Power System Small Signal Stability Research Articles

Research on power system small signal stability analysis and correction based on LightGBM algorithm

Research on power system small signal stability analysis and correction based on LightGBM algorithm

Probabilistic Analysis of Small-Signal Stability of Power Systems Affected by Wind Power Generation Uncertainties Considering Wake Effects

Probabilistic Analysis of Small-Signal Stability of Power Systems Affected by Wind Power Generation Uncertainties Considering Wake Effects

Using demand response to improve power system small-signal stability

With the increase of uncertain and intermittent renewable energy supply on the grid, the power system has become more vulnerable to instability. In this paper, we develop a demand response strategy to improve power system small-signal stability. We pose the problem as an optimization problem wherein the total demand-responsive load is held constant at each time instance but shifted between different buses to improve small-signal stability, which is measured by small-signal stability metrics that are functions of subsets of the system’s eigenvalues, such as the smallest damping ratio. To solve the problem, we use iterative linear programming and generalized eigenvalue sensitivities. We demonstrate the approach via a case study that uses the IEEE 14-bus system. Our results show that shifting the load between buses, can improve a small-signal stability margin. We explore the use of models of different fidelity and find that it is important to include models of the automatic voltage regulators and power system stabilizers. In addition, we show that load shifting can achieve similar improvements to generation shifting and better improvement than simply tuning power system stabilizers.

Admittance Criterion of Medium-Voltage DC Distribution Power System and Corresponding Small Signal Stability Analysis

Aiming at the stability of a medium-voltage DC network based on a modular multilevel converter (MMC), this paper proposes an admittance stability criterion considering the influence of current-limiting inductors at the medium voltage side, which prevents the complex products and matrix calculations of traditional criteria. The DC admittance model DC transformers (DCTs) under different working modes are then established based on Thevenin/Norton equivalent circuit methods to analyze the stability of the DC system based on the proposed admittance stability criterion, which proves that the voltage resonance problem at the medium voltage side can be improved by adding active damping control strategies on DCTs also proves the effectiveness of the proposed stability criterion. The time-domain simulation and the hardware-in-loop simulation are then built in PLECS and RT Box to further verify the correctness of the system stability analysis and the effectiveness of the proposed admittance criterion, which provides a theoretical basis and technical reserve for the stable operation of the DC distribution power system.

Power System Small Signal Stability Enhancement Using Fuzzy Based STATCOM

Power System Small Signal Stability Enhancement Using Fuzzy Based STATCOM

Passivity-Based Decentralized Criteria for Small-Signal Stability of Power Systems With Converter-Interfaced Generation

With the increasing penetration of converter-interfaced generation, it would be advantageous to specify local grid-connectivity criteria to ensure small-signal stability of the interconnected system, rather than carrying out centralized stability studies every time the connection of a new device is contemplated. Passivity of the device admittance, which is an example of a local criterion, has been used previously to avoid resonances between converter-interfaced systems and the lightly damped oscillatory modes of the network, but it is unsuitable in general due to the conservative nature of passivity. Therefore, a composite set of criteria are proposed in this paper, which include time-scale separation (slow-fast clustering) constraints on the transient behaviour, and distinct passivity constraints for the slow and fast clusters. The application of these criteria is demonstrated using a case study.

A Sequential Generation Redispatch Algorithm to Ensure Power System Small Signal Stability under Low-Frequency Oscillations

Generation rescheduling is a major action against abnormal system conditions such as small signal instability. The operating point of the power system impacts the small signal stability; therefore, this article proposes a novel sequential generation rescheduling model as a preventive control against low-frequency fluctuations. An optimal power flow (OPF) problem is utilized to determine the base operating point. Then, in the process of improving the small signal stability, the modal analysis specifies the system stability status in each step, and the proposed second-order convex redispatch model defines the optimal direction of generation rescheduling. Small signal stability is considered a constraint in this model. Using a sensitivity analysis, system generators and system buses are divided into two increasing and decreasing groups, which are included in the model according to their contribution coefficients in damping improvement. Finally, the alternating current (AC) power flow analysis provides the subsequent operating points. The redispatch model is solved using the quadratic programming algorithm, and the Newton algorithm is used to manage the nonlinear and nonconvex characteristics of the power flow model. The proposed method is simulated over the IEEE 9, 39, and 118 bus test systems. It is shown that the proposed method increases the damping of the power system from the unstable state to the desired condition by controlling the operating point.

Sensitivity analysis of power system small signal stability to geomagnetic disturbances

Geomagnetically induced currents driven by geomagnetic disturbances can cause half-cycle saturation of transformers and consequently affect the power grid with reactive losses. The impact of geomagnetic disturbances focuses on voltage stability, and the research object is the conventional system without considering wind power. In this paper, we study the impact of geomagnetic disturbances on the small signal stability of doubly-fed induction generators integrated systems. After the reactive power loss caused by geomagnetic disturbances and wind power output are equivalent to grounding admittances, the influence of geomagnetic disturbances on small signal stability can be transformed into its impact on the equivalent electrical distance between synchronous generators by shrinking the admittance matrix. Then, the electromagnetic power of synchronous generators is affected, and the impact of wind farm ratio and geomagnetic disturbances is incorporated into the system state equation. The results show that the oscillation frequency and damping ratio increase first and then decrease with the increase of wind power ratio when geomagnetic disturbances occur, but they are generally smaller than those without geomagnetic disturbances. The sensitivity of inter-area oscillation mode to induced geoelectric fields is higher than that of intra-area oscillation modes, and the sensitivity to reactive power losses caused by geomagnetic disturbances in substations is different, which provides a reference for further research on optimizing blocking devices placement to mitigate the impact of geomagnetic disturbances on small signal stability.

