Frequency Support Research Articles

Control and Stability of Grid-Forming Inverters: A Comprehensive Review

The large integration of inverter-based resources will significantly alter grid dynamics, leading to pronounced stability challenges due to fundamental disparities between inverter-based and traditional energy systems. While grid-following inverters (GFLIs) dominate current inverter configurations, their increased penetration into the grid can result in major stability issues. In contrast, grid-forming inverters (GFMIs) excel over GFLIs by offering features like standalone operation, frequency support, and adaptability in weak grid scenarios. GFMIs, unlike GFLIs, control the AC voltage and frequency at the common coupling point, impacting the inverter dynamic response to grid disturbances and overall stability. Despite the existing literature highlighting differences between GFLIs and GFMIs and their control strategies, a comprehensive review of GFMIs’ stability and the effects of their control schemes on grid stability is lacking. This paper provides an in-depth evaluation of GFMIs’ stability, considering various control schemes and their dynamics. It also explores different types of power system stability, introduces new stability concepts that correspond to power grids with integrated inverters, i.e., resonance and converter-driven stability, and reviews small-signal and transient stability analyses, which are the main two types of GFMI stability studied in the literature. The paper further assesses existing studies on GFMI stability, pinpointing research gaps for future investigations.

Empowering offshore wind with ES-STATCOM for stability margin improvement and provision of grid-forming capabilities

Offshore wind power plants (WPPs) play a pivotal role in achieving a CO2-neutral electricity sector. However, their grid connection presents significant challenges and costs. High-voltage alternating current (HVAC) offers a cost-effective solution, but it may necessitate the installation of a static synchronous compensator (STATCOM) at the onshore bus to ensure stability and compliance with connection requirements. Integrating energy storage into the STATCOM (ES-STATCOM) enables the provision of ancillary services, such as inertial response and frequency support, which require active power. This paper utilizes the generalized Nyquist criterion to demonstrate that operating the ES-STATCOM with grid-forming control enhances the stability margin of the grid-connected WPP when compared to operating it with grid-following control. Furthermore, it illustrates through network frequency perturbation (NFP) plots that the overall WPP, comprising grid-following wind turbines and a grid-forming ES-STATCOM, imparts grid-forming behavior at the grid-connection point.

Preferences of people with diabetes for diabetes care in Germany: a discrete choice experiment

ABSTRACT Objectives The objective of this study is to elicit health care preferences of people with diabetes and identify classes of people with different preferences. Methods A discrete choice experiment was conducted among people with diabetes in Germany comprising attributes of role division in daily diabetes care planning, type of lifestyle education, support for correct medication intake, consultation frequency, emotional support, and time spent on self-management. A conditional logit model and a latent class model were used to elicit preferences toward diabetes care and analyze preference heterogeneity. Results A total of 76 people with diabetes, recruited in two specialized diabetes care centers in Germany (mean age 51.9 years, 37.3% women, 49.1% type 2 diabetes mellitus, 50.9% type 1 diabetes mellitus), completed the discrete choice experiment. The most important attributes were consultation frequency, division in daily diabetes care planning, and correct medication intake. The latent class model detected preference heterogeneity by identifying two latent classes which differ mainly with respect to lifestyle education and medication intake. Conclusion While the majority of people with diabetes showed preferences in line with current health care provision in Germany, a relevant subgroup wished to strengthen lifestyle education and medication intake support with an aid or website.

Photovoltaic Power Injection Control Based on a Virtual Synchronous Machine Strategy.

The increasing participation of photovoltaic sources in power grids presents the challenge of enhancing power quality, which is affected by the intrinsic characteristics of these sources, such as variability and lack of inertia. This power quality degradation mainly generates variations in both voltage magnitude and frequency, which are more pronounced in microgrids. In fact, the magnitude problem is particularly present in the distribution systems, where photovoltaic sources are spread along the grid. Due to the power converter's lack of inertia, frequency problems can be seen throughout the network. Grid-forming control strategies in photovoltaic systems have been proposed to address these problems, although most proposed solutions involve either a direct voltage source or energy storage systems, thereby increasing costs. In this paper, a photovoltaic injection system is designed with a virtual synchronous machine control strategy to provide voltage and frequency support to the grid. The maximum power point tracking algorithm is adapted to provide the direct voltage reference and inject active power according to the droop frequency control. The control strategy is validated through simulations and key experimental setup tests. The results demonstrate that it is possible to inject photovoltaic power and provide voltage and frequency support.

