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This paper proposes a maintenance policy for a k-out-of-n: F system operating to fulfil several jobs without interruptions. The system is replaced when the Nth job completes or at the kth failure, whichever occurs first. So, there are some non-failed components when a replacement is done. These components can be sold as second-hand products to continue working in other systems for a while. The price of them is also considered in the proposed maintenance policy. An optimal maintenance policy is studied to minimise long-run average cost under the constraint of relative mean operating time. Comprehensive numerical studies are done to assess the effect of the model parameters on the optimal solutions. Also, to demonstrate the applicability of the proposed plan, a data set related to wind turbine generator failures is considered as a case study. [ABSTRACT FROM AUTHOR]

With the increasing proportion of renewable energy power generation, its accompanying intermittency and volatility problems are becoming increasingly prominent, and the frequency fluctuation of the power system is becoming increasingly severe. Participation in frequency regulation services can be economically rewarding for generating units. The flywheel energy storage system can effectively improve the frequency regulation capability of coal-fired units. In this paper, the improvement of the FM capability of coal-fired units in the operation of a two-area interconnected power system containing wind power is investigated, and a model of a two-area interconnected power system comprising a turbine generator, wind power, and flywheel energy storage is established. The enhancement of the FM capability of coal-fired units by adding a flywheel energy storage system is analyzed. The simulation results show that adding the flywheel energy storage system improves the FM capability of the coal-fired unit to a considerable extent, and the coal-fired unit can decide the flywheel capacity it needs to be equipped with through detailed economic calculations. [ABSTRACT FROM AUTHOR]

The aim of this research is to evaluate the performance of the distribution network by connecting wind distributed generation (DG) and determining the optimal location and size using the particle swarm optimization (PSO) technique, once the wind DG is connected at the optimal location, the output of wind turbines is not constant but varies with changes in wind speed. Wind turbines are designed to generate the energy from the wind. As the output of the wind turbines changes, it influences the power flow and voltage levels in the distribution network. The injection of power from the wind turbines can cause variations in voltages within the distribution network. Additionally, the changing power flow may contribute to power losses in the distribution system. In this paper, the voltages and active power losses are evaluated with the change in wind speed for the IEEE 15 Bus system by conducting load flow analysis in MATLAB. The results reveal optimized solutions that contribute to reduced power losses, increased renewable energy generation, and improved voltage profiles. This research underscores the potential of PSO-based optimization in conforming more efficient and sustainable distribution networks. [ABSTRACT FROM AUTHOR]

The results of experimental and modeling studies of the distributed generation sources (DG) influence on the occurrence in the Interconnected Power System (IPS) of Ukraine asynchronous modes (AM) caused by accidents in its main electrical network are presented. According to simulation scenarios it was assumed that the DG power was introduced into electrical distribution networks instead of the power units of thermal power plants of the IPS of Ukraine which were destroyed as a result of missile attacks by the Russians. In the absence of information about DGs, certain generalizations and assumptions are made regarding the possibility of DG groups modeling of in the form of turbine generators with different inertia constants. Various scenarios of the accidents occurrence and the functioning of relay protection and anti-emergency automation devices were considered. Conducted studies results show that the DG introduction into distribution electrical networks does not contribute to the AM occurrence in the main electrical network of the IPS of Ukraine. References 11, figures 10, tables 3. [ABSTRACT FROM AUTHOR]

This paper proposes a fault current limiting scheme (FCLS) for full-scale wind power generators based on logic bang-bang funnel control (LBFC). Different from the convention methods such as frequency droop control and sliding control, which design the control strategy according to the specific fault currents, LBFC is able to restrict various fault current within acceptable range in the shortest time, and it is robust to system nonlinearities and external disturbances. The control signal of the LBFC is bang-bang with the upper and lower limits of control variables. In the model of full-scale wind power generators connecting with the power grid, LBFC is designed to control the switches of inverter bridges when over-current is detected, and a vector controller is applied during the normal operation. Time-domain simulations were conducted with PSCAD, and the performance of LBFC was validated. [ABSTRACT FROM AUTHOR]

