MATLAB-Based Programs for Power System Dynamic Analysis

Small signal stability is one of the factor to assesst the reliability of a power system. Small signal stability is related to the ability of a power system to maintain synchronization after being exposed by small disturbance. In Indonesia, the reliability of power system is one of the important aspect that has to be achieved. However, very scant attention has been paid on studied small signal stability performance on Indonesia electricity. Hence, this paper studied the small signal stability analysis and its enhancement. 150 kV Sulselrabar interconnected power system is used as test system. To enhance the performance of the system designing coordinated controller of power system stabilizer (PSS) and redox flow batteries (RFB) using cuckoo search algorithm (CSA) is conducted. Eigenvalue, damping ratio, participation factor analysis, and time domain simulation is performed to assess the small signal stability performance and the successfulness of the CSA to optimize the PSS and RFB parameter. From the cases studies, it is found that 150 kV Sulselrabar has 12 local mode and 4 inter-area mode. Furthermore, the coordinated controller between PSS and RFB based on CSA could enhance the small signal stability performance of 150 kV Sulselrabar interconnected system indicated by higher damping, smallest overshoot and fastest settling time.

This paper presents a dynamic model of the equivalent Great Britain (GB) 36-zone power system, which can be used for reliable and realistic assessment of emerging load frequency control mechanisms. Flexible architecture of the presented dynamic test system permits a broad range of security of supply and small-signal stability studies for design of future power grids. It can be particularly useful for academic research, but also for undertaking feasibility studies in power industries. The proposed dynamic test system, which is obtained through network reduction of the original full-scale GB transmission power system developed by National Grid Electricity System Operator (NGESO) Company, provides detailed information about the GB power system. In this regard, the required data and modelling approaches to develop the 36-zone system are provided in detail. The presented dynamic test system represents the system topology, impedance characteristics and electromechanical oscillations of the original GB power system however, it is not an exact equivalent of the master GB system. Illustrative dynamic models of the key system components, including synchronous generators, automatic voltage regulators, power system stabilizers, hydro and steam turbines models along with speed governing systems are presented. Dynamic behavior of 36-zone test system in response to infeed loss contingencies is investigated. Particularly, the impact of changes in the system inertia on the system electromechanical modes is examined using the modal analysis approach. In this context, the mode shape concept is employed to determine dominant generators and contribution of different zones in the low frequency oscillations. Moreover, time-domain simulations are undertaken to validate the modal analysis results. Additionally, the condition of different zones from the viewpoint of frequency nadir and maximum rate of change of frequency for various contingencies and extreme cases are examined.

A static synchronous series compensator (SSSC) has the ability to emulate a reactance in series with the connected transmission line. A static synchronous compensator (STATCOM) is able to provide the reactive power to an electricity network. When fed with some supplementary signals from the connected power system, both SSSC and STATCOM are able to participate in the power system inter-area oscillation damping by changing the compensated reactance or the provided reactive power. This paper analyses the influence of SSSC and STATCOM on power system small signal stability. The damping controller schemes for SSSC and STATCOM are presented and discussed. The IEEE 39-bus New England system model as the test system is built in DIgSIELNT PowerFactory, in which the damping control strategies for both SSSC and STATCOM are validated by time domain simulations and modal analysis. Furthermore, comparison studies show that the SSSC is a better solution in term of equipment capabilities and costs.

Identification of the equivalent linear dynamics and controller design for an unmanned underwater vehicle

Fault diagnosis of the synchronous machine is essential for the safe operation of the modern power system. Recently, impulse frequency response analysis (IFRA) has been used to detect synchronous machine winding short circuit (SC) faults since the failure will significantly alter the IFRA signature of machines. However, there is no standard and reliable code for interpreting the IFRA signatures. It often refers to the frequency response analysis of power transformer standards, the mathematical-statistical indicator of relative factor is directly used to perform the judgment by the standards’ threshold, which might not be appropriate. Besides, the internal mechanism of frequency response analysis diagnosis is unclear. Therefore, this study proposes a technique based on image classification and smooth grade and gradient-based class activation maps (Smooth Grad-CAM++) to understand and interpret the IFRA method. It trains and analyzes the visualization results of the fault data set of a 5 kW synchronous machine’s winding. The experimental results show that the average accuracy of the image classification model based on Resnet18 reaches 99.63%. We performed an IFRA difference analysis according to the visualization results and gave some suggestions about IFRA. The training and detection process can be accelerated based on these suggestions. To illustrate the generalization of the suggestions, another 8 kW synchronous machine is used for the case study, and the experimental results show that these suggestions are still effective. The main contributions of this study are understanding the internal mechanism of IFRA diagnosis from another perspective and providing some conclusions different from previous research results on the IFRA method for the synchronous machine.

