Mode-based damping torque analysis method in power system low-frequency oscillations

This research evaluates the viability of the artificial eco-system optimization (AEO), a novel metaheuristic algorithm, for optimal power system stabilizers (PSSs) tuning in single-machine infinite bus (SMIB) and western system coordinating council (WSCC) multi-machine power systems. The PSS design problem was converted to an optimization problem to achieve optimal tuning, and an eigenvalue-based objective function was employed. The eigenvalue objective function was defined to optimally obtain the PSSs parameters and enhance the power system dynamic performance by improving the damping of electromechanical modes (EMs). The proposed AEO-based PSS performance was validated by comparing the results obtained with genetic algorithm (GA)-based PSS, particle swarm optimization (PSO)- based PSS design, and similar published work. AEO-based PSS method of tuning has been shown to damp electromechanical modes (EMs), control low-frequency oscillations (LFO), and provide better transient performance and convergence rate. Cite this article as: T. Ebuka Odoh, A. Sabo, N. Izzri Abdul Wahab and H. Beiranvand, "Artificial eco-system-based optimization algorithm for optimal design of single-machine infinite bus power system stabilizer," Electrica, 23(3), 522-533, 2023.

An efficient and most famous tool to enhance damping of the power system low frequency oscillations is the conventional widely used lead-lag Power System Stabilizer (PSS). To achieve the desired level of robust performance under transient situation, selecting a suitable design method for optimal tuning of PSS parameters is very important in multi-machine power system. Because, it is a multimodal and difficult combinatorial optimization problem, this paper presents a novel parameter automation strategy for Particle Swarm Optimization (PSO) called PSO with Time-Varying Acceleration Coefficients (PSO-TVAC). This optimization method has a strong ability to successfully control both global and local search in each iteration process for considerably increasing the probability of finding the global optimum solution. The PSO-TVAC algorithm is applied to optimal tuning PSS parameters problem in order to reduce the PSS design effort and find the best possible solution within a reasonable computation time. For this reason, the robustly selection of PSSs parameters is converted as an optimization problem based on the time domain-based objective function under different operating conditions. The robustness of the proposed method is demonstrated on a multi-machine power system in comparison with the classical PSO and conventional method based designed PSSs. It is shown through the nonlinear time domain simulation and some performance indices for a wide range of loading condition. The analysis of the results shows that the improved PSO-TVAC is not only very effective but also provides an excellent ability for damping low frequency oscillations and greatly enhance the dynamic stability of the power system. Moreover, the proposed PSO-TVAC algorithm is superior than that of the classical PSO one in terms of accuracy, convergence and computational effort. Key words: Power system stabilizer (PSS) design, particle swarm optimization, power system dynamics, time-varying acceleration coefficients.

Single machine infinite bus (SMIB) power system and multi-machine power system (MMPS) stability improvement by tuning of static var compensator (SVC) based controller parameters are investigated in the proposed method. The design problem is formulated as an optimization problem with a time-domain simulation-based objective function and real-coded genetic algorithm is used for searching optimal controller parameters. SMIB power system and MMPS models are developed using MATLAB’s SIMULINK which incorporates SVC controller. A fault is created on the transmission line. The simulation results of SMIB power system and MMPS without SVC controller and with SVC controller are presented. The simulation results are analyzed which show that the power system becomes unstable on the occurrence of the fault if SVC controller is not used. This paper proves the effectiveness of the proposed design. Thus the proposed method enhances the power system stability.

Linear quadratic regulator design via metaheuristics applied to the damping of low-frequency oscillations in power systems

Power systems have an increasing demand for operational condition monitoring and safety control aspects. Low-frequency oscillation mode identification is one of the keys to maintain the safe and stable operation of power systems. To address the problems of low accuracy and poor anti-interference of the current low-frequency oscillation mode identification method for power systems, a low-frequency oscillation mode feature identification method combining the adaptive variational modal decomposition and sparse time-domain method is proposed. Firstly, the grey wolf optimization algorithm (GWO) is used to find the optimal number of eigenmodes and penalty factor parameters of the variational modal decomposition (VMD). And the improved method (GWVMD) is used to decompose the measured signal with low-frequency oscillations and then reconstruct the signal to achieve a noise reduction. Next, the processed signal is used as a new input for the identification of the oscillation modes and their parameters using the sparse time-domain method (STD). Finally, the effectiveness of the method is verified by the actual low-frequency oscillation signal identification in the Hengshan power plant and numerical signal simulation experiments. The results show that the proposed method outperforms the conventional methods such as Prony, ITD, and HHT in terms of modal discrimination. Meanwhile, the overall reduction in the frequency error is 34, 44, and 21%, and the overall reduction in the damping error is 37, 41, and 18%, compared with the recently proposed methods such as the EFEMD-HT, RDT-ERA, and TLS-ESPRIT. The effectiveness of the methods in suppressing the modal confusion and noise immunity is demonstrated.