ABSTRACT Safety analysis of power systems is concerned with the system's ability to maintain critical variables within specified limits following a disturbance. Frequency control adequacy has become increasingly important as the system inertia decreases due to the increase in renewable energy penetration. Various controllers for inverters have been proposed to improve the system frequency response and few are capable to ensure the safety of the response. In this article, a diesel‐wind energy system is considered and modeled as a switching system between normal, faulted, and post‐fault modes. A safety feedback controller is designed as a supplementary signal for a wind turbine generator such that the speed of the diesel generator stays within a permissible range in the presence of a finite energy disturbance. Numerical results on the modified 33‐bus microgrid system obtained of the proposed novel approach indicate that the suggested control configuration can guarantee adequate frequency response without excessive conservativeness. [ABSTRACT FROM AUTHOR]

This nationally adopted international standard is applicable to land-based gas turbines, steam turbines and generators (whether coupled with gas and/or steam turbines) with power outputs greater than 40 MW, fluid-film bearings and rated speeds of 1 500 r/min, 1 800 r/min, 3 000 r/min or 3 600 r/min. The criteria provided in this document can be applied to the vibration of the gas turbine, steam turbine and generator (including synchronizing clutches). This document establishes provisions for evaluating the severity of the following in-situ, broad-band vibration: a) structural vibration at all main bearing housings or pedestals measured radial (i.e. transverse) to the shaft axis; b) structural vibration at thrust bearing housings measured in the axial direction; c) vibration of rotating shafts radial (i.e. transverse) to the shaft axis at, or close to, the main bearings. [ABSTRACT FROM AUTHOR]

A simplified technique has been developed for accurately evaluating the steady-state performance of self-excited induction generator (SEIG). This proposed technique employs nodal analysis of the equivalent circuit of SEIG, taking the core loss resistance (Rm) also into consideration. This circuit has no voltage or current source and hence the net value of its complex nodal admittance becomes zero. The real and imaginary parts of this admittance, are then individually equated to zero and a closed-form expression for per unit (pu) speed (b), without involving the magnetizing reactance (Xm), is easily obtained in a few steps, for the specified pu frequency (a). Then, the expressions for Xm and Rm are also obtained. Subsequently, the complete performance of the SEIG is evaluated using the equivalent circuit. It is also shown that the proposed technique does not require lengthy complex derivations and it takes much less computational time, compared to the other commonly used methods for the analysis of SEIG. Test results, obtained on a three-phase, 4-pole, 3.7 kW, 230 V SEIG very closely agree with the computed values. The formulated technique is also slightly modified to make it applicable, if the performance evaluation is needed for a given pu speed. [ABSTRACT FROM AUTHOR]

A steam turbine generator is a very complex machine and very dangerous because it has the potential to explode. Therefore, it should be equipped with a control system and protection system. A protection system for steam turbine generators is more complex than other facilities in the power-generating industry. Due to its complexity, a high-skill operator is required to operate the facility. In this study, a simulator of a protection system for a steam turbine generator based on a distributed control system DCS ABB 800xA has been developed. The system was developed considering eight parameters to ensure safety, including turbine speed, inlet temperature, vibration, turbine shaft position, steam drum tank level, and lubricating oil pressure. The system also provides a manual emergency push button to anticipate an uncontrollable condition. The developed simulator has been tested to ensure it works properly and protects the steam turbine generator from abnormal conditions. Tests were performed to check interlocking responses caused by a single variable. All the variables have been tested. Another test was performed to check the ability of the simulator to detect abnormal conditions and respond to those conditions. All the tests showed that the simulator system could operate properly. The simulator system is very comprehensive in detecting the potential of turbine trips. This system considered all the variables that were highly reported as the factors of the turbine malfunction. It is the main advantage of the proposed system. The developed system provides significant benefits for training the operator without interrupting the operation of power-generating facilities. [ABSTRACT FROM AUTHOR]

With the large-scale interconnection of wind power generation, the voltage problem of the power system becomes more and more prominent. Compared with adding external reactive power compensation devices, it is more economical and responsive for fans to adjust their control strategies to provide reactive power support. To make full use of reactive power supported by wind turbines, a mathematical model of doubly fed induction generator (DFIG) wind turbines is constructed to characterize the reactive power boundary of wind turbines. Then, active disturbance rejection control (ADRC) is used to generate a voltage control signal to effectively improve the unit's reactive response speed; in addition, a variable gain coefficient is used to adjust the reactive power output of the unit, which effectively improves the reactive power response speed and its control adaptability and robustness under changing power grid conditions. Finally, a wind turbine generator (WTG) simulation model is built using MATLAB/Simulink simulation software, different fault locations are perturbed, and the effectiveness of reactive power support of the proposed ADRC-based strategy is simulated and verified. The proposed ADRC-based strategy could inject more reactive power to the grid to improve the voltage. [ABSTRACT FROM AUTHOR]

