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

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

High voltage direct current （HVDC） transmission based on modular multilevel converter （MMC） is widely used in large-scale renewable energy delivery. However， the lagged inertia of MMC controllers may undermine the small-signal stability. Firstly， the mechanical inertia of synchronous generators is analyzed， and a second-order unified expression of inertia applicable to MMC controller is proposed. Secondly， based on the dynamic and inertial delay of MMC closed-loop controller， a small-signal stability criterion for MMC controller connected to weak power grid is presented. Finally， through simulation analysis of a double-side MMC grid-connected system， the correctness of the proposed stability criterion is validated.

DC side dynamics are ignored in most of the research on grid-connected converter, which is dealt as a constant voltage source. In this case, the analysis result of small-signal stability is affected to some extent. In this paper, the impedance model of grid-following converter is reconstructed, then followed by stability analysis of the system considering DC side dynamics. Firstly, the applicable conditions are analyzed, that is to say, DC side is equivalent whether to voltage source or controlled current source. It is demonstrated that the DC side dynamics must be considered in case of small-signal stability analysis. Then, the impedance model of the grid-following converter is established based on harmonic state-space (HSS). Secondly, the stability of the system with different DC side structures is analyzed by Bode criterion under different grid strengths. Subsequently, it is revealed that the influence mechanism of grid strength on the stability of grid-following converter. In addition, the influence of different links on impedance characteristics of the system is analyzed, including phase-locked loop, current loop and filter. Finally, the theoretical analysis and electromagnetic transient simulation results show that under the condition of weak grid, the interaction between phase-locked loop and grid is strengthened, which reduces the small-signal stability of the system. Moreover, the critical short-circuit ratio of the system considering the DC side dynamics is larger.

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. [ABSTRACT FROM AUTHOR]

The effective operation of model-based control strategies in modern energy systems, characterized by significant complexity, is contingent upon highly accurate large-scale models. However, achieving such precision becomes challenging in complex energy systems rife with uncertainties and disturbances. Controlling different parts of the energy system poses a challenge to achieving optimal power system efficiency, particularly when employing model-based control strategies, thereby adding complexity to current systems. This paper proposes a novel model-independent control approach aimed at augmenting transient stability and voltage regulation performance in multi machine energy systems. The approach involves the introduction of an optimized model-free fractional-order-based excitation system stabilizer for synchronous generators in a multi machine energy system. To overcome the limitations associated with complex system model identification, which add degrees of simplification at defined operating conditions and assume the system model remains fixed despite high uncertainty and numerous disturbances, an optimal model-independent fractional-order-based excitation control strategy is introduced. The efficacy of the proposed approach is validated through comparative numerical analyses using the MATLAB/Simulink environment. These simulations were conducted on a two-area, 12-bus multi-machine power system. Simulation results demonstrate that the presented excitation system stabilizer outperforms conventional controllers in terms of transient and small-signal stability. It also suppresses the low-frequency electromechanical oscillations within the multimachine energy system. [ABSTRACT FROM AUTHOR]

The development of regional integrated electric-thermal energy systems (RIETES) is considered a promising direction for modern energy supply systems. These systems provide a significant potential to enhance the comprehensive utilization and efficient management of energy resources. Therein, the real-time power balance between supply and demand has emerged as one pressing concern for system stability operation. However, current methods focus more on minute-level and hour-level power optimal scheduling methods applied in RIETES. To achieve real-time power balance, this paper proposes one virtual asynchronous machine (VAM) control using heat with large inertia and electricity with fast response speed. First, the coupling time-scale model is developed that considers the dynamic response time scales of both electric and thermal energy systems. Second, a real-time power balance strategy based on VAM control can be adopted to the load power variation and enhance the dynamic frequency response. Then, an adaptive inertia control method based on temperature variation is proposed, and the unified expression is further established. In addition, the small-signal stability of the proposed control strategy is validated. Finally, the effectiveness of this control strategy is confirmed through MATLAB/Simulink and HIL (Hardware-in-the-Loop) experiments. [ABSTRACT FROM AUTHOR]

The frequency deviation from the nominal working frequency in power systems is a consequence of the imbalance between total electrical loads and the aggregate power supplied by production units. The sensitivity of energy system frequency to both minor and major load variations underscore the need for effective frequency load control mechanisms. In this paper, frequency load control in single-area power system with multi-source energy is analysed and simulated. Also, the effect of the photovoltaic system on the frequency deviation changes in the energy system is shown. In the single area energy system, the dynamics of thermal turbine with reheat, thermal turbine without reheat and hydro turbine are considered. The simulation results using Simulink/Matlab and model analysis using eigenvalue analysis show the dynamic behaviour of the power system in response to changes in the load. [ABSTRACT FROM AUTHOR]