Capacitor virtual inertia control and equivalent inertia analysis for a grid-forming wind generation system

A grid-forming wind generation system exhibits exceptional grid frequency support abilities. The DC capacitor of the grid-forming wind generation system, which is characterized by rapid response and high sensitivity to minor disturbances, can provide short-term inertia support for the power system. This paper proposes the capacitor virtual inertia control for the grid-forming wind generation system, coupling the DC capacitor voltage with the power system frequency, which enables the DC capacitor to participate in the system frequency response process and reduces the rate of change of the system frequency during the disturbance. To analyze the inertia of the wind power generation system, this paper establishes an equivalent Philips–Heffron model for the grid-forming wind generation system and uses the equivalent inertia constant to quantify the inertia of the wind power generation system. The effectiveness of the proposed control strategy and the reasonableness of the inertia assessment method are verified through simulations in the single-turbine system and the IEEE four-machine two-area system.

An optimal operation strategy of wind farm for frequency regulation reserve considering wake effects

When wind farms (WFs) participate in power system frequency regulation, deloaded control can increase the stored rotational kinetic energy in the wind turbines (WTs), thereby enhancing their frequency support capability. However, due to the wake effects and deloaded control of turbines, this method can also lead to increased power losses. An optimal operation strategy has been proposed to balance power generation and frequency regulation reserve in WFs, taking wake effects into account. Initially, a WF deloaded control model that considers wake effects, and an adaptive combined frequency control model based on kinetic energy reserve, are established for participation in power system frequency regulation. Subsequently, the Covariance Matrix Adaptation Evolution Strategy (CMAES) is utilized to determine the optimal operation allocation of maximum WF output power within the FLORIS wake model, meeting frequency regulation reserve requirements. A comparative analysis of the optimal allocation results under various wind conditions is conducted to test the frequency support capabilities. The results indicate that the proposed strategy can achieve varying levels of frequency regulation reserve, reduce wake losses to maximize output power under deloaded control, and improve frequency support capability.

Decentralized control strategy of thermostatically controlled loads considering the energy efficiency ratio and measurement error correction

The elimination of traditional thermal generators and the increase of renewable energy source access reduced the inertia of the power system, and thermostatically controlled loads have the potential to provide ancillary services to the power system. This paper introduces a decentralized control strategy for thermostatically controlled loads (TCLs), which focuses on assisting large-scale TCLs in providing frequency support to power systems while considering energy efficiency ratio and measurement error correction. Initially, the nonlinear relationship between heat flow and TCLs’ power is modeled using a polynomial relationship, and the coefficients are determined through a data-driven method to enhance accuracy in TCLs modeling and assess their regulation potential precisely. Subsequently, a decentralized control strategy tailored for power system frequency regulation is developed. To account for measurement errors in TCLs controllers, a measurement error back-correction method is proposed. Simulation examples demonstrate the effectiveness of the proposed control strategy in achieving accurate modeling and control of TCLs and reducing power system frequency fluctuations.

A methodological assessment to determine the frequency response of utility-scale deloaded PV under variability