Due to high probability of blade faults, bearing faults, sensor faults, and communication faults in pitch systems during the long-term operation of wind turbine components, and the complex operation environment which increases the uncertainty of fault types, this paper proposes a fault diagnosis method for wind turbine components based on an Improved Dung Beetle Optimization (IDBO) algorithm to optimize Support Vector Machine (SVM). Firstly, the Halton sequence is initially employed to populate the population, effectively mitigating the issue of local optima. Secondly, the subtraction averaging optimization strategy is introduced to accelerate the dung beetle algorithm in solving complex problems and improve its global optimization ability. Finally, incorporating smooth development variation helps improve data quality and the accuracy of the model. The experimental results indicate that the IDBO-optimized SVM (IDBO-SVM) achieves a 96.7% fault diagnosis rate for wind turbine components. With the proposed IDBO-SVM method, fault diagnosis of wind turbine components is more accurate and stable, and its practical application is excellent. [ABSTRACT FROM AUTHOR]

In this study, discrete event time-variant parameter of a lumped SISO dynamical system is obtained for a novel energy harvester. The harvester utilizes the resonance vibration of a coupled fluid-mechanic system, which is comprised of a reciprocating-piston, a tunable oscillator and twin electric turbine generators. The system model is simplified by an underdamped spring-mass-damper with tunable parameters subjected to periodic or arbitrary impulse forces. We developed a method that solves general problems underlining non-homogenous ordinary second order differential equation with discrete event time-variant parameters. The method uses the superposition to compile the general solution by segmenting the problem into ODE equations with constant coefficient. Each segment corresponds to a change in system, and it is solved analytically with recursively updated initial conditions. We utilized this method to tune the system's natural frequency such that the accumulated energy is maximum within desired time range. We obtained the general solution of the displacement response due to varying parameters and input impulse force. We obtained the displacement peaks and their time of occurrence that could help understand the structural design limitation. We showed system displacement responses (constructive and destructive) corresponding to various impulse repetition patterns. We derived the relationship between energy, volume displacement, and volumetric flow rate (or piston velocity) and provided illustrative case studies. One finding shows that for a given impulse condition the accumulative energy exhibits local maximum and minimum within a narrow band of natural frequency range. The simulations showed the feasibility of generating considerable power from electric turbine when the air flow is driven by a resonating piston. [ABSTRACT FROM AUTHOR]

The widespread adoption of the power grid has led to increased attention to load frequency control (LFC) in power systems. The LFC strategy of multi-source hybrid power systems, including hydroelectric generators, Wind Turbine Generators (WTGs), and Photovoltaic Generators (PVGs), with thermal generators is more challenging. Existing methods for LFC tasks pose challenges in achieving satisfactory outcomes in hybrid power systems. In this paper, a novel method for the multi-source hybrid power system LFC task by using an optimal active disturbance rejection control (ADRC) strategy is proposed, which is based on the combination of the improved linear quadratic regulator (LQR) and the ADRC controller. Firstly, an established model of a hybrid power system is presented, which incorporates multiple regions and multiple sources. Secondly, utilizing the state space representation, a novel control strategy is developed by integrating improved LQR and ARDC. Finally, a series of comparative simulation experiments has been conducted using the Simulink model. Compared with the LQR with ESO, the maximum relative error of the maximum peaks of frequency deviation and tie-line exchanged power of the hybrid power system is reduced by 96% and 83%, respectively, by using the proposed strategy. The experimental results demonstrate that the strategy proposed in this paper exhibits a substantial enhancement in control performance. [ABSTRACT FROM AUTHOR]

This paper deals with the key operational problems of wind turbosets, especially offshore, where vibrations are generated by rotor blades, as a consequence of erosive wear or icing. The primary causes of the imbalance of wind turbine rotors have been characterised, the observable symptoms of which include various forms of vibrations, transmitted from the turbine wheel to the bearing nodes of the power train components. Their identification was the result of an active diagnostic experiment, which actually entered the aerodynamic-mass imbalance of a turbine rotor into a wind power train, built as a small scale model. The recording of the observed monitoring parameters (vibration, aerodynamic, mechanical and electrical) made it possible to determine a set of symptoms (syndrome) of the deteriorated (entered) dynamic state of the entire wind turboset. This provides the basis for positive verification of the assumed concept and methodology of diagnostic testing, the constructed laboratory station and the measuring equipment used. For this reason, testing continued, taking into account the known and recognisable faults that most often occur during the operation of offshore wind turbosets. Transferring the results of this type of model research to full-size, real objects makes it possible to detect secondary (fatigue) damage to the elements transmitting torque from the wind turbine rotor to the generator early, especially the thrust bearings or gear wheel teeth. [ABSTRACT FROM AUTHOR]