The power system stabilizer (PSS) is vital to enhance the dynamic stability of the electrical grid. The conventional PSS, designed at a fixed operating point may fail to retain the system stability in real life due to varying system conditions. Hence, it is essential to develop a robust stabilizer that guarantees system stability and gives the best performance under wide-range scenarios. This research work presents a novel method to design a robust PID-PSS utilizing a decentralized approach. The extended multi-machine power system is divided into subsystems in this study. To depict broad operating conditions resulting from widespread system conditions, a transfer function with interval coefficients is developed for each subsystem. The necessary and sufficient constraints for robust stability are derived using a systematic way, and a performance index is devised to improve PSS performance. Global search and fmincon tool in MATLAB is employed to identify robust controller gains. The proposed method's efficacy is demonstrated using a two-area, 10-bus, four-machine system. The system is tested for short circuit faults that are both symmetrical and asymmetrical, as well as load disturbances. The proposed controller's robustness and superiority over the existing are demonstrated by nonlinear simulation results. [ABSTRACT FROM AUTHOR]

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

Small-signal stability analysis is essential for the safe operation and parameter design of power electronic-dominated grids. Unbalanced conditions introduce more frequency-coupling terms, which are unneglectable in the stability assessment. This paper proposes a novel Linear Time-Periodic (LTP) theory-based stability analysis method and focuses on grid-connected voltage-source converters (VSCs) without improved unbalancing controls. Firstly, the analysis of fundamental solutions of the LTP system reveals that each LTP mode is characterized by a unique damping factor and multiple oscillation frequencies, defined by LTP eigenvalues and related transformation vectors, i.e., (λi,Vi(t)). Then, a method for calculating (λi,Vi(t)) is proposed using the characteristic matrix of the Harmonic State-Space (HSS) model. An iterative sorting method based on the time-domain interpretation of HSS eigenvalues/eigenvectors is proposed to determine accurate (λi,Vi(t)) in the case of the minimum truncation order. Finally, generalized definitions and calculation methods of the widely used indicators for modal analysis are presented to assess system stability and guide the parameter design. Numerical and simulation results verify the proposed stability analysis method and indicate its advantages compared to the existing Floquet and HSS methods.

DC microgrids, considered building blocks of smart grid technologies, are subjected to small-signal instability due to the extensive introduction of power electronics devices. Therefore, in this paper, a sequence Virtual Filter (VF) controller, which considers not only the longitudinal virtual parameters but also the lateral capacitance and resistance, is first developed to increase the flexibility of system stability adjustment compared to the Virtual Impedance (VI) controller. Then, as distribution feeders are normally unbalanced and the application of the proposed sequence VF controller may amplify the distortion of imbalances on DC voltage, a novel Reference Current Generation (RCG) strategy considering the VF controller is proposed for Grid-Connected Converter (GCC) to improve DC microgrid power quality. The double-frequency fluctuation of the DC-link voltage is eliminated by regulating the oscillation of the active power flowing into the converter instead of the Point of Common Coupling (PCC) to 0. The PSCAD simulation results illustrate that the sequence VF controller can enhance the stability adjustment since, in some cases, the system can only be stabilized by adjusting lateral parameters. On the other hand, the proposed RCG strategy can significantly reduce DC voltage fluctuations compared to the traditional approach. Furthermore, incorporating the proposed strategy with the sequence VF controller offers greater flexibility in reducing the negative-sequence current while maintaining a power transfer capacity for GCCs in a master–slave-based DC microgrid, comparable to that of the traditional strategy.

The frequency deviation from the nominal working frequency in power systems is a consequence of the imbalance between total electrical loads and the aggregate power supplied by production units. The sensitivity of energy system frequency to both minor and major load variations underscore the need for effective frequency load control mechanisms. In this paper, frequency load control in single-area power system with multi-source energy is analysed and simulated. Also, the effect of the photovoltaic system on the frequency deviation changes in the energy system is shown. In the single area energy system, the dynamics of thermal turbine with reheat, thermal turbine without reheat and hydro turbine are considered. The simulation results using Simulink/Matlab and model analysis using eigenvalue analysis show the dynamic behaviour of the power system in response to changes in the load.

This paper investigates the dynamic patterns in the small-signal behavior of power systems with wind power generation. The interactions between synchronous generators and wind generators are investigated. In addition, the impact of increased wind generation penetration on the damping and frequency of the synchronous generator's electromechanical oscillations is addressed. Wind generators of three different technologies are considered throughout this study. Very detailed dynamic models of wind generators are used and detailed. [ABSTRACT FROM AUTHOR]

