation with Dynamic Trajectory Planning of Participation Factors

The energy transformation has led to a high proportion of new energy entering the grid. New energy has high randomness, which challenges the frequency stability of the power system. A new approach to improve frequency based on dynamic trajectory planning of participation factors is proposed in this work. In the frequency regulation interval, the trajectory and termination time of participation factors are regarded as the variables to be optimized. Then, taking the frequency regulation performance and economy as the goals, a multi-objective optimization problem is constructed. The participation factors are used to dispatch the output power of different units, which breaks the constraint that the output characteristics of different units are consistent in the original regulation process. Therefore, the generator units with different regulation characteristics in the system achieve complementary coordination on the second time scale. In simulation cases, frequency oscillation is reduced, while the overall economy of the system is improved. The numerical evaluation results show that the frequency performance is improved by 2.7% at most and 2.9% of the economy is improved at most simultaneously. The above results demonstrate the effectiveness of the proposed approach.

A Parameter-Adaptive Method for Primary Frequency Regulation of Grid-Forming Direct-Drive Wind Turbines

When wind turbines contribute to system frequency support using virtual synchronous generator (VSG) control, conventional VSG methods often fall short of meeting operational demands, particularly in terms of inertia and frequency support. In this study, considering both the frequency regulation and dynamic performance of VSG, a novel parameter design method that enhances frequency modulation capabilities is proposed in this paper. Initially, VSG control is integrated into the grid-side converter of a direct-drive permanent magnet synchronous generator (D-DPMSG) wind turbine. A small-signal model of the D-DPMSG-VSG active power is then formulated to analyze how the moment of inertia and damping coefficient impact system stability. Subsequently, ensuring that system parameter constraints are met, the key parameters of VSG are adaptively designed to dynamically adjust the system’s frequency and output power during transient responses. Finally, simulation results based on D-DPMSG-VSG in MATLAB/Simulink validated the feasibility, effectiveness, and advantages of the proposed parameter-adaptive VSG control strategy for enhancing the frequency modulation (FM) performance of wind turbines.

Adaptive VSG control of flywheel energy storage array for frequency support in microgrids

The application of virtual synchronous generator (VSG) control in flywheel energy storage systems (FESS) is an effective solution for addressing the challenges related to reduced inertia and inadequate power supply in microgrids. Considering the significant variations among individual units within a flywheel array and the poor frequency regulation performance under conventional control approaches, this paper proposes an adaptive VSG control strategy for a flywheel energy storage array (FESA). First, by leveraging the FESA model, a variable acceleration factor is integrated into the speed-balance control strategy to effectively achieve better state of charge (SOC) equalization across units. Furthermore, energy control with a dead zone is introduced to prevent SOC of the FESA from exceeding the limit. The dead zone parameter is designed based on the SOC warning intervals of the flywheel array to mitigate its impact on regular operation. In addition, VSG technology is applied for the grid-connected control of the FESA, and the damping characteristic of the VSG is decoupled from the primary frequency regulation through power differential feedback. This ensures optimal dynamic performance while reducing the need for frequent involvement in frequency regulation. Subsequently, a parameter design method is developed through a small-signal stability analysis. Consequently, considering the SOC of the FESA, an adaptive control strategy for the inertia damping and the P/ω droop coefficient of the VSG control is proposed to optimize the grid support services of the FESA. Finally, the effectiveness of the proposed control methods is demonstrated through electromagnetic transient simulations using MATLAB/Simulink.

An Integrated Frequency Regulation Method Based on System Frequency Security Posture

As the share of renewable energy in a grid increases, the grid’s frequency support capability weakens, and the spatial distribution of grid frequency becomes more pronounced. As a result, control strategies based on system frequency consistency and traditional frequency regulation dominated by synchronous machines are becoming increasingly inadequate for meeting the frequency regulation requirements of new-type power systems. To enhance the system’s frequency support capability, it is imperative to fully utilize the frequency regulation resources within the power system. To address this issue, this paper first introduces a system frequency security posture assessment method that accounts for the spatial distribution characteristics of the grid. Subsequently, a parameter optimization method for diverse frequency regulation resources is proposed in conjunction with the proposed comprehensive evaluation method for frequency regulation. Next, using a renewable energy feeder regional grid as an example, an integrated frequency regulation method based on the system frequency security posture is presented. Finally, the frequency regulation performance and economic costs of different frequency regulation methods are analyzed under various operating scenarios and disturbances using a model based on actual data from the renewable energy feeder regional grid. The simulation and index calculation results demonstrate that the method proposed in this paper effectively enhances the system’s frequency support capability, reduces the frequency disparity between different nodes within the grid, and maintains high economic performance.