Renewable energies have a fundamental role in sustainability, with wind power being one of the most important due to its low production costs. Modern wind turbines are becoming bigger and more complex, and their operation and maintenance must be as optimized as possible. In this context, supervisory control and data acquisition systems provide valuable information, but there is no precise methodology for their analysis. To overcome this need, a generalized methodology is proposed to determine the recognition of critical subsystems through alarm analysis and management. The proposed methodology defines each subsystem in a precise way, shows the indicators for the alarms, and presents a theoretical framework for its application using the quantity and activation times of alarms, along with the real downtime. It also considers the transition of states when the wind turbine is operationally inactive. To highlight the proposal's novelty, the methodology is exemplified with a case study from the Southern Cone, applying the method through a data management and analysis tool. Four critical subsystems were found, with the alarms of wind vanes, anemometers, and emergency speeds being of relevance. The indicators and the graphical tools recommended helped guide the applied analysis. [ABSTRACT FROM AUTHOR]

To reduce the significant economic losses caused by the fault deterioration of wind turbine generators, it is urgent to detect and diagnose the early faults of generators. The existing condition monitoring and fault diagnosis (CMFD) methods have disadvantages of less considering data temporal characteristic, acquiring early faults with difficulty, and having lower diagnostic accuracy. To address those limitations, a novel LSDAE-stacking CMFD method of generators was proposed. Specifically, a multivariate spatiotemporal condition monitoring model (LSDAE) was established by combining the LSTM and SDAE networks, which can detect generator early anomalies through real-time monitoring the reconstruction residual. Then, based on the stacking ensemble algorithm, a multi-classification fault diagnosis model (Stacking) was constructed to identify early fault types, which can integrate advantages of different base-classifiers to achieve a better diagnostic accuracy. Case studies on three actual generator failures were employed to validate the effectiveness and accuracy of the proposed LSDAE-stacking method. The results illustrated that, compared with conventional SDAE model, the proposed LSDAE model had higher reconstruction precision and superior early-fault-warning capacities. And compared with traditional algorithms such as SVM, RF, AdaBoost, GBDT and XGBoost, the constructed Stacking model can effectively identify the fault types of generators and had higher diagnostic accuracy. [ABSTRACT FROM AUTHOR]

One of the most important challenges of smart grids is the congestion of transmission lines. A flexible smart grid with demand-side resources can be a suitable solution to manage transmission lines congestion. This paper proposes a multi-objective model with the aim of congestion management through generation rescheduling considering cost and emission purposes in a flexible smart grid. An inconvenience cost for consumers is defined to model the consumers' unsatisfactory as a consequence of participating in demand response programs (DRPs). Furthermore, a smart grid flexibility index (SGFI) has been presented to show the available flexibility of smart grid as a result of DRPs and gas turbine generators as fast response resources. The DRPs could increase the flexibility of the smart grids due to their impact on flattening the load curve, but this may cause some inconveniences for consumers. On the other hand, participation of consumers in DRPs and the power output gas turbine are associated with uncertainty. In this paper, the uncertainty of consumer's participation in the DRPs has been modeled by Fuzzy-Markov. The proposed multi-objective particle swarm optimization (MOPSO) has been implemented on the IEEE 30-bus system. The results show that the total operation cost including the generation cost, DRP cost, inconvenience cost of consumers, and pollution is reduced. In fact, the share of generation of expensive generators is reduced. [ABSTRACT FROM AUTHOR]