In the modern power grid, characterized by the increased penetration of power electronics and extensive utilization of renewable energy, inverter-based power plants play a pivotal role as the principal interface of renewable energy sources (RESs) and the grid. Considering the stability characteristics of grid-following (GFL) inverters when the grid is relatively weak, the application of grid-forming (GFM) controls becomes imperative in enhancing the stability of the entire power plant. Thus, there is an urgent need for suitable and effective models to study the interaction and stability of the paralleled inverters employing GFL and GFM controls. Thus, the small-signal modeling with full-order state-space model and eigenvalues analysis are presented in this paper. First, the small-signal state-space model of the individual GFL and GFM inverters is obtained, considering the control loop, interaction, reference frame, transmissions, and time delays. Then, the models of the individual inverter are extended to the hybrid inverters to study the effects of the GFM inverters on the small-signal stability of the entire system. And the impacts of the inertia and damping are analyzed by the eigenvalues of the state-transition matrix. A case comprising three parallel GFL inverters and two GFL inverters with one GFM inverter, respectively, are studied to examine the effectiveness and accuracy of the model. Finally, the stability margin obtained from the eigenvalue analysis of the entire system is verified by time-domain simulations. [ABSTRACT FROM AUTHOR]

Challenges in the operation of power systems arise from several factors such as the interconnection of large power systems, integration of new energy sources and the increase in electrical energy demand. These challenges have required the development of fast and reliable tools for evaluating the operation of power systems. The load margin (LM) is an important index in evaluating the stability of power systems, but traditional methods for determining the LM consist of solving a set of differential-algebraic equations whose information may not always be available. Data-Driven techniques such as Artificial Neural Networks were developed to calculate and monitor LM, but may present unsatisfactory performance due to difficulty in generalization. Therefore, this article proposes a design method for Physics-Informed Neural Networks whose parameters will be tuned by bio-inspired algorithms in an optimization model. Physical knowledge regarding the operation of power systems is incorporated into the PINN training process. Case studies were carried out and discussed in the IEEE 68-bus system considering the N-1 criterion for disconnection of transmission lines. The PINN load margin results obtained by the proposed method showed lower error values for the Root Mean Square Error (RMSE), Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE) indices than the traditional training Levenberg-Marquard method. [ABSTRACT FROM AUTHOR]

This paper investigates the small-signal stability of a DC shipboard power system (SPS) with the integration of a supercapacitor. As an efficient energy storage solution, supercapacitors can not only provide rapid energy response to sudden power demand spikes, effectively mitigating load fluctuations, but also enhance the system's resilience to disturbances. In the context of the parallel operation of two Permanent Magnet Synchronous Generators (PMSGs), the inclusion of supercapacitors may alter the system's dynamic behaviors, thereby affecting its small-signal stability. This paper develops the small-signal model of SPS and explores the small-signal model under various power distribution strategies in the parallel operation of diesel generator sets. Through the calculation of eigenvalues and influence factors, the system's oscillation modes are analyzed, and key parameters affecting the stability of the DC distribution system are identified. Furthermore, this paper meticulously examines the specific impacts of electrical and control parameter variations on the system's small-signal stability. Simulation experiments validate the accuracy of the small-signal stability analysis after supercapacitor integration into SPS. [ABSTRACT FROM AUTHOR]

The small-signal stability of multi-terminal high voltage direct current (HVDC) systems has become one of the vital issues in modern power systems. Interactions among voltage source converters (VSCs) have a significant impact on the stability of the system. This paper proposes an interaction quantification method based on the self-/en-stabilizing coefficients of the general $\boldsymbol{N}-\mathbf{terminal}$ HVDC system with a weak AC network connection. First, we derive the explicit formulae of self-/en-stabilizing coefficients for any $\boldsymbol{N}-\mathbf{terminal}$ HVDC system, which can quantify the interactions through different paths analytically. The relation between the self-/en-stabilizing coefficients and the poles of the system can be used to evaluate the impact of the interactions on the system stability effectively. Then, we employ the obtained formulae to analyze the parameter sensitivity and explain how a parameter affects the stability of the system through different paths of interactions. Finally, extensive examples are given to demonstrate the effectiveness of the proposed method.

Energy storage system based on grid-forming converter (GFMC) is regarded as the key equipment in photovoltaic (PV) system for energy consumption and inertia improvement. However, the design of GFMC aiming at stability improvement of PV & energy storage system (PVESS) is still open to public. Hence, this study takes the PVESS composed of photovoltaic grid-following converter (GFLC) and energy-storage GFMC as the research object, explores the impact of GFMC on the PVESS stability under different operating conditions, and proposes a stability-oriented parameter design method for GFMC. Firstly, the impact of operating conditions on the output impedance of GFLC and GFMC in PVESS is analyzed. Secondly, by treating the GFMC and the grid as an equivalent grid (i.e., an equivalent subsystem) and taking into account the operating status of PVESS, the system stability under different operating conditions is discussed in detail. Results show that the PVESS stability is the worst when the PV output is maximum, and, because the output impedance of GFMC in low-to-mid frequency range is dominated by its filter inductor, the strength of the equivalent grid is seriously affected by the GFMC filter inductor. Hence, as the key factor affecting the PVESS stability, the GFMC filter inductor deserves a careful selection. Subsequently, a comprehensive design for GFMC filter and control parameters is proposed, which can effectively improve the PVESS stability under the weak grid. Hardware-in-the-loop (HIL) experiments are conducted to verify the effectiveness of the proposed method.