The Impact of Frequency Support by Wind Turbines on the Small-Signal Stability of Power Systems

Rising wind energy integration, accompanied by a decreasing level of system inertia, requires additional sources of ancillary services. Wind turbines based on doubly fed induction generators (DFIGs) can provide inertial and primary frequency support when equipped with specific controls. This paper investigates the effect of frequency support provision by DFIGs on the small-signal stability of power systems. To this end, a modified version of the Kundur two-area test system is employed to analyze different scenarios. Wind energy generation is either added to the existing system or displaces part of the synchronous generation. Simulations show that primary frequency support tends to improve the damping of electromechanical oscillations and deteriorate it for converter control-based ones. On the other hand, the inertial response depends on the control parameters.

Small-Signal Stability Improvement of Grid Integrated DFIG and SOFC System with SSSC-POD Using Coordinated Optimization Approach

Background: Focusing on the stability problems brought by integrated wind power and fuel cell, the objective of this paper is to analyze small-signal stability and improvement of a hybrid renewable energy system connected with doubly-fed induction generators (DFIGs) and solid oxide fuel cells (SOFCs) energy with the static series synchronous compensator (SSSC) and power-oscillation damper (POD). Methods: For this purpose, a SSSC-POD controller is designed and the state-space representation of such a hybrid power system for modal analysis is developed. Then an approach of coordination and optimization of SSSC-POD parameters based on genetic algorithm (GA) and modal analysis is proposed to further improve the power system small-signal stability. Results: Several designed scenarios, including changing the tie-line power, POD input signal and SOFC power output, are considered in IEEE two-area system to test the proposed method through small-disturbance eigenvalue analysis and time-domain simulations. Conclusion: Simulation results demonstrate that the proposed approach can effectively suppress the local and inter-area oscillations and improve power system stability.

Small-signal stability analysis of uncertain power systems via interval analysis

This paper proposes an interval analysis based framework to assess the small-signal stability of power systems in the presence of uncertainty sources. As opposed to stochastic small-signal stability analysis, this framework does not imply either an accurate characterization of probability distributions or significant computational burden.Interval analysis returns robust enclosures of the eigenvalues characterizing the system, which are guaranteed to include all possible scenarios generated by uncertain variables. This is achieved by solving an interval eigenvalue problem, which requires low computational capabilities.The single machine infinite bus and the IEEE 39-bus test systems are employed to validate the effectiveness of the proposed framework in calculating interval eigenvalues in uncertain small-signal stability analysis. In order to show its improved performances, both in terms of robustness and computing speed, the results are compared to Monte Carlo simulations.

A method for monitoring the load margin of power systems under load growth variations

The load margin is an important safety measure used in operation centers to assess the voltage stability of power systems. Usually this measure is calculated considering a single load growth direction and voltage stability requirements. However, oscillation modes with low damping rates can compromise the small-signal stability of power systems and different load growth directions can also affect load margin estimates. Thus, these two factors must be considered to provide adequate load margin for power system operation. This paper proposes a load margin monitoring scheme based on Artificial Neural Networks (ANN) considering voltage stability requirements and small-signal stability and load growth variations. Thus, the power system operator will have real-time load margin information considering voltage stability requirements and small-signal stability requirements. ANN uses as input data the voltage magnitude and voltage angle measurements provided by Phasor Measurement Units (PMUs) installed in system buses. A method to select a reduced set of buses for the monitoring system is proposed and evaluated. Case studies are presented and the results achieved provide indications of the applicability of the proposed scheme in the real-time operation of power systems.

Data-driven power system small-signal stability assessment and correction control model based on XGBoost

The influence of small-signal stability on the safety and stability of the power system is becoming more prominent. A mapping model based on steady-state operation information is established using the sample learning method, which provides a new technical path for the rapid assessment and correction of significant power grid oscillation characteristics. This paper establishes a small signal stability assessment and correction control model based on the Extreme Gradient Boosting (XGBoost) algorithm. Firstly, the XGBoost model is obtained by analyzing the mapping relationship between generator power, node power, branch power, and minimum damping ratio. Then, the sensitivity of the generator damping ratio is calculated, and the objective is to minimize the active power adjustment amount of the generator. The stability constraint and power balance are the constraint conditions to establish the optimization correction model, obtain the optimal adjustment amount, correct the minimum damping ratio, and improve the system’s stability. Finally, the minimum damping ratio after correction is obtained, and the modified damping ratio is estimated by XGBoost algorithm. The performance of the proposed model is verified in IEEE 3-machine 9-node and 10-machine 39-node systems.