Replacing the traditional synchronous generators with photovoltaic systems (PV) causes an overall reduction in grid inertia. Further, as the newly installed PV plants do not require any rotational mechanism to generate active power, they are not also able to ramp the generation during contingency situations leading to frequency collapse of the grid. To deal with this issue, a portion of peak solar generation can be kept as deloaded reserve which can be released during emergency conditions emulating the conventional system. However, the allocation of deloading as a percentage of PV power can introduce randomness on the expected support as the dispatched PV power varies depending on the irradiance and temperature values. Therefore, it is essential to accurately estimate the frequency support of a given deloading percentage to maintain frequency stability considering PV variability. In this regard, this study presents a generalized approach to determine the frequency response of deloaded support under utility-scale PV integration. To achieve this, linear and quadratic regression are employed to establish a mathematical correlation using the data derived from dynamic simulations conducted on a modified IEEE 39 bus grid at various PV penetration levels. The obtained results indicate a minimum generation of PV power is required to prevent under-frequency load shedding for a fixed deloading percentage. These findings are later verified by comparing them with two other techniques - battery energy storage system and synchronous condenser based on the simulated results achieved from DIgSILENT PowerFactory software. Moreover, this paper provides insights into how this required minimum PV generation changes with the variation in sanctioned deloading percentage. This can aid the grid designers to allow proper deloaded operation depending on the environmental condition.

Grid control strategy of wind turbines based on LADRC voltage control

Traditional grid-controlled wind turbines are required to rely on AC power grid operation, but when the power grid fluctuates, it will cause a series of oscillation instability problems in wind turbines, such as low-frequency oscillation, subsynchronous oscillation, etc. The safe and stable operation of the crisis power grid needs to be ensured. In this study, the virtual synchronous machine is supposed to be adopted as the main control strategy for grid-type control, transforming the traditional system into a more robust and reliable one. Additionally, a converter model of the grid-type control network is set up. By implementing grid-type control, voltage support and frequency support can be offered without relying solely on AC power grid operation. This approach effectively addresses issues caused by preventive such as reliance on wind turbines. The stability of the networked control system is dependent on maintaining stable system power. When there are fluctuations in system power, it impacts the stability of the networked control system. To mitigate these effects and enhance overall stability, this paper proposes using linear active disturbance rejection control (LADRC) based voltage and grid controls to suppress voltage fluctuations through linear active disturbance rejection techniques. The overall system performance is demonstrated through simulations conducted using Matlab/Simulink platform.

Fractional amplitude of low-frequency fluctuations in sensory-motor networks and limbic system as a potential predictor of treatment response in patients with schizophrenia

BackgroundPrevious investigations have revealed substantial differences in neuroimaging characteristics between healthy controls (HCs) and individuals diagnosed with schizophrenia (SCZ). However, we are not entirely sure how brain activity links to symptoms in schizophrenia, and there is a need for reliable brain imaging markers for treatment prediction. MethodsIn this longitudinal study, we examined 56 individuals diagnosed with 56 SCZ and 51 HCs. The SCZ patients underwent a three-month course of antipsychotic treatment. We employed resting-state functional magnetic resonance imaging (fMRI) along with fractional Amplitude of Low Frequency Fluctuations (fALFF) and support vector regression (SVR) methods for data acquisition and subsequent analysis. ResultsIn this study, we initially noted lower fALFF values in the right postcentral/precentral gyrus and left postcentral gyrus, coupled with higher fALFF values in the left hippocampus and right putamen in SCZ patients compared to the HCs at baseline. However, when comparing fALFF values in brain regions with abnormal baseline fALFF values for SCZ patients who completed the follow-up, no significant differences in fALFF values were observed after 3 months of treatment compared to baseline data. The fALFF values in the right postcentral/precentral gyrus and left postcentral gyrus, and the left postcentral gyrus were useful in predicting treatment effects. ConclusionOur findings suggest that reduced fALFF values in the sensory-motor networks and increased fALFF values in the limbic system may constitute distinctive neurobiological features in SCZ patients. These findings may serve as potential neuroimaging markers for the prognosis of SCZ patients.

