Power System Dynamic Stability Research Articles

Multimodal Unified Control Method Using the Lie Derivative and Lyapunov Theory for Enhancing the Dynamic Stability of Power Systems With 100% Renewable Energy

Multimodal Unified Control Method Using the Lie Derivative and Lyapunov Theory for Enhancing the Dynamic Stability of Power Systems With 100% Renewable Energy

Performance Evaluation of Optimally Placed SVC for Dynamic Stability of the Power System

Given the complexity of power systems, particularly in the deregulated power industry found in Nigeria, a consistent, safe, controllable, and high-quality power supply is required. The loss of the system's overall damping torque, which reduces the system's susceptibility to fluctuations and problems with dynamic stability, is one of the key downsides of network expansion. Flexible AC transmission systems (FACTS) controllers have been used to overcome problems with power system stability control. In order to improve dynamic stability, this study investigates how the generator's rotor angle, speed, voltage magnitude profile, and real power affect how well SVC operates under the effect of a three-phase fault. With a fault introduced on Bus 33 (Geregu Substation) and SVC placed optimally on Bus 21 (Jos Transmission Station) using voltage stability sensitivity factor (VSSF) after the simulation of continuation power flow (CPF), the 48-bus power system network in Nigeria was modeled using commercial PSAT software in a MATLAB environment. The power system's oscillation was significantly reduced, and the voltage profile was enhanced for power system dynamic stability, per simulation results with and without SVC.

A unified power flow controller-based robust damping controller considering time delay in electrical power systems

Nowadays, different power systems are connected to each other due to technical and economic reasons and form a complex developed network. Such networks measure and send system data to decision-making centers for control and protection. This information transmission is accompanied by a delay and causes the performance of the system’s damping controllers to be affected. To improve power system dynamic stability, the supplementary controller in flexible alternating current transmission system (FACTS) devices is designed to account for information transmission delays. In these methods, to increase the controllability and observability of the inter-area mode, the remote signals extracted from the wide area measurement system (WAMS) are used as the input of the modulator. WAMS systems’ time delay reduces power system stability and even causes instability, so it’s crucial to find the maximum delay margin that ensures stability. Therefore, it is necessary to carefully study the role of FACTS tools in stabilizing the power system and damping interregional fluctuations, considering the delay. This research shows that supplementary controller design can dampen frequency and load angle fluctuations in multi-zone power systems despite information transmission delays. The method works in power system analysis toolbox (PSAT) simulation and MATLAB programming.

Mitigating Low-Frequency Oscillations and Enhancing the Dynamic Stability of Power System Using Optimal Coordination of Power System Stabilizer and Unified Power Flow Controller

The integration of a flexible alternating current transmission system (FACTS) and a power system stabilizer (PSS) can increase dynamic stability. This paper presents the enhancement of power system dynamic stability through the optimal design of a power system stabilizer and UPFC using an ant lion optimization (ALO) technique to enhance transmission line capacity. The gained damping ratio, eigenvalue and time domain results of the suggested ALO technique were compared with a base case system, ALO-based PSS and ALO-based PSS-UPFC to test the effectiveness of the proposed system in different loading cases. Eigenvalues gained from an ant lion approach-based UPFC with a PSS and a base case system are compared to examine the robustness of the ALO method for various loading conditions. Thus, this paper addresses the mechanism regarding the power system dynamic stability of transmission lines by integrating the optimal size of a PSS and UPFC into the power system. Therefore, the main contribution of this manuscript is the optimal coordination of a power system stabilizer, power oscillation damper and unified power flow using ant lion optimization for the mitigation of low-frequency oscillation.

New Energy Power System Dynamic Security and Stability Region Calculation Based on AVURPSO-RLS Hybrid Algorithm

Using a high proportion of new energy is becoming the development trend of the modern power industry, with broad application prospects and potential threats to power system operation safety. This paper proposes a hybrid adaptive velocity update relaxation particle swarm optimization algorithm (AVURPSO) and recursive least square (RLS) method to quickly estimate the DSSR boundary using hyper-plane expression. Firstly, the operating point data in the high-dimension nodal injection space are analyzed using the AVURPSO algorithm to identify the key generators, equivalent search space, and critical points, which have relatively great effects on transient angle stability. The hyper-plane expression of the DSSR boundary, which matches the critical points best, is finally fitted by the RLS approach. Hence, the adopted algorithm is applied to rapidly approximate the DSSR boundary by hyper-plane expression in power injection spaces. Finally, the proposed algorithm is validated using a simulation case study on three wind farm regions of the actual Hami Power Grid of China using the DIgSILENT/Power Factory software. Consequently, the mentioned method effectively captures the security stability boundary of the new energy power system and realizes the three-dimensional visualization space of DSSR. By leveraging the DSSR, the state analysis can be conducted rapidly on several parameters, including security and stability assessments in relation to various energy supply capabilities. Meanwhile, these indices are calculated offline and applied online. The findings of this investigation confirm the efficacy and accuracy of the suggested modeling used in the analyzed system, offering technical assistance ensuring the stability of the new energy power system. The DSSR allows the rapid analysis of several parameters, including security and stability assessments with various energy supply capabilities.

