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Rotor interturn short circuit (RISC) is a common electrical fault in generators. Investigations about such fault on the rotor vibrations, magnetic field variations, and current/voltage changes have been widely carried out, while the thermal properties of the stator side have been rarely studied. This paper presents a comprehensive study on the stator thermal behavior in synchronous generators under different RISC position and varied power load cases. Such thermal behavior includes not only the core loss, copper loss and temperature variations of the stator, but also the mechanical responses of the stator core due to the unbalanced thermal distribution. The whole work is based on the magnetic flux density (MFD) analysis, the core loss and copper loss calculation. Theoretical analysis, finite element calculation, and experimental study are carried out, respectively, by taking a 5 kV A two-pole prototype generator as the case study. During the analysis, the reinforced excitation performance by the automatic control system of the generator set due to the voltage sag caused by RISC is fully considered. It is shown that RISC will significantly increase the stator temperature due to the reinforced excitation. The farther RISC position away from the big tooth is, the larger temperature/thermal risk will be. Besides, the stator temperature will also enlarge with the increase in power load. [ABSTRACT FROM AUTHOR]

This study conducts an in-depth exploration into the principal factors that influence the reliability of specialized rail cars and auto-rail vehicles. It places a particular emphasis on key performance metrics including the average operational duration prior to failure, the probability of faultless operation, the rate of failure, and the gamma-percentage resource. Additionally, the paper examines various methodologies for computing these metrics and quantitatively evaluating their respective values. It elucidates how specific units of electromechanical equipment, which operate in conjunction with asynchronous motors and clutches, exhibit distribution patterns during failure that overlap between exponential and normal distributions. The study further presents a mathematical formula to approximate the reliability density of the distribution, a critical factor in recalibrating the metrics associated with specialized rail cars. [ABSTRACT FROM AUTHOR]

Starting an induction motor causes voltage sag in the industrial grid that may disturb the operation of grid equipment. Direct-on-line starting is the simplest and most cost-effective method for starting induction motors, but also the most problematic. Large industries often use internal power plants with synchronous generators and starting powerful motors may impact the generator operations. The synchronous generators could be operated with the automatic or manual mode of voltage control. As the operation experience proves, the generator voltage control mode has a significant impact on the transient behaviours in the industrial power grid when starting a large induction motor. This article presents a case study of the synchronous generator tripping within a true medium-voltage industrial grid during the direct-on-line starting of a large induction motor driving the feed water pump. An analysis of the generator protection logs after the tripping showed that the synchronous generator was controlled in manual mode and its protection relay settings were exceeded. The transients initiated by induction motor starts were studied for possible configurations and operating conditions of the grid using a model developed on the Matlab/Simulink Software platform. The simulations have shown that concern about starting large motors in industrial grids containing internal synchronous generators needs to be solved considering the grid configurations and the coordination of generator protection and control devices. [ABSTRACT FROM AUTHOR]

Maintenance of transient stability is important for the stable operation of power systems. However, as a large amount of renewable energy sources are concerned that the transient stability deteriorates. Excitation control systems have been widely used to improve the transient stability. The defect is that only the synchronous generator (SG) near the fault location changes the excitation voltage so much immediately after the fault. In this study, we propose a novel excitation control method based on an event‐based wide‐area emergency control system. In this method, the SGs that are distant from the fault location play a role to mitigate the first swing as well as the SGs near the fault. The effectiveness of the proposed method is verified demonstrated by numerical simulation for a multi‐machine test system [ABSTRACT FROM AUTHOR]

Modern electrical power systems are characterized by a high rate of transient processes, the use of digital monitoring and control systems, and the accumulation of a large amount of technological information. The active integration of renewable energy sources contributes to reducing the inertia of power systems and changing the nature of transient processes. As a result, the effectiveness of emergency control systems decreases. Traditional emergency control systems operate based on the numerical analysis of power system dynamic models. This allows for finding the optimal set of preventive commands (solutions) in the form of disconnections of generating units, consumers, transmission lines, and other primary grid equipment. Thus, the steady-state or transient stability of a power system is provided. After the active integration of renewable sources into power systems, traditional emergency control algorithms became ineffective due to the time delay in finding the optimal set of control actions. Currently, machine learning algorithms are being developed that provide high performance and adaptability. This paper contains a meta-analysis of modern emergency control algorithms for power systems based on machine learning and synchronized phasor measurement data. It describes algorithms for determining disturbances in the power system, selecting control actions to maintain transient and steady-state stability, stability in voltage level, and limiting frequency. This study examines 53 studies piled on the development of a methodology for analyzing the stability of power systems based on ML algorithms. The analysis of the research is carried out in terms of accuracy, computational latency, and data used in training and testing. The most frequently used textual mathematical models of power systems are determined, and the most suitable ML algorithms for use in the operational control circuit of power systems in real time are determined. This paper also provides an analysis of the advantages and disadvantages of existing algorithms, as well as identifies areas for further research. [ABSTRACT FROM AUTHOR]

It is well-known that co-ordination of protective devices and fault localization techniques in active distribution networks require results of various short-circuit (SC) analyses in the time domain. Accordingly, the main aim of this paper is to calculate the three-phase bolted SC current in the time domain for a radial medium voltage (MV) feeder, which is connected to a MV distribution network, and which has one induction generator (IG) and one synchronous generator (SG) at two different locations. The SC analysis of this concrete case study can be regarded as a novelty. The SC analysis is based on the well-known equivalent circuit models for the MV distribution network, IG and SG, as well as the applications of Kirchhoff's laws and the theorem of superposition. In addition, the proposed analysis method enables calculation of the SC current in the cases where the arc resistance at the fault location cannot be neglected. Finally, the results showed that there are no limitations on the application of the proposed method to the task of calculating asymmetrical SC currents. [ABSTRACT FROM AUTHOR]