Social health and subsequent cognitive functioning in people aged 50 years and older: examining the mediating roles of depressive symptoms and inflammatory biomarkers in two European longitudinal studies

Social health markers, including marital status, contact frequency, network size, and social support, have been shown to be associated with cognition. However, the mechanisms underlying these associations remain poorly understood. We investigated whether depressive symptoms and inflammation mediated associations between social health and subsequent cognition. In the English Longitudinal Study of Ageing (ELSA), a nationally representative longitudinal study in England, UK, we sampled 7136 individuals aged 50 years or older living in private households without dementia at baseline or at the intermediate mediator assessment timepoint, who had recorded information on at least one social health marker and potential mediator. We used four-way decomposition to examine to what extent depressive symptoms, C-reactive protein, and fibrinogen mediated associations between social health and subsequent standardised cognition (verbal fluency and delayed and immediate recall), including cognitive change, with slopes derived from multilevel models (12-year slope). We examined whether findings were replicated in the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K), a population-based longitudinal study in Sweden, in a sample of 2604 individuals aged 60 years or older living at home or in institutions in Kungsholmen (central Stockholm) without dementia at baseline or at the intermediate mediator assessment timepoint (6-year slope). Social health exposures were assessed at baseline, potential mediators were assessed at an intermediate timepoint (wave 2 in ELSA and 6-year follow-up in SNAC-K); cognitive outcomes were assessed at a single timepoint (wave 3 in ELSA and 12-year follow-up in SNAC-K), and cognitive change (between waves 3 and 9 in ELSA and between 6-year and 12-year follow-ups in SNAC-K). The study sample included 7136 participants from ELSA, of whom 3962 (55·5%) were women and 6934 (97·2%) were White; the mean baseline age was 63·8 years (SD 9·4). Replication analyses included 2604 participants from SNAC-K, of whom 1604 (61·6%) were women (SNAC-K did not collect ethnicity data); the mean baseline age was 72·3 years (SD 10·1). In ELSA, we found indirect effects via depressive symptoms of network size, positive support, and less negative support on subsequent verbal fluency, and of positive support on subsequent immediate recall (pure indirect effect [PIE] 0·002 [95% CI 0·001-0·003]). Depressive symptoms also partially mediated associations between less negative support and slower decline in immediate recall (PIE 0·001 [0·000-0·002]) and in delayed recall (PIE 0·001 [0·000-0·002]), and between positive support and slower decline in immediate recall (PIE 0·001 [0·000-0·001]). We did not observe mediation by inflammatory biomarkers. Findings of mediation by depressive symptoms in the association between positive support and verbal fluency and between positive support and change in immediate recall were replicated in SNAC-K. The findings of this study provide new insights into mechanisms linking social health with cognition, suggesting that associations between interactional aspects of social health, especially social support, and cognition are partly underpinned by depressive symptoms. EU Joint Programme-Neurodegenerative Disease Research (JPND) and Alzheimer's Society. For the Swedish translation of the abstract see Supplementary Materials section.

Frequency Support Strategy for Fast Response Energy Storage Systems

Frequency Support Strategy for Fast Response Energy Storage Systems

Stability analysis and application of a synchronverter-based control approach to DFIG-based wind energy conversion systems

This work proposes an enhanced control approach relying on the synchronverter concept for wind energy conversion systems (WECSs) based on the doubly-fed induction generator (DFIG). It consists of incorporating a virtual filter resistor into the control loop of the synchronverter, which is associated with the grid-side converter (GSC) aiming at emulating the behavior of a synchronous generator when providing ancillary services such as frequency support. A comprehensive state-space representation is derived to demonstrate that the virtual filter resistor is essential to ensure stability. After the proper adjustment of the model, it is possible to verify the effectiveness of the synchronverter-based control applied in the IEEE 14-bus modified system employing parameters obtained from a real power plant. The results show that the application of the introduced method results in less severe frequency dips and faster transient response during frequency support even when compared with the case in which only synchronous machines are connected to the grid.

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.

Smooth Transition Control Strategy for Operation Modes of Optical Storage Microgrid based on VSG

Addressing the challenge of suppressing voltage and frequency oscillations during mode transitions and achieving smooth transitions between grid-connected and islanded operation modes in peer-to-peer structured optical storage microgrids, is an urgent technical issue. This paper proposes a control strategy for smooth mode transitions based on numerical soft starters, focusing on the dynamic characteristics of voltage and frequency in optical storage microgrids during grid-connected and islanded operation modes. The numerical soft starter smoothens the input reference value of the current inner loop, reducing the impact of transient surge current on the current inner loop during transitions, thus ensuring the oscillations of bus voltage and frequency during microgrid mode transitions. In islanded operation mode, a VSG control strategy is introduced by constructing a small signal model to analyze the frequency response characteristics of the system under different inertia and damping characteristics, setting appropriate control parameters to provide strong frequency support for the system during islanded operation. Finally, an optical storage microgrid system is established using Matlab/Simulink to conduct simulation experiments under conditions such as grid-connected/islanded mode transitions, load fluctuations, and sudden changes in photovoltaic output power, validating the effectiveness of the proposed smoothing strategy.