This paper aims to develop a small-signal stability analysis method for large-scale power electronics-based power systems. For this purpose, the nodal admittance matrix (NAM)-based approach is recognized as the most precise technique. However, the original implementation of NAM method is tailored for the entire system, thereby correlating the matrix dimensions with the number of converters present in the system. Consequently, it becomes impractical to directly apply the original NAM method to a large-scale system. To address this challenge, this paper introduces a novel system-partitioning-based NAM approach. In this method, the large-scale system is decomposed into several subsystems first, followed by analysis at the interconnection level. The general concept, the detailed mathematical derivation, and the applications of the proposed method to a 6-converter system and a modified 140-bus NPCC system are presented. It has been validated that the proposed approach can significantly reduce computational burden while simultaneously preserving the accuracy for large-scale PE-rich power systems.

The high-voltage voltage-source converter (VSC)-based multi-terminal dc (MTDC) grid is a key technology for integrating offshore wind energy and enabling bulk power transmission across nations and continents. This paper addresses the small-signal stability of an MTDC grid equipped with a power flow controller (PFC) under extremely weak ac system interconnections. Using a comprehensive linearized state-space model, eigenvalue analysis uncovers that beyond the well-documented low-frequency oscillations (LFO), an MTDC grid may experience unstable medium-frequency oscillations (MFO) under rectifier operation of droop voltage-controlled VSCs when interfaced to an extremely weak ac system. Moreover, it was shown that the most challenging scenario is when multiple droop voltage-controlled VSCs are interfaced to very weak ac systems, with unstable LFO and MFO observed at short-circuit ratio values of 1.4 and 1.8, respectively. Sensitivity analysis is conducted to assess the impact of the droop voltage control gains, PFC control parameters, and dc breaker reactor on the system dominant eigenmodes in such critical weak conditions. Simple yet efficient LFO and MFO compensators are proposed to stabilize the system, and their parameters design was detailed. Extensive simulation studies and real-time validation tests verify the analytical analysis and demonstrate the effectiveness of the proposed compensators and their feasibility for real-time implementation.

The sub-synchronous oscillation (SSO) phenomenon presents a significant risk to the overall safety and stability of power networks, as evidenced by numerous real-world incidents. This paper introduces a novel approach to mitigating SSO in series-compensated transmission lines by employing a resonant controller in conjunction with a control loop for the doubly fed induction generator (DFIG). To begin, the resonant controller is integrated into the converter controllers of the DFIG system to determine the optimal placement that yields enhanced damping characteristics. Subsequently, an analysis is conducted to explore the impact of different parameters associated with the resonant controller on system stability, with the goal of identifying the most suitable parameter configuration. The proposed control strategy is thoroughly evaluated through time-domain simulations and small signal stability analysis, considering various compensation levels, wind speeds, and sub-synchronous control interactions (SSCI). Furthermore, a comparative analysis is performed between the proposed method and a recent SSO damping technique to validate the efficacy and robustness of the proposed approach. The results of the comparison clearly demonstrate the superiority and effectiveness of the proposed control strategy in alleviating SSO. Specifically, the proposed method achieves the shortest SSO damping time across all feasible operational scenarios, thereby reinforcing its practical value and applicability.

A distributed-power-generating source (DPGS) is intended to locally supply the increased power demand at a load bus. When applied in small amounts, a DPGS offers many technical and economic benefits. However, with large DPGS penetrations, the stability of the transmission system becomes a significant issue. This paper investigates the stability of a transmission system equipped with a DPGS at load centres supplying power to both a constant power (CP) and induction motor (IM) load. The DPGSs considered in the present study are microturbine and diesel turbine power generators (MTGS and DTGS), both interfaced with synchronous generators. The influence of an IM load supplied by the DPGS on small-signal stability is studied by a critical damping ratio analysis. On the other hand, time-domain indicators of the transient response following a short circuit are employed in the analysis. Further, a variance analysis test (VAT) is performed to determine the contribution of IM and CP loads on the system stability. The study revealed that large penetration levels of IM loads significantly affect the stability and depend on the kind of DPGS technology used. [ABSTRACT FROM AUTHOR]