Current physical systems are built in more that one coordinate: for example, electrical power systems, aeronautical systems and robotic systems can be modeled in multibond graphs (M B G) . However, in these systems, some elements use only one axis or dimension—for example, actuators and controllers—which can be modeled in bond graphs (B G) . Therefore, in this paper, modeling of systems in multibond graphs and bond graphs ( M B G - B G ) is presented. Likewise, the junction structure of systems represented by ( M B G - B G ) is introduced. From this structure, mathematical modeling in the state space is presented. Likewise, modeling of systems on a platform ( M B G - B G ) can be seen as symmetric to the mathematical model that represents these systems. Finally, a synchronous generator modeled by ( M B G - B G ) as a case study is developed, and simulation results using 20-Sim software are shown. Furthermore, an electrical power system connected to the power supply of a DC motor as another case study is explained. [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]

The article presents the solution of a power rectifier system dedicated to cooperating with an electric generator based on a special synchronous generator, which can be used in wind or water energy systems. In this generator, a pair of three-phase windings in a stator is utilized. One of the windings is connected in a star, and the second one is connected in a delta configuration. Two six-pulse uncontrolled (diode) rectifiers are included at the outputs of the windings. The rectifiers are coupled by a pulse transformer. The primary windings of this transformer are supplied by a power-electronics current source called a current modulator. With the help of this current modulator, the quasi-sinusoidal magnetomotive force (mmf) in the stator of the machine can be obtained. Additionally, to improve the efficiency of the described system, the low-power transistor rectifier, which is connected to the DC bus of the current modulator, has been used. With the help of this converter, it is possible to control and stabilize the voltage level in a DC circuit. It works, in this case, in inverter mode. The principle of working and elaborated control methods of the current modulator and the additional rectifier are presented. Selected results of simulation and experimental tests are also presented. [ABSTRACT FROM AUTHOR]

In the development of a digital twin (DT) for hydropower turbines, dynamic modeling of the system (e.g., penstock, turbine, speed control) is crucial, along with all the necessary data interface, virtualization, and dashboard designs. Since the DT must mimic the actual dynamics of the hydropower turbine accurately, adaptive learning is required to train these dynamic models online so that the models in the DT can effectively follow the representation of the actual hydropower turbine dynamics accurately and reliably. This study presents an adaptive learning method for obtaining the hydropower turbine models for DT development of hydropower systems using the recursive least squares algorithm. To simplify the formulation, the hydropower turbine under consideration was assumed to operate near a fixed operating point, where the system dynamics can be well represented by a set of linear differential equations with constant parameters. In this context, the well-known six-coefficient model for the Francis turbine was formulated as the starting point to obtain input and output models for the turbine. Then, an adaptive learning mechanism was developed to learn model parameters using real-time data from a hydropower turbine testing system. This led to semi-physical modeling, in which first principles and data-driven modeling are integrated to produce dynamic models for DT development. Applications to a pilot system at the Norwegian University of Science and Technology (NTNU) were made, and the models learned adaptively using the data collected from the university's pilot system. Desired modeling and validation results were obtained. [ABSTRACT FROM AUTHOR]

A dynamic rotor interturn short circuit fault may occur during synchronous generator operation. However, there is no method to analyze the generator's characteristics under the dynamic rotor interturn short circuit fault and identify the fault. In order to solve this problem, a new dynamic rotor interturn short circuit fault analysis model is creatively proposed through mathematical derivation. Firstly, the rotor vibration characteristics and the mechanical response under magnetic pull excitation are theoretically analyzed. In addition, a finite element modeling method for the dynamic rotor interturn short circuit fault is proposed, and an experimental device is designed. The model of a synchronous generator under the dynamic rotor interturn short circuit fault is established to obtain the rotor's unbalanced magnetic pulls and mechanical responses by finite element calculation. Finally, the rotor vibrations are tested on a CS-5 prototype generator. The validity of the model is verified by finite element calculation and an experiment. This paper provides theoretical support for the diagnosis of a synchronous generator's dynamic rotor interturn short circuit fault. [ABSTRACT FROM AUTHOR]

Loss of Excitation (LOE) is the most considerable fault in Synchronous generators since it affects both the generators and power network. The traditional protection method for LOE is based on impedance trajectory of the machine with negative offset mho relay. Meanwhile the traditional method experiences malfunctions and speed dip in LOE detection. This paper presents machine learning approach to detect LOE fault as well as classification logic to discriminate LOE fault from power swing conditions due to Line fault. This paper utilizes Hotelling's-T2 statistical method to calculate Hotelling's-T2 based Fault Indices (HT2-FI) for fault detection and Support Vector Machine (SVM) for classification. The time series data of electrical quantities such as Terminal voltage and Reactive Power of the generator are extracted from simulated Single Machine Infinite Bus test system and used as input data. These data involved in calculation of HT2-FI and in development of classification logic. The proposed method is simulated and verified for complete, partial LOE conditions and power swing conditions. Simulation outcomes depict the remarkable signs of the proposed method in LOE identification from power swing. Comparative assessment also reports that the method is capable of saving time in detecting LOE. [ABSTRACT FROM AUTHOR]

Faults in the power system should be detected as soon as possible. Otherwise, some defects in the protection system can result in imposing considerable destructive damage to the system equipment. The excitation system of a synchronous generator plays a significant role in the proper operation and control of the generator. Loss-of-excitation (LOE) may cause harmful effects on both the generator and power system. If LOE is not correctly detected, an unnecessary trip signal may be issued, resulting in the overloading of parallel generators and even a system blackout. Conventional techniques for detecting this fault are based on impedance measurement. Despite the simple structure of these techniques, they are sometimes unable to detect some faults correctly. The presence of flexible alternating current transmission system devices can significantly affect the impedance characteristic of the system and as a result, the operation of impedance relays. In this article, first, LOE and other bugs causing failures and errors in the protection of LOE are simulated in the presence and absence of a unified power flow compensator (UPFC), and parameters with different behavior are determined. Then, the most sensitive parameters are sorted using an intelligent method based on their sensitivity. Once the sort order table is obtained, the first two parameters are applied to a ground data handling neural network method, and LOE is detected. The simulation results show that the proposed algorithm is significantly reliable in detecting LOE faults. Moreover, LOE is detected very quickly in the presence or absence of the UPFC in the system by preventing the tolerance of electrical and mechanical stresses by the machine and system; thus, the maloperation of the protection system is avoided. [ABSTRACT FROM AUTHOR]