Economic dispatch (ED) is one of the key problem in power systems. ED tends to minimize the fuel/operating cost by optimal sizing of conventional generators (CG). Greenhouse/toxic gas emission is one of the major problem associated with the CG. Emission dispatch (EMD) deals with the reduction of greenhouse/toxic gas emissions by the optimal output of generators. The multi-objective economic emission dispatch (MOEED) problem has been formulated by considering both fuel cost and emission objectives. The main objective is optimization of fuel cost and environmental emissions from the CG in a compromised way. In this paper, CONOPT solver in General Algebraic modeling system (GAMS) has been proposed to find the the optimal solutions for ED, EMD, and MOEED problems of a microgrid. The microgrid consists of a wind turbine generator (WTG), a photovoltaic (PV) module, three CGs, and a battery energy storage system (BESS) option. The proposed algorithm has been implemented in four case studies, including all energy sources, without WTG, without PV module, and without renewable energy sources (RES). To establish the effectiveness of the proposed algorithm, it has been compared with various algorithms. The comparison result shows that proposed algorithm is more effective, novel, and powerful. Finally, result shows the effectiveness of proposed approach to optimize the objective function for all aforementioned case studies and the CONOPT solver in GAMS outperformed all the approaches in comparison. The impact of BESS on the operating/fuel cost of the microgrid has also been presented for ED. Paradigm is changing in terms of demand response in μG. Demand flexibility (DF) model has also been established with consumers demand variation in optimization process. Result with DF shows the reduction in cost and better management from demand side. [ABSTRACT FROM AUTHOR]

To ensure the stable operation of a wind turbine generator system when the wind speed exceeds the rated value and address the issue of excessive rotor speed during high wind speeds, this paper proposes a novel variable pitch controller strategy based on a back-propagation neural network and optimal control theory to solve this problem. Firstly, a mathematical model for the wind turbine is established and linearized. Then, each optimal sub-controller is designed for different wind speed conditions by optimal theory. Subsequently, a back-propagation neural network is utilized to learn the variation pattern of controller parameters with respect to wind speed. Finally, real-time changes in wind speed are applied to evaluate and adjust controller parameters using the trained back-propagation neural network. The model is simulated in MATLAB 2019b, real-time data are observed, and the control effect is compared with that of a Takagi–Sugeno optimal controller, firefly algorithm optimal controller and fuzzy controller. The simulation results show that the rotor speed overshoot of the optimal controller under the step wind speed is the smallest, only 0.05 rad/s. Under other wind speed conditions, the rotor speed range fluctuates around 4.35 rad/s, and the fluctuation size is less than 0.2 rad/s, which is much smaller than the fluctuation range of other controllers. It can be seen that the back-propagation optimal controller can ensure the stability of the rotor speed above the rated wind speed. At the same time, it has better control accuracy compared to other controllers. [ABSTRACT FROM AUTHOR]

To ensure the safe and stable operation of small and medium-sized wind turbine generators within distributed energy systems, a new active pitch adjustment method for a 1.5 kW distributed pitch wind turbine generator is proposed in this article. The stress and displacement responses of blades under uniform inflow and extreme operating gust inflow conditions were calculated and analyzed using a two-way fluid–structure coupling method. The results showed that under the two different flow conditions, as the pitch angle increased, the stress and displacement responses of the wind turbine blades both significantly decreased, and the decrease was greater with increasing wind speed. The feasibility of the proposed variable-pitch adjustment for blade load reduction under different inflow conditions was further illustrated. The peak of the blade stress response was located at the leading-edge position in the middle of the blades (0.55R) for the different inflow conditions, while the displacement response of the blades was mainly along the waving direction. Through comparative analysis of the blade stress and displacement responses at the same wind speed under different flow conditions, it was found that the maximum mean ratio of the blade displacement and stress responses reached 1.66 and 1.67, respectively. [ABSTRACT FROM AUTHOR]

The primary goal of this study is to develop and test a small-scale horizontal-axis underwater Ocean Current Turbine (OCT) by creating a mathematical model for coupled dynamics aided by a Blade Element Momentum (BEM) simulation-integrated experimental approach. This research is motivated by the urgent need for sustainable energy sources and the vast potential of ocean currents. By integrating mathematical modeling with the experimental testing of scaled model OCTs, this study aims to evaluate performance accurately. The experimental setup involves encapsulating a 3D-printed turbine model within a watertight nacelle which is equipped with sensors for comprehensive data recording during towing tank tests. Through these experiments, we seek to establish correlations between the generated power, force, and rotational speed of the turbine's Permanent Magnet DC (PMDC) motor, which determines the turbine's capability to extract dynamic energy inflow. Moreover, this research aims to provide valuable insights into the accuracy and applicability of theoretical predictions in real-world scenarios by comparing the experimental results with BEM simulations. This combined approach not only advances our understanding of hydrokinetic energy conversion, but also contributes to the development of reliable and efficient renewable energy technologies that address global energy challenges while mitigating environmental impacts. [ABSTRACT FROM AUTHOR]