This paper establishes a closed-loop interconnected dynamic model of a power system with a doubly fed induction generator (DFIG) for wind power generation, wherein, the DFIG and power system are modeled as two open-loop interconnected subsystems. The established model indicates that the impact of the dynamic interactions introduced by the DFIG on the power system's small-signal angular stability is the difference between the closed-loop and open-loop electromechanical oscillation modes (EOMs). The analysis conducted in this study reveals that when an open-loop DFIG oscillation mode (DOM) is close to an open-loop EOM on the complex plane, the modal coupling of the open-loop EOM and DOM can cause strong dynamic interactions between the DFIG and the power system; thus, the DFIG has a significant impact on the power system's small-signal angular stability. An example multimachine power system with grid-connected DFIGs is presented to demonstrate and validate the analysis and conclusions made in the paper.

In part I of this paper, based on the extended Phillips-Heffron model of a single-machine infinite-bus power system installed with a FACTS-based stabilizer, the conventional frequency-domain phase compensation method is applied to design the FACTS-based stabilizer. Three types of FACTS-based stabilizers, the SVC-based, TCPS-based and TCSC-based stabilizer, are investigated. Examples of successful applications are presented. In part II the frequency domain phase compensation method's application in multi-machine power systems to design FACTS-based stabilizers is presented. An example of three-machine power system is demonstrated, where a TCSC-based stabilizer is successfully designed by the phase compensation method to damp system oscillations.

A PSO based unified power flow controller for damping of power system oscillations

This paper examines the effects of noise on the adaptive damping of low-frequency oscillations in power systems. Recursive extended least squares (RELS) is incorporated in a self-tuning adaptive controller which uses an enhanced linear-quadratic control algorithm. Simulation results are presented to demonstrate the effectiveness of the controller in a noisy power system environment. These results demonstrate that recursive extended least squares (RELS) can be beneficial to adaptive damping by determining colored noise parameters in addition to system parameters. >

Power-system stability improvement by a static synchronous series compensator SSSC-based damping controller is thoroughly investigated in this paper. The present study considered both local and remote signals with associated time delays. The design problem of the proposed controller is formulated as an optimisation problem, and gravitational search algorithm GSA is employed to search for the optimal controller parameters. The performances of the proposed controllers are evaluated under different disturbances for both single-machine infinite bus power system and multi-machine power system. The performance of the proposed controllers with variations in the signal transmission delays has also been investigated. Simulation results are presented under various operating conditions and disturbances to show the effectiveness and robustness of the proposed approach.

The paper presents a simple method for transient stability assessment of a single machine-Infinite bus power system as well as multimachine power system using a new swallowtail catastrophe model. The control parameter of the above model is calculated algebraically and this reduces the computational burden significantly. The computation for critical fault clearing angle and critical fault clearing time of a typical power system using catastrophe theory has been demonstrated in each case and the same has been compared with the results obtained by the standard step-by-step numerical method.

The quality of power system operating need to assess maturity of small oscillation stability issues of regional power grid thoroughly, analysis level of operating, controller installation allocating and parameter optimization scheme from different develop stage of regional power grid accurately. The assessment scheme is based on damping torque analysis of real large scale power system. Small oscillation stability is to be evaluated through the mechanism of damping torque analysis with automatic voltage regulator and other power system stabilizers. By analyzing the characteristic of the link between damping torque provided or transferred through each generator and the oscillation mode detected in the power system, the maturity indice has been established. This indice may cover the information of the contribution of controllers towards the power system and the dispatching within each generator in power system. Practical application effects in a real large scale power grid indicates this assessment can thoroughly describe the action of control elements in the power grid, help to depict the whole picture of impact applying power system controllers. A novel maturity evaluation of small oscillation in power grid is presented.

In this paper, a new method for analyzing low-frequency oscillation between analytic areas based on energy coefficient is proposed. The concept of energy coefficient is proposed by constructing the energy function, and the low-frequency oscillation is analyzed according to the energy coefficient under the current operating conditions; meanwhile, the concept of model energy is proposed to analyze the energy exchange behavior between two generators. Not only does this method provide an explanation of low-frequency oscillation from the energy point of view, but also it helps further reveal the dynamic behavior of complex power systems. The case analysis of four-machine two-area and the power system of Jilin Power Grid proves the correctness and effectiveness of the proposed method in low-frequency oscillation analysis of power system.

Differential evolution algorithm for SSSC-based damping controller design considering time delay

This study investigates one of the most fundamental issues of integrating fuel cell (FC) generation into power systems – its effect on power system small-signal stability when it operates jointly with conventional power generation. The study first presents a comprehensive mathematical model of the solid oxide fuel cell (SOFC) power plant integrated with the single-machine infinite-bus power system. Based on the model, conventional damping torque analysis is carried out to study the effect of SOFC power generation on power system small-signal stability. The analysis concludes that system small-signal stability can be affected either positively or negatively by the SOFC power plant when system operating conditions change. Two examples of power systems with gird-connected SOFC power plants are presented. Small-signal stability of the first example of single-machine power system was examined when the power system operated at different load conditions and levels of mixtures of conventional and FC power generation. The second example is a four-machine two-area power system where the power supplied by the gird-connected SOFC power plant is variable. Results of simulation using full non-linear model of the power systems and the SOFC power plants are given. All the results from the example power systems confirm and further demonstrate the analysis presented and conclusions obtained.