The loss of excitation (LOE) is a very common fault in synchronous machine operations and can be caused by a short circuit in the field winding, unexpected operation of the field breaker. Several methods are proposed to detect LOE, but most of them are impedance-based. It is possible that these methods will not be able to identify between LOE and stable power swing (SPS). In this paper, a new method for LOE fault detection is presented, which is designed based on the derivative of the terminal voltage and the derivative power angle of the synchronous generator. According to the proposed idea, complete simulation studies have been performed by considering different fault modes in the synchronous generator and the different conditions governing it to check the accuracy of the performance. These studies show that the proposed algorithm is faster and more accurate in detecting LOE fault. It also has higher security in distinguishing LOE fault from SPS. [ABSTRACT FROM AUTHOR]

This paper presents a precise analysis of the efficiency characteristic of the synchronous generator under both normal and SAGE conditions. In this work, various losses of the synchronous generator are computed by the qualitative theoretical model and the finite element analysis in detail. Further, the generator efficiency model is proposed according to the relationship between the output power and the loss. The presented model is verified in a 5-kW non-salient synchronous generator. The result demonstrates that the loss increases and the efficiency reduce as the SAGE intensifies. [ABSTRACT FROM AUTHOR]

Fast and accurate detection of emerging faults in synchronous generators, which have found wide application in power and transport systems, contributes to ensuring reliable operation of the entire system. This article presents a new approach to making accurate decisions on the continuation of the operation of damaged generators in accordance with the requirements of IEEE standards. The necessity of limiting the duration of operation of the generator in conditions of asymmetric short circuits in the stator windings is substantiated. The authors of the article, based on an artificial neural network in the Matlab software environment, have developed a model for detecting, classifying, and making quick and accurate decisions about the operation of the generator in the event of asymmetric short circuits in the stator windings of the generator. This makes it possible to simulate the operation of the generator at various parameters. Prior to training the neural network, the database formed by phase current and voltage signals was analyzed by various features. The neural network was trained using the back-error-propagation algorithm. The output 10 neurons of the network showed the state of the phase windings of the stator. The recorded information of the output neurons was evaluated, in terms of meeting the requirements of the IEEE standard, and decisions were made about continuing or interrupting the generator operation. Tests of the effectiveness of the model showed that it could achieve the desired result at step 49, and the calculated accuracy was 99.5833%. The results obtained can be successfully used in the development of high-speed and highly reliable diagnostic systems and control and decision-making systems for generators for various purposes. [ABSTRACT FROM AUTHOR]

Shaft voltage often exists in synchronous generators due to the assembly error or various faults after the long‐term performance. The article investigates the shaft voltage characteristic under the stator interturn short circuit (SISC) condition. Different from other studies, this article mainly considers the mapping relationship between the amplitude–frequency characteristics of the shaft voltage and the SISC degrees. The detailed shaft voltage expressions are first derived based on the magnetic flux density under the normal condition and SISC condition. Then the finite element analysis and the experiment is studied on a CS‐5 prototype synchronous generator with two poles in order to validate the theoretical formula. The result shows that there is no shaft voltage in the normal condition, while the shaft voltage is generated obviously under the SISC condition. Meanwhile, the frequency component of the shaft voltage is mainly composed of odd harmonics including the first, third and fifth harmonics. [ABSTRACT FROM AUTHOR]

Faults between stator winding turns of synchronous generators have led to specific changes in the harmonic content of currents. In this paper, these changes are used to detect faults in variable-speed synchronous generators connected to three-level converters during their operation. Currents typically measured for control purposes are used to avoid installation of additional sensors. The neutral point current of the three-level converter is also evaluated under faults in the generator. Encoder-tuned dynamic filters based on Park transformation and Fourier coefficients together with low-pass filters are used to detect the selected harmonics under variable speeds. The geometric loci of these components are proposed as a method to distinguish between healthy and faulty conditions. Simulation and experimental data are used to test sensitivity, selectivity and detection time of the proposed technique for different fault types. Generalization for a different generator is also presented and tested. Most fault cases were detected using the harmonics. [ABSTRACT FROM AUTHOR]

The synchronous generators (SGs) supplying non-linear loads have harmonically distorted terminal voltages. Hence, these distorted terminal voltages adversely affect the performance parameters of the supplied loads such as the power factor, current distortion, losses, and efficiency. To mitigate the harmonic voltages and currents, passive and active filters are generally employed. However, passive filters cause resonance problems, while active filters can cause high costs. On the other hand, in several recent studies to reduce the SG's terminal voltage harmonic distortion, which depends on the constructional design under the no-loading condition, the conventional DC excitation current has been modulated with AC harmonic components. These field current modulation methods have high computational complexity, and require extra hardware for their implementation. In the present paper, firstly, for the reduction of the terminal voltage harmonic distortion of the SG under non-linear loading conditions, the validity of the field current modulation technique is investigated. The numerical results show that by using the field current modulation method, under rated loading conditions, the total harmonic distortion of the terminal voltage can be reduced from 18% to 11%. Secondly, to provide a computational efficient and low-cost tool for optimal field current modulation, which minimizes the terminal voltage harmonic distortion, an Artificial Neural Network (ANN)-based model is proposed. Finally, with the integration of ANSYS Maxwell, ANSYS Simplorer, and MATLAB/Simulink software, the implementation of the developed model is demonstrated for the construction of the optimally modulated field current. [ABSTRACT FROM AUTHOR]

This study aims to develop and test a new accelerated method for analyzing low-frequency oscillations in power systems using phasor measurements. The proposed method is based on the use of mathematical statistics methods that do not require significant computing power and have high reliability. Changes in the structure of power generation and integration of control devices based on power electronics cause low-frequency oscillations of power system operation parameters that present a threat. These changes result in a reduction in the total inertia of power systems with the subsequent impact on the operation of automatic voltage regulators and power system stabilizers, the purpose of which is to damp low-frequency oscillations. We conduct a careful review of the existing methods for low-frequency oscillations analysis in power systems to identify the gaps in the literature and design a new method to address the issues. The proposed method is tested on real-life data that was obtained during a disturbance with a transient event. Estimation of the low-frequency oscillation parameters was carried out, and the potential threat posed by these phenomena was examined. The implementation of the proposed algorithm for analyzing low-frequency oscillations is done using the Matlab programming language. Evaluation of the proposed algorithm is performed on physical data obtained during real transient processes occurring at large power plants. [ABSTRACT FROM AUTHOR]