Some Notes on Two Tests for Stability in Lossy Power Systems

Analysis of the small-signal stability of power system is commonly based on the swing equation model. Due to the special structure of the power grid swing equations, an equilibrium set corresponding to a so-called frequency equilibrium has to be analyzed. We present two new and short proofs for two tests by Skar concerning both the nonuniformly and the uniformly damped system. Based on the latter we derive a simple stability test for uniformly damped systems, which does not rely on eigenvalue computations. The nonhyperbolicity of the equilibria in original coordinates is tackled by the concept of normally hyperbolic invariant manifolds. The derivations are completely based on the theory of quadratic pencils.

Impact of Frequency Support by Wind Turbines on Small-Signal Stability of Power Systems

Impact of Frequency Support by Wind Turbines on Small-Signal Stability of Power Systems

Using Demand Response to Improve Power System Small-Signal Stability

Using Demand Response to Improve Power System Small-Signal Stability

Probabilistic analysis of small-signal stability in power systems based on direct polynomial approximation

Along with expanding power systems, stochastic factors affecting the performance of these systems have increased. Uncertainties due to successive changes in the load power are one of the mentioned factors. These random changes have made the methods of uncertainty analysis particularly important in the analysis of power systems stability. This paper propose a probabilistic small-signal stability analysis method based on polynomial approximation of eigenvalues. Since the correct determination of unknown coefficients has a direct effect on the accuracy of the polynomial approximation method, this paper presents a method that can determine the mentioned coefficients, with more coverage on the probabilistic input domain of the problem. With increasing the number of random input variables, the proposed method can continue to maintain its efficiency. After determining the unknown coefficients, the load flow results and the system state matrix are determined for random changes of all loads based on the Hermite polynomial approximation. Then, the small-signal stability of the system is probabilistically evaluated based on a stochastic analysis of eigenvalues in the system. The consistency and validity of the proposed method are demonstrated based on the simulation studies in the MATLAB® software environment. In the simulation studies, the performance of the proposed method is examined by comparison with the Monte Carlo and Point Estimation methods, for the 14-bus IEEE test system.

Power System Small-signal Stability Assessment Model Based on Residual Graph Convolutional Networks

Small-signal stability (SSA) is important to power system security. A data-driven approach is established for rapid prediction of the power system oscillation characteristics. The key of the approach is the Graph Convolution Networks (GCN) with residual mechanism, which works to aggregate features from high-dimension steady-state operation information and is denoted as ResGCN (RESidual GCN) in the paper. The residual mechanism helps to overcome the network degradation phenomenon. Both the oscillation frequency and damping ratio of multiple modes can be predicted by the proposed model. The performance of the proposed scheme as well as its adaptability to the power system topological changes is verified on the IEEE 39 Bus system.

Lyapunov modal analysis and participation factors applied to small-signal stability of power systems

In large dynamical systems subjected to noise or forced oscillations, disturbances constantly arise over time. In this case, the small-signal stability is determined by the energy of perturbations accumulated in the system. To analyze this perturbation energy, this study proposes a novel physically motivated Lyapunov modal analysis (LMA) framework that combines selective modal analysis with the spectral decompositions of specially chosen Lyapunov functions. Based on this approach, we propose new modal indicators that characterize individual modes and modal interactions in connection with specific state variables. Conventional participation factors characterize the relative contributions of the system modes to the evolution of states. In contrast, the proposed Lyapunov participation factors make similar contributions to the Lyapunov functions that estimate the integral energy associated with the states and signals on an infinite or finite time interval. The Lyapunov modal interaction factors characterize the pairwise interaction between modes in terms of their mutual actions produced in states over time. We prove that the proposed modal indicators characterize the stability of individual modes and resonant modal interactions in linear parameter-varying systems and demonstrate the application of these indicators for the small-signal stability analysis of a two-area power system model. New indicators can be calculated independently for a selected part of the system spectrum and used to quickly assess the behavior of critical modes in large-scale dynamical systems.

Probabilistic Analysis of Small Signal Stability of Power System with Penetration of Distributed Generation: A Review

The liberalization of electricity markets, continuous increase in power demand, shortage in conventional generating and transmission capacities and the environmental awareness of consumers contribute to the wide application of Distributed Generation (DG) into power systems. The presence of DG presents system operators with new challenges regarding DG availability, integration and impact on system security and stability. Therefore, analysis of renewable energy penetrated power system using probabilistic approaches is of utmost importance in other to ascertain the impact of intermittency of the renewable generation on the power network. This work firstly reviews the problem of instability of power systems with a considerable share of renewable generation and its significant demand for probabilistic analysis, then, provides a critical evaluation of the available probabilistic methods that have been used for the assessment of power system small signal stability. Overview of frequently used methods are presented stressing their advantages and disadvantages with the aim of highlighting their strength and weaknesses. This paper, then proposes a method known as Stochastic Collocation Method that promises to be an effective probabilistic tool for the analysis of renewable energy penetrated power system.