Разработка метода оценки динамической устойчивости энергосистем на основе применения теории искусственного интеллекта с учётом топологической связанности сети

Разработка метода оценки динамической устойчивости энергосистем на основе применения теории искусственного интеллекта с учётом топологической связанности сети

A Novel Control to Improve Dynamic Stability of Power Systems Including DFIG and SSSC

A Novel Control to Improve Dynamic Stability of Power Systems Including DFIG and SSSC

Stochastic Power System Dynamic Simulation and Stability Assessment Considering Dynamics From Correlated Loads and PVs

The integration of uncertain photovoltaics (PVs) and flexible loads leads to uncertainties in the power system dynamic simulation results. Furthermore, geographically close PV farms are correlated and may exhibit nonlinear correlations. This article proposes a copula-based sparse polynomial chaos expansion (PCE) framework for quantifying the impacts of uncertain dynamic PVs and loads on power system dynamic simulations and stability. The dynamics include both PV and load stochasticity and those governed by differential and algebraic equations. The copula statistics are utilized to accurately characterize the dependence structure of PVs and further used to develop the copula-PCE for quantifying the impacts of uncertain PVs and loads. A probabilistic TSI is also developed to assess the uncertainties from PVs and loads on the system stability. To address the cases, where both stable and unstable conditions coexist, a preprocessing step via sample classification is proposed. The effects of different dependence structures of PVs and different numbers of uncertain sources are investigated. Comparison results with other methods on the modified IEEE 39- and 118-bus systems, including the Monte Carlo method, Latin hypercube sampling, and traditional PCE without consideration of uncertain input correlations show that the proposed method is able to accurately quantify the uncertain dynamic simulations and transient system stability while being computationally efficient.

Application of Improved Quasi-Affine Transformation Evolutionary Algorithm in Power System Stabilizer Optimization

This paper proposes a parameter coordination optimization design of a power system stabilizer (PSS) based on an improved quasi-affine transformation evolutionary (QUATRE) algorithm to suppress low-frequency oscillation and improve the dynamic stability of power systems. To begin, the simulated annealing (SA) algorithm randomly updates the globally optimal solution of each QUATRE iteration and matches the inferior solution with a certain probability to escape the local extreme point. This new algorithm is first applied to the power system. Since the damping ratio is one of the criteria with which to measure the dynamic stability of the power system, this paper sets the objective function according to the principle of maximization of the damping coefficient of the electromechanical mode, and uses SA-QUATRE to search a group of global optimal PSS parameter combinations to improve the safety factor of the system as much as possible. Finally, the method’s rationality and validity were validated by applying it to the simulation examples of the IEEE 4-machine 2-area system with different operation states. The comparison with the traditional optimization algorithm shows that the proposed method has more advantages for multi-machine PSS parameter coordination optimization, can restrain the low-frequency oscillation of the power system more effectively and can enhance the system’s stability.

Data/Model Jointly Driven High-Quality Case Generation for Power System Dynamic Stability Assessment

For data-driven dynamic stability assessment (DSA) in power systems, learning cases collected from actual historical records appear to be more reliable than those obtained from numerical simulations with an inevitable reality gap. However, due to the scarceness of transient events in practical systems, historical case sets generally encounter the small sample size and class-imbalance problems. To tackle these challenging issues, this article proposes a novel data/model jointly driven framework to generate high-quality cases for power system DSA applications. Model-driven numerical simulations are first utilized for rough case generation, based upon which case refinement is then intelligently carried out via cycle generative adversarial network (CycleGAN) learning. In this data-driven manner, the CycleGAN is able to produce refined cases highly resembling actual historical ones. A long short-term memory-based semisupervised learning scheme is further designed to reliably label all the refined cases. Numerical tests are comprehensively carried out on the realistic Guangdong Power Grid in South China. With only a small and skewed historical case set initially provided, the proposed framework is able to generate highly realistic cases to augment the set and mitigate the class-imbalance issue. These synthetic cases further help derive a more discerning DSA model, which contributes to enhanced reliability and adaptability of online DSA in practical power grids.