Stochastic renewable sources of energy have been causing changes in the structure and operation of power systems. High penetration of this type of generation results in decreased inertia of a power system, increased active power fluctuations, and a higher probability of false tripping of emergency control devices. Traditional algorithms of emergency control are not adaptable and flexible enough for systems with high penetration of renewables and flexible alternating current transmission systems. Integration and development of phasor measurement units make it possible to create adaptable emergency control systems, which would require minimal pre‐defined data. The purpose of this study is to develop an adaptable algorithm for turbine fast valving control synthesis and transient stability estimation for a generator. The suggested algorithm is based on the equal area criterion in the domain synchronous generator "torque–load angle". The measurements of the generator operation under consideration are used as the input data for the steam turbine fast valving control synthesis. Thus, the algorithm becomes adaptable because no pre‐defined parameters of a power system model are required. The suggested algorithm was tested on the power system model NE39bus using Matlab/Simulink. The efficiency of the suggested algorithm is verified and demonstrated. [ABSTRACT FROM AUTHOR]

In this article, we present a comprehensive analysis on the thermal response characteristics of the stator winding insulation under static air-gap eccentricity (SAGE) conditions in synchronous generators. Different from previous studies, this article not only takes into account the interactions of both the core-loss-caused heat and the copper-loss-caused heat but also investigates the thermal degrading distribution regularities due to SAGE. The whole work is based on the qualitatively theoretical analysis, the finite-element analysis, and the experimental validation on a nonsalient synchronous generator. The study shows that SAGE will significantly make the temperature rise, resulting in uneven temperature distribution and intensifying the thermal responses, such as the thermal deformations, stresses, and strains, of the insulation. The nose part and the joint between the line winding and the end winding on the smaller air-gap side are the two most dangerous positions. [ABSTRACT FROM AUTHOR]

Geomagneticallyinduced current (GIC) studies usually focus on transformer response to dc but seldom analyze generator excitation systems. A GIC is driven by an electric field which is induced by a very low-frequency geomagnetic field. It is widely acceptable to model GICs with dc, mostly suitable for static voltage stability analysis, but this does not adequately characterize a power system's dynamic response. Considering this, we studied a multi-machine power system on an OPAL-RT digital real-time simulator (DRTS)-MATLAB/Simulink system. We used real GIC measurement data from high and mid-latitude regions. Wavelet analysis related the frequency components of the GIC to the power system's response. A dynamic generator model with excitation voltage control modelled the source. Our main finding is that excitation system control contributes to reducing the voltage drop caused by increased var demand in saturated transformers with GICs. Measured GICs revealed non-negligible short-term dynamics affecting bus voltages that are not captured with dc-modelling assumptions, yet they are important for voltage stability analysis. This study implies that excitation control creates a buffer for high GICs to flow without violating the grid codes for minimum operating voltages and this paper demonstrates the optimization of this novel approach. [ABSTRACT FROM AUTHOR]

Condition monitoring of synchronous generators through non-invasive methods is widely requested by maintenance teams for not interfering the machine operation. Among the techniques used, external magnetic field monitoring is a recent strategy with great potential for detecting incipient faults. In this context, this paper proposes the application of a simple strategy with low computational cost to process data of external magnetic field time derivative signals for the purposes of condition monitoring and fault detection in synchronous machines. The information of interest is extracted from changes in the magnetic signature of the synchronous generator, obtained from frequency spectra of monitored signals using induction magnetic field sensors. The process forms a set of time series that reflects constructive and operational characteristics of the machine. The Shewhart control chart method is applied for anomaly detection in these time series, allowing the detection of changes in the machine magnetic signature. This method is employed in an algorithm for continuous condition monitoring of synchronous generators, presenting as output a global change indicator for the multivariable problem associated with magnetic signature monitoring. Correlation matrices are used to improve the algorithm response, filtering series with similar variation patterns associated with detected events. The proposed method is validated through tests on an experimental bench that allows the controlled imposition of faults in a synchronous generator. The proposed global change indicator allows the automatic detection of stator and rotor faults with the machine synchronized with the commercial power grid. The proposed methodology is also applied on data obtained from an equipment installed in a 305 MVA synchronous generator of a hydroelectric power plant where the evolution of an incipient fault, i.e., a mechanical vibration fault, has been detected. [ABSTRACT FROM AUTHOR]

The results of testing the algorithms of the adaptive model of a synchronous generator using theoretical and real physical data are presented in this study. The adaptive model of a synchronous machine is an equations system, which describes both the static and transient operation of a generator. Parameters of the adaptive model are found using measurements of a generator's operational parameters. The single-machine model was created in Matlab/Simulink software to test the theoretical data. This single-machine model consists of a synchronous generator, a step-up transformer, and a transmission line. The test model also includes models of the automatic voltage regulator and steam turbine governor. The real electrodynamic model was used to verify the adaptive model of a synchronous machine. It consisted of four synchronous generators, with values of power capacity of 5 kW and 15 kW. The data logger with a sampling rate of 57.8 kHz was developed and installed to measure the operating parameters of each generator. As a result of testing on both models, the following values were estimated: inertia moment, d-axis and q-axis reactance, and load angle. These values were compared with the reference values. The adaptive model of a synchronous machine can be used in systems of emergency control and assessment of generator state. [ABSTRACT FROM AUTHOR]