Small‐signal stability is an important task and key research in electrical engineering for networks. This research article focuses on the implementation of a multi‐objective approach for choosing an optimal location for Phasor Measurement Units (PMUs) to quantify a power system's small‐signal stability by maximizing the signal‐to‐noise ratio (SNR) in the system. The novelty of this research lies in the implementation of Dingo Optimization (DOX) technique along with the Prony Analysis (PA) approach for the assessment of small‐signal stability in standard grid networks. The voltage angle, amplitude and the range of frequencies are measured by the optimal placement of PMUs, which primarily focus on the multi‐signal PA. To achieve the objective of this research, DOX integrated with the multi‐signal PA approach is used to determine the ideal position for PMU placement by considering maximum redundancy and optimizing the signal to noise ratio to a maximum level. The effectiveness of the DOX strategy is established with improved accuracy and fewer disturbances by optimizing the electromechanical oscillations of the system. The implementation of the DOX approach for attaining the best value of the maximized SNR is obtained by analyzing a wide set of conditions, perturbations, and additive noise, which provides an accurate assessment of damping ratio (DR) and frequency (f) of electromechanical oscillations. Numerical results obtained from the standard IEEE test systems (14, 39, 57, 118, and 300 bus systems) are compared with the existing methods in the literature. The statistical indices demonstrate that under the highly limited optimization context selected, the intended optimizer functions satisfactorily. [ABSTRACT FROM AUTHOR]

Modern electrical power systems place special demands on the speed and accuracy of transient and steady-state process control. The introduction of renewable energy sources has significantly influenced the amount of inertia and uncertainty of transient processes occurring in energy systems. These changes have led to the need to clarify the existing principles for the implementation of devices for protecting power systems from the loss of small-signal and transient stability. Traditional methods of developing these devices do not provide the required adaptability due to the need to specify a list of accidents to be considered. Therefore, there is a clear need to develop fundamentally new devices for the emergency control of power system modes based on adaptive algorithms. This work proposes to develop emergency control methods based on the use of deep machine learning algorithms and obtained data from synchronized vector measurement devices. This approach makes it possible to ensure adaptability and high performance when choosing control actions. Recurrent neural networks, long short-term memory networks, restricted Boltzmann machines, and self-organizing maps were selected as deep learning algorithms. Testing was performed by using IEEE14, IEEE24, and IEEE39 power system models. Two data samples were considered: with and without data from synchronized vector measurement devices. The highest accuracy of classification of the control actions' value corresponds to the long short-term memory networks algorithm: the value of the accuracy factor was 94.31% without taking into account the data from the synchronized vector measurement devices and 94.45% when considering this data. The obtained results confirm the possibility of using deep learning algorithms to build an adaptive emergency control system for power systems. [ABSTRACT FROM AUTHOR]

With global trends of carbon neutrality, offshore wind energy is considered as the most promising resource. However, as large-scale renewable energy resources replace the existing synchronous generators (SG), concerns about the system stability are growing. Owing to the absence of system supports provided by the SG. Therefore, operators require the wind generators to participate in frequency control. In addition, controls have been devised to perform frequency support even when large-scale offshore wind farm (OWF) linked to High Voltage Direct Current (HVDC). However, this frequency support control’s impacts on the overall system stability are not investigated in deeply yet. Therefore, in this study, the impacts of frequency control from OWF-linked HVDC system using communication-less scheme on the system instability were investigated using small-signal stability analysis. Its results revealed that this frequency support control caused instability. Modal analysis and simulations support these interpretations and improve the understanding its mechanism and dynamics.

The effective operation of model-based control strategies in modern energy systems, characterized by significant complexity, is contingent upon highly accurate large-scale models. However, achieving such precision becomes challenging in complex energy systems rife with uncertainties and disturbances. Controlling different parts of the energy system poses a challenge to achieving optimal power system efficiency, particularly when employing model-based control strategies, thereby adding complexity to current systems. This paper proposes a novel model-independent control approach aimed at augmenting transient stability and voltage regulation performance in multi machine energy systems. The approach involves the introduction of an optimized model-free fractional-order-based excitation system stabilizer for synchronous generators in a multi machine energy system. To overcome the limitations associated with complex system model identification, which add degrees of simplification at defined operating conditions and assume the system model remains fixed despite high uncertainty and numerous disturbances, an optimal model-independent fractional-order-based excitation control strategy is introduced. The efficacy of the proposed approach is validated through comparative numerical analyses using the MATLAB/Simulink environment. These simulations were conducted on a two-area, 12-bus multi-machine power system. Simulation results demonstrate that the presented excitation system stabilizer outperforms conventional controllers in terms of transient and small-signal stability. It also suppresses the low-frequency electromechanical oscillations within the multimachine energy system.

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.

Wide-Area Power System Stabilizers (WAPSSs) are damping controllers used in power systems that employ data from Phasor Measurement Units (PMUs). WAPSSs are capable of providing high damping rates for the low-frequency oscillation modes, especially the inter-area modes. Oscillation modes can destabilize power systems if they are not correctly identified and adequately damped. However, WAPSS communication channels may be subject to failures or cyber-attacks that affect their proper operation and may even cause system instability. This research proposes a method based on an optimization model for the design of a WAPSS robust to multiple permanent communication failures. The results of applications of the proposed method in the IEEE 68-bus system show the ability of the WAPSS design to be robust to a possible number of permanent communication failures. Above this value, the combinations of failures and processing time are high and they make it difficult to obtain high damping rates for the closed-loop control system. The application and comparison of different optimization techniques are valid and showed a superior performance of the Grey Wolf Optimizer in solving the optimization problem.