Guest Editorial: Situational awareness of integrated energy systems

Marman clamp system is usually used to fasten spacecraft and the launch vehicle, or different sections of spacecraft. In this paper, the axial stiffness of the marman clamp system was calculated by theoretical calculation. Then stiffness of marman clamp system was taken into account in the finite element method (FEM) model of spacecraft. Finally, modal analysis and frequency response analysis were carried out to validate the effects of marman clamp system on dynamic characteristics of spacecraft. The simulation results were compared with those results based on the FEM where the spacecraft was considered to be fixed to explore the effect of the marman clamp system on dynamic characteristics of spacecraft. The results showed that the fundamental frequency of satellite decreases when taking into account of marman clamp system, and the later fundamental frequencies at horizontal directions decrease more than the longitudinal direction. The acceleration responses of the satellite changed little when taking into accounting of the marman clamp system. The analysis method and results may extend to other spacecrafts with marman clamp system.

This paper proposes notions and a tool for passivity properties of non-homogeneous switched Differential Algebraic Equation (DAE) systems and their relationships with stability and control design. Motivated by the lack of results on input-output analysis (such as passivity) for switched DAE systems and their interconnections, we propose to model non-homogeneous switched DAE systems as a class of hybrid systems, modeled here as hybrid DAE systems with linear flows. Passivity and its variations are defined for switched DAE systems and methods relying on storage functions are proposed. The main contributions of this paper are: 1) passivity and detectability concepts for switched DAE systems, 2) links of the aforementioned passivity and detectability properties to stabilization via static output-feedback. Our results are illustrated in a power system, namely, the DC-DC boost converter, whose model involves DAEs and requires feedback control.

Traditionally, the linear analysis of a power system is performed by first computing a state space model, followed by the application of a suitable analysis method. However, the applicability of this approach is restricted by several practical limitations: typical power systems are represented by very large state matrices that require specialized large-scale eigen analysis programs; the program where the power system models reside does not include linearization capabilities; only time domain data is available. This article illustrates the applicability of a new system identification software program, SYSID, developed to circumvent these limitations. The program incorporates several identification techniques that allow for the computation of equivalent linear models, suitable for control design applications, from time domain simulation data. The program has been used to calculate equivalent models from simulations performed with standard stability programs, as well as from the Electromagnetic Transient Program (EMTP) simulations of detailed three-phase power systems. The equivalent systems are small and retain the modal characteristics of the original system. The identification techniques are based on various algorithms including Prony's method, transfer function fitting, and Hankel matrices. In addition to the identification algorithms, the program also includes signal processing, plotting, modal analysis functions, and basic control design capabilities to assess closed loop system performance.

In recent years, machine learning (ML) tools have gained tremendous momentum and received wide-spread attention in different segments of modern-day life. As part of digital transformation, the power system industry is one of the pioneers in adopting such attractive and efficient tools for various applications. Apparently, a nonthreatening, but slow-burning issue of the electric power systems is the low-frequency oscillations (LFO), which, if not dealt with appropriately and on time, could result in complete network failure. This paper addresses the role of a prominent ML family member, particle swarm optimization (PSO) tuned adaptive neuro-fuzzy inference system (ANFIS) for real-time enhancement of LFO damping in electric power system networks. It adopts and models two power system networks where in the first network, the synchronous machine is equipped with only a power system stabilizer (PSS), and in the other, the PSS of the synchronous machine is coordinated with the unified power flow controller (UPFC), a second-generation flexible alternating current transmission system (FACTS) device. Then, it develops the proposed ML approach to enhance LFO damping for both adopted networks based on the customary practices of statistical judgment. The performance measuring metrics of power system stability, including the minimum damping ratio (MDR), eigenvalue, and time-domain simulation, were used to analyze the developed approach. Moreover, the paper presents a comparative analysis and discussion with the referenced works’ achieved results to conclude the proposed PSO-ANFIS technique’s ability to enhance power system stability in real-time by damping out the unwanted LFO.