Many methods used for precise fault detection in salient pole synchronous generators (SPSGs) often require a priori knowledge of the healthy case, but this requirement impedes application of the methods since an accurate analysis of different machine quantity waveforms is not usually carried out during commissioning. The inspection and maintenance processes in SPSGs are also costly and time consuming; therefore, reliable methods that can detect and discriminate between different faults without comparison with the healthy condition are highly desirable. This article proposes a precise method for detection and discrimination between different fault types in the SPSG. The method does not require healthy machine data and is applied to diagnose both interturn short circuits (ITSCs) in the field winding and dynamic eccentricities (DEs). The proposed nonintrusive detection algorithm is based on advanced signal analysis of stray magnetic field data and can be applied during SPSG operation. The method is highly precise for monitoring the condition of the rotor field winding and yields a unique pattern for diagnosing possible ITSC faults. Moreover, a distinctive pattern for the DE fault enables the discrimination between both considered failures, even if they are present at the same time. The proposed method is validated through finite-element modeling and experimentally on 100-kVA and 22-MVA SPSGs to demonstrate its applicability in real power plants. [ABSTRACT FROM AUTHOR]

Stochastic renewable sources of energy have been causing changes in the structure and operation of power systems. High penetration of this type of generation results in decreased inertia of a power system, increased active power fluctuations, and a higher probability of false tripping of emergency control devices. Traditional algorithms of emergency control are not adaptable and flexible enough for systems with high penetration of renewables and flexible alternating current transmission systems. Integration and development of phasor measurement units make it possible to create adaptable emergency control systems, which would require minimal pre-defined data. The purpose of this study is to develop an adaptable algorithm of turbine fast valving control synthesis and transient stability estimation for a generator. The suggested algorithm is based on the equal area criterion in the domain synchronous generator Torque—Load angle. The measurements of the generator operation under consideration are used as the input data for the steam turbine fast valving control synthesis. Thus, the algorithm becomes adaptable because no pre-defined parameters of a power system model are required. [ABSTRACT FROM AUTHOR]

The increasing complexity of modern AC/DC power systems poses a significant challenge to a fast solution of large-scale transient stability simulation problems. This paper proposes the hybrid parallel-in-time-and-space (PiT+PiS) transient simulation on the CPU-GPU platform to thoroughly exploit the parallelism from time and spatial perspectives, thereby fully utilizing parallel processing hardware. The respective electromechanical and electromagnetic aspects of the AC and DC grids demand a combination of transient stability (TS) simulation and electromagnetic transient (EMT) simulation to reflect both system-level and equipment-level transients. The TS simulation is performed on GPUs in the co-simulation, while the Parareal parallel-in-time (PiT) scheduling and EMT simulation are conducted on CPUs. Therefore, the heterogeneous CPU-GPU scheme can utilize asynchronous computing features to offset the data transfer latency between different processors. Higher scalability and extensibility than GPU-only dynamic parallelism design is achieved by utilizing concurrent GPU streams for coarse-grid and fine-grid computation. A synthetic AC/DC grid based on IEEE-118 Bus and CIGRÉ DCS2 systems showed a good accuracy compared to commercial TSAT software, and a speedup of 165 is achieved with 48 IEEE-118 Bus systems and 192 201-Level detail-modeled MMCs. Furthermore, the proposed method is also applicable to multi-GPU implementation where it demonstrates decent efficacy. [ABSTRACT FROM AUTHOR]

A pico hydropower plant is an energy harvesting system that allows energy production using the power of the water flowing in small watercourses, and in water distribution network. Axial Flow Flux Permanent Magnet Synchronous Generator (AFPMSG) are particularly suitable for this application, being efficient machines that achieve high power with small dimensions. This paper presents a parametrical study of several configurations and topologies of three-phase and single-phase AFPMSG, for pico hydropower application, to assess the most suitable dimensional characteristics for the most energy production using a safe voltage of 25 V. The AFPMSGs here considered has a simple single stator and rotor configuration, commercial-type permanent magnets, and concentric windings, to facilitate their cost-effective construction and the spread of their use also in developing countries. For each AFPMSG considered, the power output was calculated using 3-D modelling and Finite Element Analysis; besides, the different parameters and features that affect the power output were evaluated at different rotational speeds. The results achieving a power density up to 100 W/cm3, at 1000 rpm with energy produced to 1.7 kWh/day. [ABSTRACT FROM AUTHOR]

Power grids are traditionally dominated by synchronous generators (SGs) but are currently undergoing a major transformation due to the increasing integration of inverter-based resources (IBRs). The state space method with transparent apparatus models can be readily used. However, models of IBRs are usually not disclosed by manufacturers. Alternatively, the port-based approach represents dynamics by input-output transfer functions without exposing internal states. These transfer functions at various ports are normally configured with a particular focus: an SG-dominated grid is traditionally analyzed in a mechanical-centric view which ignores fast electrical dynamics and focuses on the torque-speed dynamics, whereas the emergent IBR-dominated grid usually takes an electrical-centric view which focuses on the voltage-current interaction. In this article, a new perspective called the port-mapping method is proposed to combine these two views. Specifically, the mechanical dynamics are mapped to the electrical impedance seen at the electrical port; and the electrical dynamics are also mapped to the torque coefficient seen at the mechanical port. The bidirectional mapping gives additional flexibility and insights to analyze the sub-system interactions in whole-system dynamics and guide the tuning of parameters. Application of the proposed method is illustrated in three cases with increasing scales. [ABSTRACT FROM AUTHOR]

Interturn field windings faults are quite common in synchronous machines, particularly in turbogenerators. The synchronous machine can operate with a certain interturn fault severity level. This paper presents a new field winding interturn fault severity estimation method based on machine learning regression algorithms. The theoretical excitation current is estimated by artificial intelligent. For this purpose, it is necessary the use of numerous healthy operational data to train the algorithm. Afterward, the algorithm estimates the field current, which is compared to the real current measured. The fault severity level is calculated from this comparison. The use of machine learning implies an improvement on the sensitivity to previous method based on the estimation of the theoretical excitation current by traditional synchronous machines models as Potier or ASA. The measurement errors increase the minimum fault severity level that can be detected. The proposed algorithm has been verified with more than 1800 experimental results in a special laboratory synchronous machine, obtaining a better estimation on the fault severity level than traditional methods. [ABSTRACT FROM AUTHOR]