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

The operation of modern power systems must meet stability requirements to guarantee the supply of electrical energy. One of these requirements is to ensure that the low-frequency oscillation modes have high damping ratios to avoid angular instability and future power system blackouts. Advances in phasor measurement units (PMUs) have contributed to the development and improvement of wide-area damping controllers (WADCs) capable of increasing the damping rates of the oscillation modes of the system, especially the inter-area modes. Nevertheless, the operation of WADCs is vulnerable to communication failures and cyber-attacks, and if not properly designed the WADC can affect the stability of the entire system. This research proposes a procedure for designing a WADC robust to permanent communication failures using a linear quadratic regulator (LQR) and genetic algorithms. Case studies conducted on an IEEE 68-bus test power system show the effectiveness of the WADC designed by the proposed procedure even when communication failures are occurring in the system. The use of genetic algorithms improves the convergence and results of the LQR-based method. [ABSTRACT FROM AUTHOR]

Owing to their stability, doubly-fed induction generator (DFIG) integrated systems have gained considerable interest and are the most widely implemented type of wind turbines and due to the increasing escalation of the wind generation penetration rate in power systems. In this study, we investigate a DFIG integrated system comprising four modules: (1) a wind turbine that considers the maximum power point tracking and pitch-angle control, (2) induction generator, (3) rotor/grid-side converter with the corresponding control strategy, and (4) AC power grid. The detailed small-signal modeling of the entire system is performed by linearizing the dynamic characteristic equation at the steady-state value. Furthermore, a dichotomy method is proposed based on the maximum eigenvalue real part function to obtain the critical value of the parameters. Root-locus analysis is employed to analyze the impact of changes in the phase-locked loop, short-circuit ratio, and blade inertia on the system stability. Lastly, the accuracy of the small-signal model and the real and imaginary parts of the calculated dominant poles in the theoretical analysis are verified using PSCAD/EMTDC. [ABSTRACT FROM AUTHOR]

This paper investigates the dynamic patterns in the small-signal behavior of power systems with wind power generation. The interactions between synchronous generators and wind generators are investigated. In addition, the impact of increased wind generation penetration on the damping and frequency of the synchronous generator’s electromechanical oscillations is addressed. Wind generators of three different technologies are considered throughout this study. Very detailed dynamic models of wind generators are used and detailed.

This paper investigates the small-signal stability of a DC shipboard power system (SPS) with the integration of a supercapacitor. As an efficient energy storage solution, supercapacitors can not only provide rapid energy response to sudden power demand spikes, effectively mitigating load fluctuations, but also enhance the system’s resilience to disturbances. In the context of the parallel operation of two Permanent Magnet Synchronous Generators (PMSGs), the inclusion of supercapacitors may alter the system’s dynamic behaviors, thereby affecting its small-signal stability. This paper develops the small-signal model of SPS and explores the small-signal model under various power distribution strategies in the parallel operation of diesel generator sets. Through the calculation of eigenvalues and influence factors, the system’s oscillation modes are analyzed, and key parameters affecting the stability of the DC distribution system are identified. Furthermore, this paper meticulously examines the specific impacts of electrical and control parameter variations on the system’s small-signal stability. Simulation experiments validate the accuracy of the small-signal stability analysis after supercapacitor integration into SPS.

Challenges in the operation of power systems arise from several factors such as the interconnection of large power systems, integration of new energy sources and the increase in electrical energy demand. These challenges have required the development of fast and reliable tools for evaluating the operation of power systems. The load margin (LM) is an important index in evaluating the stability of power systems, but traditional methods for determining the LM consist of solving a set of differential-algebraic equations whose information may not always be available. Data-Driven techniques such as Artificial Neural Networks were developed to calculate and monitor LM, but may present unsatisfactory performance due to difficulty in generalization. Therefore, this article proposes a design method for Physics-Informed Neural Networks whose parameters will be tuned by bio-inspired algorithms in an optimization model. Physical knowledge regarding the operation of power systems is incorporated into the PINN training process. Case studies were carried out and discussed in the IEEE 68-bus system considering the N-1 criterion for disconnection of transmission lines. The PINN load margin results obtained by the proposed method showed lower error values for the Root Mean Square Error (RMSE), Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE) indices than the traditional training Levenberg-Marquard method.