Forced Oscillation Grid Vulnerability Analysis and Mitigation Using Inverter-Based Resources: Texas Grid Case Study

Forced oscillation events have become a challenging problem with the increasing penetration of renewable and other inverter-based resources (IBRs), especially when the forced oscillation frequency coincides with the dominant natural oscillation frequency. A severe forced oscillation event can deteriorate power system dynamic stability, damage equipment, and limit power transfer capability. This paper proposes a two-dimension scanning forced oscillation grid vulnerability analysis method to identify areas/zones in the system that are critical to forced oscillation. These critical areas/zones can be further considered as effective actuator locations for the deployment of forced oscillation damping controllers. Additionally, active power modulation control through IBRs is also proposed to reduce the forced oscillation impact on the entire grid. The proposed methods are demonstrated through a case study on a synthetic Texas power system model. The simulation results demonstrate that the critical areas/zones of forced oscillation are related to the areas that highly participate in the natural oscillations and the proposed oscillation damping controller through IBRs can effectively reduce the forced oscillation impact in the entire system.

A new approach to parameter identification of generation unit equipped with brushless exciter using estimated field voltage

Parameter estimation of power plants is one of the main challenges of power system studies. Among different components of a power plant, excitation system (EXS) has great importance because of its effect on dynamic stability of power systems. Thus, it is vital to have accurate models of EXSs for power system dynamic studies. Since the field voltage and current are not accessible in brushless EXSs, parameter estimation of them is more difficult and challenging. Therefore, a new method is proposed in this paper to estimate field voltage signal using other measurements of the synchronous generator (SG). The proposed method is carried out through three stages; 1) parameter estimation of the SG using load rejection tests, 2) field voltage estimation, and 3) parameter estimation of EXS. The proposed method is applied to a 147 MVA industrial gas unit. The estimated model outputs are compared to the experimental results to show the accuracy and effectiveness of the proposed method.

Robust Power Designing of Supplementary Damping Controller in VSC HVDC System to Improve Energy Conversion Efficiency of Wind Turbine and Power System Stability

Because of low losses and voltage drop, fast control of power, limitless connection distance, and isolation issues, using high-voltage direct-current (HVDC) transmission system is recommended to transfer power in the power systems, including wind farms. This paper aims to propose a supplementary damping controller (SDC) based on the HVDC to improve not only power system dynamic stability but also energy conversion efficiency and torsional vibration damping in the wind power plants (WPPs). When the WPPs are working in power control mode, the active power is set to its reference value, which is extracted from power-speed curve. This paper shows that torsional oscillations associated with the poorly torsional modes can be affected by different operating regions of the power-speed curve of WPP. Therefore, it is essential to employ an SDC to have the optimum energy conversion efficiency in the wind turbine and the most dynamic stability margin in the power system. The SDC is designed using a fractional-order PID controller (FOPID) based on the multiobjective bat-genetic algorithm (MOBGA). The simulation results show that the proposed control strategy effectively works in minimizing the torsional and electromechanical oscillations in power system and optimizing the energy conversion efficiency in the wind turbine.

PMU-Based Power System Stabilizer Design: Optimal Signal Selection and Controller Design

Phasor measurement unit (PMU) provides beneficial information for dynamic power system stability, analysis, and control. One main application of such useful information is data-driven analysis and control. This article presents an approach for optimal signal selection and controller structure determination in PMU-based power system stabilizer (PSS) design. An algorithm is suggested for selecting the optimal input and output signals for PSS, in which a combination of system clustering, modal analysis, and principal component analysis techniques is used. The solution for the optimal PSS input–output selection is determined to increase the observability and damping of the power system. The approach can efficiently reduce the number of input–output signals, while the overall performance is not deteriorated. Then, a linear matrix inequality-based technique is elaborated to design the PMU-based PSS parameters. The stabilizer design approach is formulated as a convex optimization problem and the appropriate stabilizer for pole allocation of the closed-loop model is designed. This method is simulated on two sample power systems. Also, to compare the results with the previous methods, the system is simulated and the results of two previously developed algorithms are compared with the proposed approach. The results show the benefit of the suggested method in reducing the required signals, which decreases the number of required PMUs, while the system damping is not affected.

Fast Power System Restoration Via Load Shedding Practices in The Egyptian Power System.(Dept.E)

This paper investigates the dynamic stability of power systems due to disturbances of finite magnitude that last for some minutes. In this paper the effect of only active power deficits is investigated. A computer program is developed to discuss system frequency changes during such disturbances. The program implements a practical approach using an energy aproach and gives an insight to the following issues :

Dynamic Stability Enhancement Through the Application of Stabilizers of Electromechanical Oscillations

Power system dynamic stability is one of key issues system engineers face. Oscillations that regularly occur in the system, limit the transmission capability of the network. The need to study the stability of power systems has been increasingly growing along with the development of power systems and their grouping into large interconnections. The focus of this paper is determining the dynamic stability of a synchronous generator, and thus the power system, by applying the general theory of stability of dynamic systems. Furthermore, the procedure for the initial adjustment of the parameters of a conventional (IEEE3 type PSS1A) stabilizer of electromechanical oscillations is briefly described based on the frequency response analysis of a linear generator model also known as the Heffron-Phillips generator model.