Impact of Communication Time Delay in a 5G Network on Frequency Regulation Performance of a High Renewable Energy Penetrated Power System

Impact of Communication Time Delay in a 5G Network on Frequency Regulation Performance of a High Renewable Energy Penetrated Power System

VSG-LFC on multi-area power system under unsecured communication channel using hybrid trigger mechanism

This paper studies the frequency fluctuation problems of a multi-area power system with renewable energy sources (RESs) under denial-of-service (DoS) attacks. (i) Due to the decoupling of the RESs from power system using electronic devices, the RESs have no natural frequency response capability, which result in decreasing of entire power system equivalent inertia with large penetration of RESs. (ii) DoS attacks cause the insecurity of network communication, which can vanish data transmission and yield data packet dropout. To address the above issues, a virtual synchronous generator (VSG) incorporated with load frequency control (LFC) method (VSG-LFC) is proposed by introducing a hybrid-triggered mechanism (HTM) to (i) reduce the system sensitivity to the penetration level of RESs; (ii) compromise between frequency regulation performance and the reasonable usage of network resource under unsecured communication environments. Then, a switched system model is constructed considering non-identical DoS attack situations. Furthermore, theoretical analyses using Lyapunov functional related methods are carry out for asymptotical mean-square stability with H∞ performance on frequency regulation. Simulation evaluations of power system verify the effectiveness of this development. It shows that in a two-area power system frequency derivation performance indicators (IAE, ITAT, ISE) in Area1 are reduced by (82.996%, 86.273%, 85.823%) and in Area2 are reduces by (77.996%, 83.613%, 82.315%).

Correlating analysis and optimization between hydropower system parameters and multi-frequency oscillation characteristics

This paper aims to study the relationship between multi-frequency oscillation characteristics and parameters of hydro-turbine governing systems (HTGS), as well as improve the system oscillation quantification accuracy and primary frequency regulation performance. Firstly, an HTGS model with multi-frequency oscillation characteristics is established using an actual hydropower system as the object. Then, system oscillation components and the sources of each oscillating link are identified using eigenvalue and correlation analysis. To address the issue that sub-wave interference with dominant oscillation quantization, we innovatively incorporate correlation and frequency indexes into quantification process, and the dominant oscillations of complex HTGS are accurately quantified. On this basis, the detailed partitioning of control parameters is established to obtain the guide graph quickly reflecting the relationship between control parameters and system oscillations. Finally, an integrated optimization strategy with ultra-low frequency oscillation (ULFO) safety and regulation performance constraints is constructed, and control parameters are further optimized under two typical parameter setting methods. The results indicate over 90 % of the stable parameters enable the system to enter ULFO mode, and optimized control parameters utilizing proposed strategy increase regulation speed by 46 % while effectively suppressing ULFO. This paper provides a powerful tool and novel ideas for complex HTGS oscillation analysis and parameter optimization.

Quantifying the performance and compensation of secondary frequency regulation of pumped storage plants considering variable-speed operation

Aiming at the “net-zero carbon” target, a higher proportion of variable renewable energies (VREs) has been integrated into power grids, and pumped storage plants (PSPs) are crucial for guaranteeing the safe and stable operation of hybrid energy systems. As secondary frequency regulation (SFR) is related to the economic operation and the quality of auxiliary services provided by PSPs, it is critical to clarify its performance and compensation. Therefore, the corresponding quantitative evaluations of the SFR of pumped storage units (PSUs) are carried out in this paper. First, the performance of SFR is quantified based on the fuzzy analytic hierarchy process (FAHP). Considering the current situation in China’s electricity market, the average compensation of the PSP with each MW is determined to be 9.336 CNY per day, and a method for calculating the compensation of SFR is constructed. Then, taking a real Chinese PSP as an example, based on different wind power deviation signals, the quantitative evaluation of the compensation of SFR is conducted in accordance with the fixed-speed pumped storage units (FSPSUs) and the variable-speed pumped storage units (VSPSUs) in power priority and speed priority modes. The results show that the compensation of FSPSUs and VSPSUs (power priority mode and speed priority mode) is 10,900 CNY per day; 54,400 CNY per day; and 17,300 CNY per day. This paper could contribute to clarifying the compensation of SFR and providing technical support for the development of the auxiliary service market.