In the modern power grid, characterized by the increased penetration of power electronics and extensive utilization of renewable energy, inverter-based power plants play a pivotal role as the principal interface of renewable energy sources (RESs) and the grid. Considering the stability characteristics of grid-following (GFL) inverters when the grid is relatively weak, the application of grid-forming (GFM) controls becomes imperative in enhancing the stability of the entire power plant. Thus, there is an urgent need for suitable and effective models to study the interaction and stability of the paralleled inverters employing GFL and GFM controls. Thus, the small-signal modeling with full-order state-space model and eigenvalues analysis are presented in this paper. First, the small-signal state-space model of the individual GFL and GFM inverters is obtained, considering the control loop, interaction, reference frame, transmissions, and time delays. Then, the models of the individual inverter are extended to the hybrid inverters to study the effects of the GFM inverters on the small-signal stability of the entire system. And the impacts of the inertia and damping are analyzed by the eigenvalues of the state-transition matrix. A case comprising three parallel GFL inverters and two GFL inverters with one GFM inverter, respectively, are studied to examine the effectiveness and accuracy of the model. Finally, the stability margin obtained from the eigenvalue analysis of the entire system is verified by time-domain simulations.

The operation of power systems requires a set of requirements and studies to ensure the continuous and safe supply of electricity to consumer centers. In small-signal stability studies, low-frequency oscillation modes need to be evaluated as they can compromise the operation of power systems if they are not properly damped. Many structures and control devices have been proposed to mitigate these oscillation modes and the Wide-Area Power System Stabilizers (WAPSSs) have proven to be effective in improving the damping rates of these modes as they use remote system signals from Phasor Measurement Units (PMUs). However, cyber-attacks and communication failures can affect WAPSS communication channels and affect its operation in the power system. This article proposes a method based on a multiobjective optimization model for WAPSS design that is robust to the permanent loss of one WAPSS communication channel. Bio-Inspired Algorithms are applied and compared to solve the optimization problem. A set of case studies were conducted and discussed for the IEEE 68-bus system through modal analysis and time domain simulations. The achieved results showed the need for a fault-robust damping controller and the WAPSS-type controller was able to guarantee good dynamic performance regardless of permanent communication failures. Furthermore, different bio-inspired algorithms provided different results for the closed-loop control system when applied to the proposed optimization model.

Low-frequency oscillations (LFO) are a significant problem for multi-machine electrical power system (EPS). These oscillations are undesirable as they reduce the power transfer capability of the transmission line and thus directly influence competitive electrical markets. The power system stabilizers (PSS) play a vital role in damping low-frequency oscillations to improve the dynamic stability of the power system. However, these controllers must be tuned in a coordinated and robust manner for effective performance. PSS tuning is characterized by a complex optimization problem that may involve hundreds of variables. The tuning procedure is modeled as an optimization problem which aims at maximizing the damping ratio coefficients of the closed-loop power system considering multiple operating points. In this context, this article employs and compares three metaheuristics with quantum characteristics, namely quantum particle swarm optimization (QPSO), quantum flower pollination algorithm (QFPA) and quantum gray wolf optimizer (QGWO). The aforementioned metaheuristics are used in PSS tuning in four test systems with 5 generators–7 buses, 10 generators–39 buses, 50 generators–616 buses and 170 generators–3584 buses. The results obtained by the quantum algorithms are compared through statistical indices and boxplot. The optimization results show that the QFPA and QGWO provide better system damping than the QPSO for the large electrical system. [ABSTRACT FROM AUTHOR]

Owing to the rapid incorporation of doubly fed induction generator (DFIG)-based wind farms into the power system, the sustainability of the power system has been a major concern of system planners, operators, engineers, etc. This has necessitated a proper investigation to be implemented in the stability of the power system. The small-signal stability analysis can be used to predict the dynamic behaviour of the power system and the sustainability of energy with the application of DFIGs. The state-of-the-art of DFIG, its impacts on small signal stability and the potential effects are proposed in this paper. The control techniques on DFIG to enhance damping qualities of the power system are also presented. This paper reviews the small-signal stability analysis of wind power system integrated with DFIG-based wind farms. The developments that have been made till-date towards attaining models of DFIG-based wind farms will give a definitive conclusion about small-signal stability. The prediction methods and impacts of integrating DFIG-based wind power into the power system are reported together with their limiting factors. Lastly, the techniques that have been presented in the paper will improve the small-signal stability and guarantee the future sustainability of power supply. [ABSTRACT FROM AUTHOR]

Wide-Area Power System Stabilizers (WAPSSs) are damping controllers used in power systems that employ data from Phasor Measurement Units (PMUs). WAPSSs are capable of providing high damping rates for the low-frequency oscillation modes, especially the inter-area modes. Oscillation modes can destabilize power systems if they are not correctly identified and adequately damped. However, WAPSS communication channels may be subject to failures or cyber-attacks that affect their proper operation and may even cause system instability. This research proposes a method based on an optimization model for the design of a WAPSS robust to multiple permanent communication failures. The results of applications of the proposed method in the IEEE 68-bus system show the ability of the WAPSS design to be robust to a possible number of permanent communication failures. Above this value, the combinations of failures and processing time are high and they make it difficult to obtain high damping rates for the closed-loop control system. The application and comparison of different optimization techniques are valid and showed a superior performance of the Grey Wolf Optimizer in solving the optimization problem. [ABSTRACT FROM AUTHOR]