The purpose of the study presented in the article was to develop a method for the formation of digital twins for distributed generation plants operating as part of cyber–physical power supply systems. A method of forming a digital twin for a system for automatic regulation of the voltage and rotor speed of a synchronous generator is considered. The structure of a digital twin is presented in the form of a multiply connected model using experimental data. The possibility of using a fuzzy inference system, artificial neural networks, and a genetic algorithm for solving the problem is shown. As a result of the research, neuro-fuzzy models of the elements of the distributed generation plant were obtained, which are an integral part of the digital twin. Based on the simulation results, the following conclusions were drawn: the proposed method for constructing an optimized fuzzy model gives acceptable results when compared with experimental data and shows practical applicability in constructing a digital twin. In the future, in order to simplify the model, it is necessary to solve the problem of optimizing the number of rules in the fuzzy inference system. It is also advisable to direct further research to the formation of a complete hierarchical fuzzy system that connects all elements of the digital twin. [ABSTRACT FROM AUTHOR]

In this paper, the Unified Interphase Power Controller (UIPC) is utilized to protect the synchronous generator in case of faults occurring in the transmission system. The UIPC not only maintains the generator's stability by keeping its load angle within safe operational limits but also prevents high-amplitude currents from flowing through the stator windings. This also allows for more loading on the generator without compromising the system's stability. Moreover, utilization of the UIPC improves the LVRT capability of the generator by injecting reactive power at the faulted location. Additionally, a novel unified control scheme is proposed for the UIPC that enhances its performance by omitting the necessity of fault detection algorithms. To evaluate the performance of the proposed controller and the efficacy of the UIPC in protecting the synchronous generator under the faults, simulations have been conducted in a MATLAB/Simulink environment. A test grid was developed comprising a synchronous generator, transmission line model, UIPC, and an infinite grid representing the Point of Common Coupling (PCC), and three fault scenarios have been implemented in the transmission system. The comparative analysis of simulation results demonstrates the capability and efficacy of UIPC in isolating the synchronous generator from the faulted location, which in turn not only enhances transient stability of the generator, but also protects generator windings from detrimental faults currents. Moreover, according to the results, UIPC also contributes to recovering the voltage dip of the fault location via injecting reactive power. [ABSTRACT FROM AUTHOR]

Stability analyzes are examined with the help of simulation programs in the continuous, economical and reliable operation of multi-machine power systems. The most common stability analysis in power systems is small signal stability. In this study, small signal stability analysis was investigated with different generator controller models in a 4-machine 2-field test system. Power System Stabilizer (PSS), Automatic Voltage Regulator (AVR) and Turbine Governor (TG) are used as different generator controller models. The simulation study was carried out in the Power Systems Analysis Program (PSAT). Comparisons were made between the situation where there are no controllers in the synchronous generator and the situations with PSS, AVR and TG models. Comparisons are given in figures and tables. In this study, it was observed that the use of PSS, AVR and TG models in a synchronous generator stabilized the system in a short time, the oscillations in the parameters were reduced and the system gave more effective results in terms of small signal stability. [ABSTRACT FROM AUTHOR]

This article proposes a new rotor interturn short circuit (RISC) fault analysis model for the electromechanical property study in synchronous generators. The specific novelty of this model lies in two aspects: First, It considers that most generators exist static air-gap eccentricity (SAGE), so it analyzes the RISC fault under normal and SAGE, making the model more versatile, and second, it takes into account not only the short circuit degree, but also the short circuit position, consequently it is more universal. By feeding the number of short circuit turns (denotes the short circuit degree), the angle between the two slots, where the short circuit takes place (denotes the short circuit position) and the detailed parameters of the generator into the model, the developing tendency of the key magnetic flux density (MFD)-based parameters can be conveniently predicted. The advantages of the proposed model primarily lie in the universality and the calculation speed. It can quickly evaluate the generator operating conditions. The phase current and the electromagnetic torque are selected in this article as the representatives of the electrical parameter and the mechanical parameter, respectively. Two-dimensional finite element analysis and experimental studies validate the proposed model. [ABSTRACT FROM AUTHOR]

This article proposes a new brushless hybrid harmonic excitation scheme for wind generators, in which the excitation power is provided by the armature current and the stator harmonic control winding current together. In the generation of the field current, besides the main component produced by the excitation control winding equivalent magnetomotive force (MMF), one additional field current component is also produced by on-load armature high-order harmonic and tooth harmonic MMFs, which lead to a self-excitation loop existing in the excitation process. The additional field current component can compensate the flux weakening effect of the load current, which helps to maintain the output voltage characteristic stable in the case of load fluctuation. Besides, the power level of the excitation converter can be greatly reduced. Experimental results on prototype machines validate the effectiveness of the theoretical analyses and finite element analysis (FEA) results. [ABSTRACT FROM AUTHOR]

Compared with traditional power plants, current main stream wind turbines vary in grid connection interfaces, resulting in deficiencies like weak grid voltage and frequency support capability. In order to solve the problem, a synchronous type variable speed wind turbine is proposed in this paper. The wind turbine has the advantages such as the intrinsic properties of maintaining grid voltage and frequency, no harmonic pollution on grid, black start capability. In the wind turbine drive train, an electrically excited synchronous generator is directly coupled to the grid. A power self‐balance type electromagnetic coupling device is used to connect the synchronous generator rotor shaft and a gearbox high speed shaft. The device is composed of a permanent magnet synchronous generator (PMSG), a back‐to‐back converter and an electromagnetic coupler. The converter with small capacity, supplied by the PMSG which is coaxial with the gearbox high speed shaft, is used to apply the electromagnetic torque of the electromagnetic coupler. The matching relationship between the electromagnetic torque and the turbine mechanical torque, and the power flow in the drive train in different wind speeds are analyzed. Control strategies are proposed for the wind turbine normal operation including start, stop, maximum wind power capture, and low voltage ride through (LVRT). Compared with the main stream wind turbines, blade and tower loads can be improved greatly during LVRT. A 2 MW wind turbine model is built in Matlab/Simulink to verify the control strategies proposed and the wind turbine excellent LVRT performance. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Loss of excitation (LOE) is one of the most important issues of synchronous alternators, which may be a source of genuine harms and could lead to power system instability. The principle issue to recognize LOE and stable power swing (SPS) is the time delay, which is a primary segment of the recognition time in all ongoing promise strategies. This paper introduces an effective scheme based on the first derivative of equivalent power factor angle (EPFA) of 3-phase voltage and current quantities in the direct-quadrature axis, to detect the LOE. The new algorithm, based on EPFA, is developed to reduce the required time of LOE recognition scheme. Comprehensive simulation studies are accomplished using MATLAB/Simulink as a robust simulation tool for various generator conditions such as full load and sudden load changes in addition to 3-phase faults with different location and duration times. The relay setting is determined and the algorithm performance is evaluated depending on various scenarios in power system. The simulated study results confirm that the proposed method can discriminate SPS from LOE conditions under different modes of operations. [ABSTRACT FROM AUTHOR]