Performance enhancement and optimization of primary frequency regulation of coal‐fired units under boundary conditions

AbstractUnder the dual‐carbon goal, due to the long‐term operation of thermal power units under wide load and frequent fluctuating load after heat supply transformation, the dynamic process of subcritical units is modeled, and a frequency modulation optimization technology based on frequency signal accuracy is proposed to ensure the accuracy of the speed signal and improve the qualification rate of primary frequency modulation action. At the same time, the frequency regulation technology of steam engine side control optimization under boundary working conditions is proposed, so as to realize the sensitivity and rapidity of the digital electric hydraulic control system. The coordination optimization technology under boundary working conditions is proposed, and the primary frequency regulation performance of the unit is improved through a series of optimization adjustments. Finally, the engineering application is carried out and the optimization effect is analyzed.

Mixed Variable Parameter Energy Storage-Assisted Frequency Support Strategy

With the continuous increase in the installed capacity of new energy systems, the impact of power shocks on grid frequency is becoming more significant, seriously affecting the stability of the grid and thermal power units. For this reason, a mixed variable parameter energy storage-assisted frequency support control method is proposed. This method introduces an integral control mode based on the existing control mode and forms a co-ordinated control mode. The impact of the switching point of the mixed control mode is analyzed, and a new mode switching method is used. The model adjusts the frequency regulation parameters according to the different states of the grid frequency, making the frequency regulation more efficient. Finally, a frequency regulation model that integrates various improvement methods is built, and a 10 min continuous load disturbance is applied to compare and verify the frequency regulation performance of the model as a whole. The results indicate that the proposed control method can significantly improve the quality of grid frequency regulation, reduce the frequency deviation amplitude to 0.00096 p.u., reduce the participation time of thermal power units to 190.8393 s, and reduce the peak output to 0.1934 MW, demonstrating its engineering feasibility.

Multi-timescale analysis and quantification of dynamic regulation characteristics of DFIM-based variable-speed pumped storage units in alleviating wind power fluctuations

To comprehensively clarify the regulating role of variable-speed pumped storage system (VSPS) in alleviating wind power fluctuations, this paper quantitatively evaluates the multi-timescale frequency regulation performance of VSPS in a typical wind-hydro-pumped storage hybrid system (WHPHS). Firstly, the flexible equivalent frequency response models of VSPS and WHPHS are established. Then, the effectiveness of fixed-speed pumped storage system (FSPS) and VSPS in enhancing the stability of dominant hydropower system (HS) in WHPHS is compared, and the dynamic regulation behaviors between VSPS and FSPS are quantitatively evaluated. Based on the operational characteristics, the differences in the allocation of regulation responsibilities between VSPS/FSPS and HS for frequency regulation are clarified. The results indicate that VSPS contributes to an exhaustive improvement in HS stability, reduces the power fluctuation and frequency deviation of WHPSHS. Specifically, in the established simulation scenarios, WHPSHS with VSPS outperforms an equivalent FSPS in reducing frequency deviation frms by 20 %, power fluctuation Is by 40 %, and complementarity Ic by 50 %. Particularly effective in suppressing power fluctuations in range of 0.01 Hz to 0.8 Hz, which decreases the resonant peak of frequency deviation by 61.3 % compared to FSPS. It further highlights the regulatory advantages of VSPS in responding to low-amplitude high-frequency power variations. These findings can provide novel insights into the role of VSPS in mitigating RES fluctuations and energy management strategies in multi-type hybrid systems.

Multi-segment droop control and optimal parameter setting strategy of wind turbine for frequency regulation

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.