Coordinated fuzzy logic‐based virtual inertia controller and frequency relay scheme for reliable operation of low‐inertia power system

Coordination between protection and control devices is crucial for maintaining continuous operation of power systems. Existing strategies suffer from improper coordination of control and protection devices. Moreover, high penetration levels of renewable energy sources result in lowering the overall power system inertia. Therefore, this paper presents a robust fuzzy-logic control (FLC) method for superconducting magnetic energy storage (SMES) in low inertia power systems. The new proposed FLC enables robust and wide operating range for SMES compared to the widely employed controllers. The proposed FLC method and load frequency control are coordinated to emulate virtual inertia. In addition, a cooperate coordination between frequency relay and proposed controller is preserved to maintain reliable operation of low inertia power systems. To prove the effectiveness of proposed coordination strategy, it has been tested with considering different load and renewable energy sources (RESs) disturbances with varying inertia level of the selected case study. The results demonstrate that the proposed FLC method can achieve robust SMES operation as virtual inertia controller (VIC) at wide operating range. Moreover, cooperative operation of VIC and frequency protection is preserved using the proposed coordination strategy. The power system availability, frequency regulation, and dynamic stability are improved using the proposed method.

Optimal location and capacity of Unified Power Flow Controller based on chaotic krill herd blended runner root algorithm for dynamic stability improvement in power system

AbstractIn this manuscript, the optimal location and capacity of Unified Power Flow Controller (UPFC) based on chaotic krill herd (CKH) with runner root algorithm (RRA) for dynamic stability improvement in power system is proposed. The proposed technique is the combined execution of CKH and RRA hence it is known as CKHRA technique. Here, CKH is utilized to optimal location of unified power flow controller when occurring generator fault. CKH chooses maximal power loss line as optimal location to keep UPFC according to the objective function. The minimal voltage deviation is improved using runner root algorithm from the unified power flow controller control parameters. The minimal voltage deviation is utilized to determine the optimal unified power flow controller capacity. The CKHRA technique is executed at MATLAB/Simulink and the performance is assessed by comparison with other techniques. The performance of CKHRA technique is linked with IEEE 14 bus, IEEE 30 bus, IEEE 57 bus bench mark system, whereas the efficiency is examined against various generator fault conditions. By then the statistical analysis, result accuracy percentage and loss sensitivity index are analyzed. The comparative results thus proven the greatness of CKHRA approach and corroborate its ability to improve the dynamic stability of power system.

Method for testing output limit of AVR in AC exciter excitation system

The excitation system of synchronous generator plays an important role in the static and dynamic stability of power system. ‘Guide for modelling generator excitation system’ requires that the excitation system of new generators should be modelled and remodelled when the excitation system is upgraded. Testing the output limit of AVR is an important content of modelling. Considering inability of tetsing the output limit of AVR in AC exciter excitation system, this paper analyzes the reason using test data firstly, then proposes a new method to test the output limit of AVR, by modifying the maxim firing angle, the output limit can be got, the new method is verified during modelling test of a 145MW generator finally.

Optimal robust disturbance observer based sliding mode controller using multi-objective grasshopper optimization algorithm to enhance power system stability

Power system stabilizer (PSS) has operated as an auxiliary controller for the synchronous generator excitation system to suppress the power system low frequency oscillations. This paper aims to design an optimal robust disturbance observer based sliding mode controller (RDO-SMC) acting as PSS to enhance the power system dynamic stability through the nonlinear control of excitation system. Indeed, the sliding disturbance observer has expeditiously estimated the accumulated consequence of unknown nonlinearities, parameter uncertainties, non-ideal dynamic models and exterior time-varying interferences in support of sliding mode controller. The sliding surface trajectory has been mathematically derived using Lyapunov theory. RDO-SMC has investigated the low frequency suppression of both the terminal voltage and angular speed. Due to multi-objective nature of the designed control problem, multi-objective grasshopper optimization algorithm (MOGOA) has been implemented to optimally tune the parameters of RDO-SMC and other understudy controllers. To verify and validate the performance of proposed controller, the analyses have been performed in single-machine infinite-bus and multi-machine power systems under different disturbance conditions. At last, the comprehensive simulation results have certainly confirmed the dynamic capability of the optimal RPO-SMC.