This paper analyzes the electromagnetic torque (EMT) fluctuation characteristics in synchronous generators under rotor interturn short-circuit (DRISC) fault. The novelty of this paper is that the DRISC fault is proposed based on the intermittent interturn short circuit existing in the actual operation and compared with the static rotor interturn short-circuit (SRISC) fault. In the work, by studying the influence of DRISC with different positions and different short-circuit degrees, the fluctuation characteristic of the EMT is analyzed and verified. The results show that when the DRISC5% fails, the location is in slot 3, the amplitude of first harmonic decreases by 7.2%, second harmonic amplitude increases by 33.4%, third harmonic decreases by 4.3%, and fourth harmonic increases by 26.8%. As the degree increased and positioned away from the large tooth of the DRISC, the overall EMT amplitude and reverse pulse increased, first and third harmonics decreased, and second and fourth harmonics increased. [ABSTRACT FROM AUTHOR]

The design of a fully superconducting wind power generator is influenced by several factors. Among them, a low number of pole pairs is desirable to achieve low AC losses in the superconducting stator winding, which greatly influences the cooling system design and, consecutively, the efficiency of the entire wind power plant. However, it has been identified that a low number of pole pairs in a superconducting generator tends to greatly increase its output voltage, which in turn creates challenging conditions for the necessary power electronic converter. This study highlights the interdependencies between the design of a fully superconducting 10 MW wind power generator and the corresponding design of its power electronic converter. [ABSTRACT FROM AUTHOR]

The aim of this study is to calculate the optimum factor levels for the design parameters namely slot pitch, center slot pitch, and damper width to keep the magnetic flux density distribution in a desired range while minimizing the total harmonic distortion (THD). For this purpose, the numerical simulations are performed in the Maxwell environment. Then by the aid of regression modeling over this simulation results; the mathematical equations between the responses (THD and magnetic flux density distribution) and the factors are calculated. After the modeling phase, grasshopper optimization algorithm (GOA) is run through these regression equations to determine the optimum values of the rotor design parameters (factors). The confirmations are also performed in the Maxwell environment and the result indicated that the THD is minimized and the magnetic flux density distribution on the teeth is kept in a desired range. [ABSTRACT FROM AUTHOR]

Renewable energy resources are gaining fast adoption in the power grid because of their relatively low cost and offered environmental benefits. However, the grid will experience decreased inertia as a result of these added resources. Numerous research studies have focused on improving the grid damping, including the lack of inertia, due to renewable resource integration. In this article, we present an adaptive damping controller to help mitigate oscillations during disturbances on the grid, caused by fault occurrences, sudden load changes, capacitor switching, or even the intermittent nature of the energy sources for most renewable systems, considering both integrated transmission and distribution systems. The test system is developed based on Kundur’s two-area system as the transmission system and the IEEE 123-bus system as the distribution system. Then, the novel proposed adaptive optimal damping control architecture is validated via simulation-based test cases conducted in MATLAB/Simulink using real-life grid data. It is observed that the proposed control architecture not only damps the oscillations more than 10% as compared with the state-of-the-art methods but can also control multiple generators. [ABSTRACT FROM AUTHOR]

Synchronous generators have automatic voltage regulators with limiters that are used to prevent high or low flux in the generator by controlling the Volts/Hertz ratio. Within the operating range of this limiter, it is not necessary to activate the protection functions associated with voltage and frequency. For that, it is necessary to coordinate these limiters with such protection functions. So, this article increases the scope of (Coelho et al., 2018) and (Coelho et al., 2019) by including the coordination studies between Volts/Hertz limiter with overexcitation, overvoltage, and underfrequency protections of synchronous generators. A hardware-in-the-loop simulation is implemented in laboratory to test and evaluate this coordination, and the best settings for it are proposed. An actual power system was modeled in a real-time digital simulator. A great quantity of tests was applied to a synchronous machine (including all its electrical protections and controls) by separately applying frequency steps and voltage steps. The hardware-in-the-loop simulator was prepared to observe an actual digital relay's dynamic responses to these steps. A Volts/Hz limiter, associated with the generator under analysis, is added to the RTDS library. In addition, by analyzing the abovementioned protections and their interaction with the Volts/Hertz limiter of the synchronous machine's excitation system, it is demonstrated that the protections and the limiter should always be jointly investigated. [ABSTRACT FROM AUTHOR]

Nowadays, distributed generation (DG) has become an indispensable part for meeting the growing power demand in electrical power generation and distribution. However, one of the drawbacks of DG is unintentional islanding phenomena, which has become a safety issue for both human and equipment connected to the system. To prevent this hazardous condition, according to IEEE 1547 standards, this islanding condition must be detected within 2 s. This paper proposed an approach to develop a hybrid islanding detection method (IDM) to prevent the damages caused by this islanding condition. The proposed hybrid IDM is a combination of three different IDMs, two passive and one active; that is, rate of change of active power (ROCOAP) and rate of change of reactive power (ROCORP) are passive IDMs where load connecting strategy (LCS) is active. To differentiate islanding conditions with similar occurrences, different case studies are taken into account with photovoltaic (PV) and synchronous generator (SG) working as distributed generators on PSCAD/EMTDC platform. The simulation results confirm that proposed IDM is more favorable compared to other IDMs due to simplicity and fast islanding detection time when its performance is tested on the 11‐kV Malaysian distribution system for various cases. [ABSTRACT FROM AUTHOR]