Undetected short circuit faults are a significant problem in power transformers and can eventually develop into catastrophic faults. At present, frequency response analysis (FRA) is one of the well-recognized diagnostic tools for the detection of winding faults, but it has some limitations, such as a low signal-to-noise ratio (SNR) and instability caused by changes in the measuring voltage. In this paper, a novel method called sweep frequency impedance (SFI) is proposed to address the difficulties that arise from FRA. Based on the mechanism of this new method, a nondestructive testing system was established to demonstrate the advantages of SFI measurements. The SFI test system has a better stability, repeatability, and SNR by comparing it with the FRA test system. Moreover, FRA and SFI curves obtained under the same conditions was symmetrical about a specific straight line above 10 kHz, and the SFI value at 50 Hz is equivalent to the short circuit impedance (SCI) value of a transformer. These results indicate that the existing criteria of FRA and SCI methods can be used in the SFI method to detect transformer faults. Finally, the experiments on a special oil-immersed testing transformer demonstrate that the SFI detection system is feasible, sufficiently sensitive to detect short circuit faults and able to quantify the level of the fault.

A physically motivated approach to modeling the dynamic behavior of viscoelastic structures using augmenting thermodynamic fields was previously reported. Anelastic displacement fields, special kinds of augmenting thermodynamic fields, are now introduced. Instead of addressing physical damping mechanisms directly, as in the earlier approach, their effects on the displacement field are considered. In this approach, the total displacement field comprises two parts: 1) an elastic part and 2) an anelastic part. The material constitutive equations are developed, as well as the governing differential equations and boundary conditions for a one-dimensional structural member, and are compared to the results developed previously using the augmented thermodynamic fields approach. In addition, a physical interpretation of some of the quantities involved is advanced in terms of a classical mechanical analogy. Because the anelastic displacement field(s) and the total displacement field may be treated similarly in analytical or numerical study, the key practical benefit of this anelastic displacement fields approach is that it leads to the straightforward development of time-domain finite element models. Modal analyses and frequency response analyses have been implemented using the matrix manipulation capabilities of a commercial finite element code.

This study presents coordinate control tuning of power system stabilizer (PSS) with series and shunt FACTS controllers. Here thyristor controlled series compensator (TCSC) and static synchronous compensator (STATCOM) based controllers are coordinated to enhance the damping of power system inter area oscillations. The design of proposed damping controller is formulated as an optimization problem and the controller gains of a linearized power system are optimized instantaneously using genetic algorithm (GA). Here the power system employed with PSS and STATCOM as well as TCSC. The coordinated tuning among the damping controllers is performed on the linearized power system model. Finally, the proposed coordinated controller performance is tested with both eigen value analysis and time domain simulations. Three different control schemes are employed on the test system and the simulation results are compared.

This paper investigates the most suitable location to place variable-speed wind generator based wind farms in a power system considering the steady-state voltage stability. The doubly-fed induction generator (DFIG) and the full-converter wind generator (FCWG) based wind generation is considered and the inherent reactive power capability of these generators are accurately represented in the study. Steady-state voltage stability is analysed using QV modal analysis and QV curves. QV modal analysis is used to identify the weak and strong busbars in the test system. Wind power generators with different power outputs are integrated to the power system from weak and strong busbars and the impact of voltage stability is compared using QV stability margins of the busbars. The results demonstrate that adding wind generation from the weak busbars significantly increases the QV stability margin of the weak busbars. However, adding wind generation from strong busbars slightly improve the stability margin of the weak busbars. Therefore, placing wind farms in the weak busbars in a power system is favorable for the overall voltage stability. Furthermore, the results of DFIG and FCWG based wind generation are compared and the higher reactive power capability of the FCWG based wind generation to support the voltage stability is demonstrated.

With the increased size of the finite element model for improved accuracy, the modal frequency response analysis has been one of the common practices of evaluating the performance of vehicle dynamics. However, there is difficulty in predicting the vehicle dynamics response with non-proportional damping regarding performance. The fast frequency response analysis algorithm (FFRA) has been proved to be very effective for partially damped structural system in the modal frequency response analysis. In the fast frequency response analysis algorithm, performance depends mainly on the complex symmetric matrix eigenvalue problem. Therefore, an efficient complex symmetric matrix eigenvalue problem solver is developed in this article. This approach also uses parallel processing in a shared memory machine for more efficient analysis. Numerical examples show that the new complex symmetric matrix eigensolver provides good accuracy and high performance. Then, the fast frequency response analysis algorithm is applied to a full scale vehicle system that includes only a few viscous damping finite elements. The fast frequency response analysis algorithm significantly improves the performance of the modal frequency response analysis compared to conventional method. In addition, parallel processing improves the efficiency of the overall simulation.