Fuzzy Adaptive Frequency Support Control Strategy for Wind Turbines With Improved Rotor Speed Recovery

Fuzzy Adaptive Frequency Support Control Strategy for Wind Turbines With Improved Rotor Speed Recovery

Nonlinear Model Predictive Control for Droop-Based Grid Forming Converters Providing Fast Frequency Support

Nonlinear Model Predictive Control for Droop-Based Grid Forming Converters Providing Fast Frequency Support

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

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

Decentralized utilization of distributed energy storage resources for simultaneous frequency regulation in a microgrid

A microgrid has emerged for the transformation from centralized into localized electricity generation, which increases the opportunity for renewable-based distributed generators (DGs) applications such as photovoltaic (PV) and wind as well as small-scale conventional generation units. PV and wind integration provides environmental, technical, and economic benefits. However, the low inertia of the PV system and decoupling due to the presence of the power electronics converter in the wind generation system led to a significant declination in the microgrid's inertia, which causes an excessive frequency nadir and a high rate of change of frequency (ROCOF) in the presence of disturbances. The microgrid's inertia can be enhanced by storing or releasing energy within the microgrid. The wind generation system has intrinsic kinetic energy stored in the rotating parts, while the PV system's sorted energy is improved by introducing an external supercapacitor on the DC link. The aforementioned energy storage elements provide limited energy resources, which should be employed in a proper manner. This article proposes a control scheme to boost the cooperation of wind and PV generation systems for the enhancement of inertia and frequency support. Therefore, the proposed scheme prevents excessive stress on individual generators and improves the utilization of available energy resources. For example, at load increase by 0.5 MW, with frequency support using PV only or wind only, the frequency deviation is enhanced by 44.4 % and 29.5 %, respectively. While for both PV and wind support the frequency simultaneously, the frequency deviation is enhanced by 53.3 %. In addition, with the cooperation of PV and wind, the required energy from PV and wind is reduced by 29.5 % and 13.7 % respectively and the rate of change of frequency is enhanced by 61.9 %. The energy share among PV and wind generation systems is investigated and verified by simulations; tuning formulas are also developed to attain predefined energy support with equal energy sharing among different resources. For instance, with a non-equal energy share strategy and load increases by 0.5 MW, the wind delivers almost 1.6 times the energy delivered from the PV. Hence, more stress occurs on the wind generation compared to PV. While, using equal energy share strategy, the required energy from wind is about 1.03 times the energy delivered from the PV. The proposed control scheme is applied to an AC microgrid that comprises a thermal generation plant, a PV generation system, and a doubly-feed induction generator-based wind generation system. To verify the effectiveness of the proposed scheme, different simulation cases considering load change, wind speed variation, irradiance variations, and weak grid integration are implemented. When compared to individual frequency support, the proposed scheme provides a superior response.

Evaluating the Fast Frequency Support Ability of the Generation Units in Modern Power Systems

Modern power systems include synchronous generators (SGs) and inverter-based resources (IBRs) that provide fast frequency support (FFS) to the system. To evaluate the FFS ability of both SGs and IBRs under a unified framework, this paper proposes a method that evaluates the FFS ability of each generation unit via its dynamic trajectories of the active power output and the frequency following a contingency. The proposed method quantified FFS ability via two indexes, namely, the equivalent inertia constant and the equivalent droop, of each generation unit. The Tikhonov regularization algorithm is employed to estimate the FFS ability indexes. The New England 10-machine system serves to validate the feasibility and accuracy of the proposed method and illustrate the different FFS ability of the grid−forming and grid−following IBRs.