Variable Power Tracking Control Strategy of Doubly Fed Induction Generators for Fast Frequency Responses

Frequency regulation and droop control of doubly fed induction generators (DFIGs) can quickly respond to frequency changes and reduce the maximum rate of frequency (MROFF) in power systems. However, due to real-time dynamic changes in the MPPT control loop, the ability to improve the lowest frequency point is limited. Therefore, this article first describes an in-depth analysis of the dynamic characteristics of the incremental power of frequency regulation with droop control using an equivalent linear model. The limitations of improving the lowest frequency point under the influence of dynamic changes in the MPPT control loop are revealed. Secondly, to address the impact of these dynamics, an improved decoupling frequency regulation (IDFR) strategy based on power tracking is proposed, aiming to increase the maximum frequency deviation (MFD) and MROCOF. Then, in order to overcome the difficulty of adjusting control coefficients in the IDFR strategy, an adaptive control coefficient tuning fuzzy control method based on frequency deviation and ROCOF was proposed to flexibly adjust control requirements under various working conditions, thereby improving the control stability and performance of the system and effectively solving the problem of control coefficient allocation. Finally, to verify the frequency regulation performance of the proposed IDFR strategy under various operating conditions, simulations were conducted based on different disturbances and wind conditions. The results show that the proposed IDFR strategy significantly improves the system MFD and MROCOF improvement ability under various conditions.

Optimization of the Fast Frequency Regulation Strategy for Energy Storage-Assisted Photovoltaic Power Stations

Photovoltaic (PV) power generation is characterized by randomness and intermittency, resulting in unpredictable fluctuations in output power. This presents a significant challenge to the stable operation of the grid. To address this issue, the integration of energy storage systems provides a solution to mitigate the volatility of PV output, ensuring stability and precise control. In this study, we propose an ASS-Elman-based equivalent droop control strategy for PV power stations participating in grid frequency regulation. Furthermore, a joint PV-energy storage frequency regulation system is developed. For energy storage power stations actively engaged in grid frequency regulation, we employ an adaptive droop control strategy to enhance the traditional droop control method by incorporating additional frequency control strategies. We validate the effectiveness of the proposed strategies through simulation using MATLAB/SIMULINK. The results demonstrate that these strategies maximize the potential of energy storage and PV systems to comprehensively regulate frequency and significantly improve primary frequency regulation performance.

Suppression method of ultralow-frequency oscillation under ambient excitation in hydro-dominant power systems

Ultralow-frequency oscillations (ULFOs) have frequently occurred in hydro-dominant power systems in recent years. These phenomena seriously threaten the safe and stable operation of power systems. Therefore, measures that can effectively suppress ULFO need to be taken. Currently, the hydropower unit governor can enhance the dynamic stability and dampening oscillations of a system through adjusting the proportional–integral–derivative parameters. However, modifying these parameters can affect the primary frequency regulation performance, which compromises the assurance of grid frequency quality. This study proposes a switching type of hydro generator governor based on the local damping contribution rate to address the aforementioned problems. The approach incorporates the energy structure into the classical governor model, calculates the local damping contribution rate, and enables automatic switching of the hydro generator governor parameters based on positive and negative local damping contributions. This way allows for segmented control with different parameter settings, which enables the system to effectively consider the damping characteristics of ULFO while maintaining primary frequency regulation performance. It can also accurately and efficiently suppress the ULFO. The proposed method is verified through arithmetic analysis conducted on a 16-machine 5-zone system and an actual grid system. Simulation results demonstrate the effectiveness of the method.

An Adaptive V2G Capacity-Based Frequency Regulation Scheme With Integral Reinforcement Learning Against DoS Attacks

Aggregated electrical vehicles (EVs) can flexibly serve grid frequency regulation (FR) with adjustable FR capacity (FRC) via vehicle-to-grid (V2G) technology. Therefore, current research applies integral reinforcement learning (IRL) to FR as it can easily solve difficult modeling and optimization problems. However, communication between EVs is vulnerable to denial of service (DoS) attacks, which can significantly degrade FR performance and even destabilize V2G FR systems. This paper proposes an adaptive V2G FRC-based FR scheme with IRL to improve FR resilience and mitigate FR performance degradation against DoS attacks. The proposed scheme optimizes V2G control by IRL without analytical models, integrating an event-triggered mechanism to reduce communication burden. It adapts V2G FRC to attack intensity to minimize frequency deviation and mitigate the impact of DoS attacks. The analytical estimation of convergence rate establishes the quantitative relationships among control performance, V2G FRC, and attack intensity, thereby deriving an adaptive mechanism. The theoretical analysis of the proposed scheme yields stability conditions that guarantee the FR performance. The simulations were performed on the IEEE 39-bus test system to verify the effectiveness and advantages of the proposed scheme. The results indicate that V2G FRC should be scaled down to mitigate performance degradation when intensive attacks occur.