Synchronous generators are important components of power systems and are necessary to maintain its normal and stable operation. To perform the fault diagnosis of mild inter-turn short circuit in the excitation winding of a synchronous generator, a gate recurrent unit-convolutional neural network (GRU-CNN) model whose structural parameters were determined by improved particle swarm optimization (IPSO) is proposed. The outputs of the model are the excitation current and reactive power. The total offset distance, which is the fusion of the offset distance of the excitation current and offset distance of the reactive power, was selected as the fault judgment criterion. The fusion weights of the excitation current and reactive power were determined using the anti-entropy weighting method. The fault-warning threshold and faultwarning ratio were set according to the normal total offset distance, and the fault warning time was set according to the actual situation. The fault-warning time and fault-warning ratio were used to avoid misdiagnosis. The proposed method was verified experimentally. [ABSTRACT FROM AUTHOR]

This paper discusses the proper selection and interpretation of aggregated control performance indices values mirroring the quality of electrical energy generation by a turbine-generator set cooperating with a power system. Typically, a set of basic/classical and individual indices is used in energy engineering to ensure the mirroring feature and is related to voltage, frequency and active or reactive power deviations from their nominal values desired in the power system. In this paper, aggregated indices based on the sum of weighted integral indices are proposed, verified and built based on the well-known indices originating from control theory. These include an integral of the squared error (ISE) and an integral of the squared error multiplied by time (ITSE), applicable whenever an in-depth analysis and evaluation of various control strategies of the generation system is to be performed. In the reported research, the computer simulation tests verified their effectiveness in assessing the generated electricity on the example of a turbine-generator set controlled using a predictive control technology as well as applicability, proven by numerous simulation results to take various and different in nature requirements into account efficiently, in the form of a single aggregated index. [ABSTRACT FROM AUTHOR]

The paper presents a new model of the thermal rotor protection 49R on synchronous generators with self-excitation with the influence of generator negative sequence protection 46I2. The purpose of the analysis is to solve the problem of simultaneous occurrence of rotor overload due to excitation current and rotor overload due to the inverse component of the stator current. The numerical protections are designed to operate independently of each other, and therefore the residual thermal capacity of the copper windings is not defined with higher precision. A mathematical model that integrates these two protections is given and described. [ABSTRACT FROM AUTHOR]

This article presents a detection technique for data manipulation attacks in distribution systems using transient information present in the measurements. This technique is based on the fact that any legitimate changes in the system will have a transient response which can be measured by the monitoring system. An algorithm is developed for obtaining the transient solution for three-phase distribution networks. A backward–forward sweep technique is developed for the proposed radial electromagnetic transient program (EMTP) which exploits the radial structure of distribution network. An inclusive transient model compatible with the proposed three-phase radial EMTP for three-phase synchronous generators is also developed. The proposed radial EMTP has been benchmarked with conventional EMTP with 5-bus and 22-bus radial distribution systems and with the same test systems, the proposed detection functionality is evaluated. It is shown that the transient solution provided by radial EMTP are in agreement with the results of conventional EMTP. It is also demonstrated that the deviations between the measured values and the solution of the radial EMTP increase significantly during the transient period when a data manipulation attack is carried out. [ABSTRACT FROM AUTHOR]

Recent advancements in aircraft electrification have led to the introduction of turboelectric distributed propulsion (TeDP). For instance, NASA's N3X airplane aims to curb jet fuel emissions with the aid of TeDP. However, it is crucial to analyze the survivability of the TeDP system during extreme conditions. The endogenous failure events are of specific interest as they were found to cause a significant number of accidents for commercial aircraft. While the distribution reconfiguration is necessary to meet the critical load demands under extreme failure events, it can also create a transient overload condition in the turboshaft engine. The power system survivability is further deteriorated in the presence of constant power loads. In this article, a mathematical analysis of the survivability of the system is presented to make the aircraft power system highly resilient to endogenous failure events. A power system collapse mitigation strategy is proposed by adding an energy storage system. Moreover, the analytical expressions are formulated to size the energy storage unit to prevent the system collapse. Various failure conditions are modeled using PSCAD/EMTDC to study the minimum energy storage required to prevent system collapse. [ABSTRACT FROM AUTHOR]

• The impacts of UPFC on the conventional protection scheme is scrutinized. • Features are extracted based on simulation observance and combined with SOM method. • Classification is carried out with LVQ NN. • Proposed method compared to conventional impedance based approach. • The proposed scheme improves the LOE protection function in presence of UPFC. Loss-of-excitation (LOE) conditions may cause devastating effects on both the generator and power system. If LOE is not meticulously detected, two dangerous events may emerge: 1. unnecessary trip signal, 2. not detecting this abnormal condition or detecting it with time delay. Both mentioned flaws have considerable harmful consequences on the generator and power system. Conventional techniques for detecting LOE conditions are based on impedance measurement. The presence of flexible alternating current transmission (FACT) system devices can considerably affect the impedance characteristic of the system and as a result, the operation of impedance-based relays. This paper simulates LOE and stable power swing (SPS) conditions causing failures and errors in the LOE protection in the presence or absence of a unified power flow compensator (UPFC), and parameters with different behaviors are determined. Then, the most sensitive parameters are combined using an intelligent method. The single parameter, achieved from a combination of features in the previous process, is applied to a learning vector quantization (LVQ) neural network. The LVQ is a type of artificial neural network that is based on a prototype supervised learning classification algorithm and trained its network through a competitive learning algorithm. The simulation results show that, in a single machine infinitive bus (SMIB) test system, R-X directional scheme has 2 mal-operations and the proposed algorithm has no mal-operation without UPFC in the system. With UPFC in the system, the R-X directional scheme has four mal-operations and the proposed algorithm has no mal-operation. In the IEEE 9-bus test system, the R-X directional scheme has five mal-operations and the proposed algorithm has no mal-operation. Moreover, applying the proposed algorithm, LOE is detected very quickly in the presence or absence of the UPFC in the system and this approach prevents electrical and mechanical stresses enforced to the machine and power system. © 2017 Elsevier Inc. All rights reserved. [ABSTRACT FROM AUTHOR]