A robust, optimized power system stabilizer (PSS) is crucial for oscillation damping, and thus improving electrical network stability. Additionally, real-time testing methods are required to significantly reduce the likelihood of software failure in a real-world setting at the user location. This paper presents an Antlion-based proportional integral derivative (PID) PSS to improve power system stability during real-time constraints. The Antlion optimization (ALO) is developed with real-time testing methodology, using hardware-in-the-loop (HIL) that can communicate multiple digital control schemes with real-time signals. The dynamic power system model runs on the dSPACE DS1104, and the proposed PSS runs on the field programmable gate arrays (FPGA) (NI SbRIO-9636 board). The optimized PSS performance was compared with a modified particle swarm optimization (MPSO)-based PID-PSS, through different performance indices. The test cases include other step load perturbations and several short circuit faults at various locations. Twelve different test cases have been applied, through real-time constraints, to prove the robustness of the proposed PSS. These include 5 and 10% step changes through 3 different operating conditions and single, double, and triple lines to ground short circuits through 3 different operating conditions, and at various locations of the system transmission lines. The analysis demonstrates the effectiveness of ALO and MPSO in regaining the system's stability under the three loading conditions. The integral square of the error (ISE), integral absolute of the error (IAE), integral time square of the error (ITSE), and integral time absolute of the error (ITAE) are used as performance indices in the analysis stage. The simulation results demonstrate the effectiveness of the proposed PSS, based on the ALO algorithm. It provides a robust performance, compared to the traditional PSS. Regarding the applied indices, the proposed PSS, based on the ALO algorithm, obtains significant improvement percentages in ISE, IAE, ITSE, and ITAE with 30.919%, 23.295%, 51.073%, and 53.624%, respectively. [ABSTRACT FROM AUTHOR]

Virtual synchronous generator (VSG) control is based on the fact that the line impedance in a microgrid is highly inductive. This assumption was made due to the emulation of the stator winding of an electrical machine. This concept can affect the controllability of a microgrid with complex line impedance, generating deviations in the chosen operation point. To overcome this issue, additional techniques must be implemented. This paper describes a novel mathematical approach that uses the power line characteristics in a microgrid to rotate the power control reference frame and proposes a new control method called a "Rotated Virtual Synchronous Generator" (RVSG). This RVSG control approach integrates the effect of complex impedance on the microgrid's operation and adjusts the reference frame accordingly to improve the system's stability and performance. The use of this proposed mathematical approach in microgrids allows the further emulation of virtual inertia in microgrids that lack inertia. Finally, a comparison between RVSG control and the classical virtual synchronous generator method is carried out to show that it allows the improvement of the transient power response, power quality, stability, and performance, mainly in microgrids with complex line impedance. [ABSTRACT FROM AUTHOR]

This paper investigates the dynamic interactions between large‐scale PV plants and nearby synchronous generators. To this end, a comprehensive model of a PV plant, including the PV arrays characteristic and their voltage controller, DC/DC converter, DC‐link dynamic, DC/AC inverter controllers, and output filter, is obtained. Then, the eigenvalues of the PV plant model are calculated, and it is revealed that the PV plant has a dynamic mode in the sub‐synchronous oscillations (SSOs) range. Furthermore, the modal analysis method is employed, and it is shown that the inductance of the DC/DC converter and the DC‐link capacitor significantly contribute to the PV sub‐synchronous mode. Also, it is shown that this mode oscillations penetrate the grid and increase the risk of sub‐synchronous resonance (SSR). Then, the mechanism of dynamic interactions between large‐scale PV plants and torsional modes of nearby synchronous generators is revealed. This paper also investigates the required conditions for these interactions and shows that solar irradiation level and the DC‐link capacitance are the essential factors that can intensify these interactions. [ABSTRACT FROM AUTHOR]

The energy mix of future power systems will include high shares of electricity generation by wind turbines and solar photovoltaics. These generation facilities are generally connected via power-electronic inverters. While conventional generation responds dynamically to the state of the electric power system, inverters are power-electronic hardware and need to be programmed to react to the state of the system. Choosing an appropriate control scheme and the corresponding parameters is necessary to guarantee that the system operates safely. A prominent control scheme for inverters is droop control, which mimics the response of conventional generation. In this work, we investigate the stability of coupled systems of droop-controlled inverters in arbitrary network topologies. Employing linear stability analysis, we derive effective local stability criteria that consider both the overall network topology as well as its interplay with the inverters’ intrinsic parameters. First, we explore the stability of an inverter coupled to an infinite grid and uncover stability and instability regions. Second, we extend the analysis to a generic topology of inverters and provide mathematical criteria for the stability and instability of the system. Last, we showcase the usefulness of the criteria by examining two model systems using numerical simulations. The developed criteria show which parameters might lead to an unstable operating state.