Battery Energy Storage Participation in Primary Frequency Regulation Considering SOC Consistency

Abstract In recent years, battery energy storage has garnered increasing attention in the frequency regulation field due to its rapid and precise output characteristics. The focus of this paper is on the control strategy for battery energy storage that is involved in primary frequency regulation and addresses the coordination control issues of different storage units when implemented on a large scale. A control method is proposed that considers the consistency of the State of Charge (SOC) in battery energy storage, which is involved in primary frequency regulation. The control of the battery energy storage system is divided into upper-level and lower-level control. The upper-level control uses model predictive control to obtain the total frequency regulation power of the energy storage station. The lower-level control allocates the corresponding power based on the capacity of each battery energy storage unit. It introduces a proportional integral adjustment term related to the average SOC to achieve SOC consistency control for each unit. Simulation results demonstrate that, regardless of whether the capacities of various storage units are identical, the proposed method achieves good frequency regulation performance, restores SOC to the ideal range, and ensures SOC consistency among different storage units. This approach aids the efficient and safe operation of battery energy storage systems.

Cooperative grid frequency control under asymmetric V2G capacity via switched integral reinforcement learning

In recent years, V2G techniques have been successfully implemented to stabilize frequency deviations in the grid caused by intermittent renewable energy sources. However, the battery capacity constraints and real-time dynamic driving demands of electric vehicles (EVs) in V2G systems hinder the coordination between V2G control and power plant frequency control strategies. It leads to the dynamic asymmetry of regulation up (RU) and regulation down (RD) frequency regulation (FR) capacity of V2G system, which can affect the performance of V2G FR. To cope with this problem, this paper proposes a switched integral reinforcement learning (SIRL) scheme for cooperative grid frequency control. The proposed scheme integrates V2G control with the power plant frequency control, which are cooperated with each other to complete FR tasks. A novel switched neural network (NN) structure is constructed for the training process of the SIRL algorithm to solve the problem of dynamic asymmetric FR capacity. A switched V2G utility function and a global cost function are constructed for RU and RD. Two independent subnetworks with the same structure are adopted for RU and RD learning to optimized V2G control parameters respectively under dynamic asymmetric output constraints. Two case studies of the IEEE 14-bus test system demonstrate the effectiveness and advantages of the proposed scheme.

Aggregate Modeling of Thermostatically Controlled Loads for Microgrid Energy Management Systems

Second-to-second renewable power fluctuations can severely hinder the frequency regulation performance of modern isolated microgrids, as these typically have a low inertia and significant renewable energy integration. In this context, the present paper studies the coordinated control of Thermostatically Controlled Loads (TCLs) for managing short-term power imbalances, and their integration in microgrid operations through the use of aggregate TCL models. In particular, two computationally efficient and accurate aggregate TCL models are developed: a virtual battery model representing the aggregate flexibility of TCLs considering solar irradiance heat gains and wall/floor heat transfers, and a frequency transient model representing the aggregate dynamics of a TCL collection considering communication delays and the presence of model uncertainty and time-variability. The proposed aggregate TCL models are then used to design a practical Energy Management System (EMS) integrating TCL flexibility, and study the impact of TCL integration on microgrid operation and frequency control. Computational experiments using detailed frequency transient and thermal dynamic models are presented, demonstrating the accuracy of the proposed aggregate TCL models, as well as the economic and reliability benefits resulting from using these aggregate models to integrate TCLs in microgrid operations.

Parameter adaptive model predictive control strategy of NPC three-level virtual synchronous generator

The Virtual Synchronous Generator (VSG) emulates the characteristics of a synchronous generator to provide inertia and damping for renewable energy systems. In the case of using the NPC three-level converter structure, traditional control methods require complex dual-loop control and internal PI parameter tuning. Furthermore, although fixed-parameter VSG control can provide inertia and damping when a significant power load is switched in an islanded microgrid, it cannot guarantee frequency regulation performance. To address these issues, this paper proposes an NPC three-level VSG parameter adaptive finite control set model predictive control strategy. This method eliminates the need for dual-loop control and PI parameter tuning. By incorporating angular velocity deviation and its rate of change into adaptive adjustment, a Tracking-Differentiator (TD) is designed to calculate the rate of change of angular velocity. This approach avoids frequent fluctuation of adaptive parameters during load power switching and improves the frequency stability of the microgrid. The effectiveness of the proposed strategy is validated through simulation and experimental verification.