Current researches mainly focus on the participation of wind farms in primary frequency regulation, including overspeed load shedding control, propeller control and their coordinated control, etc. The frequency support is realized by reserving reserve capacity of wind turbines, but the influence of the dynamic characteristics of maximum power point tracking (MPPT) on the overall frequency regulation characteristics of wind turbines during frequency support is ignored. To this end, firstly, the frequency response model of the system is constructed, and the main factors that affect the frequency dynamic characteristics are revealed. Secondly, the principle of the grid-forming VSC with the function of self-inertial synchronization is introduced, the influence of the dynamic characteristics of MPPT on the frequency regulation characteristics of the wind turbine generator is clarified. Finally, based on the PSCAD/EMTDC electromagnetic transient simulation software platform, the influence of the dynamic characteristics of MPPT on the frequency regulation characteristics are verified by combining the inertia self-synchronous network control technology. The simulation results indicate that with the increase of setting of droop control, the decrease of output power of MPPT becomes large so as to weaken the frequency support capability. [ABSTRACT FROM AUTHOR]

The Oscillating Water Column (OWC) is the most promising self-rectifying device for power generation from ocean waves; over the past decade, its importance has been rekindled. The bidirectional airflow inside the OWC drives the Wells turbine connected to a generator to harness energy. This study evaluated the aerodynamic performance of two hybrid airfoil (NACA0015 and NACA0025) blade designs with variable chord distribution along the span of a Wells turbine. The present work examines the aerodynamic impact of the variable chord turbine and compares it with one with a constant chord. Ideally, Wells rotor blades with variable chords perform better since they have an even axial velocity distribution on their leading edge. The variable chord rotor blade configurations differ from hub to tip with taper ratios (Chord at Tip/Chord at Hub) of 1.58 and 0.63. The computation is performed in ANSYS™ CFX 2023 R2 by solving three-dimensional, steady-state, incompressible Reynolds Averaged Navier–Stokes (RANS) equations coupled with a k-ω Shear Stress Transport (SST) turbulence model in a non-inertial reference frame rotating with the turbine. The accuracy of the numerical results was achieved by performing a grid independence study. A refined mesh showed good agreement with the available experimental and numerical data in terms of efficiency, torque, and pressure drop at different flow coefficients. A variable chord Wells turbine with a taper ratio of 1.58 had a peak efficiency of 59.6%, as opposed to the one with a taper ratio of 0.63, which had a peak efficiency of 58.2%; the constant chord Wells turbine only had a peak efficiency of 58.5%. Furthermore, the variable chord rotor with the higher taper ratio had a larger operating range than others. There are significant improvements in the aerodynamic performance of the modified Wells turbine, compared to the conventional Wells turbine, which makes it suitable for wave energy harvesting. The flow field investigation around the turbine blades was conducted and analyzed. [ABSTRACT FROM AUTHOR]

Wind turbine generator output cables are subjected to alternating torsional loads during long-term operation, combined with electrothermal stress, which may lead to insulation failure and other serious issues. Currently, the electrothermal aging mechanism under torsional stress is not fully understood. This study explores the synergistic degradation mechanism of electrothermal aging and nonlinear torsion by constructing a multi-stress aging test platform in the laboratory environment. This study involved accelerated aging tests with thermal, electrothermal, and electrothermal–torsional alternating stresses. The aged cable samples were analyzed for their physical and chemical properties using differential scanning calorimetry and Fourier transform infrared spectroscopy, while dielectric spectroscopy and mechanical tests were employed to evaluate their dielectric and mechanical performance. The results indicate that torsional stress induces physical changes at the molecular level in the ethylene–propylene rubber (EPR), leading to reduced strength, hardening, and increased brittleness, resulting in decreased mechanical strength. In addition, torsional stress promotes oxidation reactions and chain scission processes in the insulation layer, reducing crystallinity and causing a decline in mechanical performance. Increased oxidation and chain scission reactions result in an increase in polar groups, leading to an increase in the dielectric loss factor of the EPR. The findings of this study provide valuable insights for the design, manufacturing, and operational monitoring of wind turbine generator output cables. [ABSTRACT FROM AUTHOR]

Currently, many utility‐scale wind turbine generator original equipment manufacturers are dependent on imported rare earth permanent magnets, which are susceptible to market risks from cost instability. To lower the production costs of these generators and stay competitive in the market, several small wind manufacturers are pursuing continuous improvements to both generator design and manufacturing. However, traditional design and manufacturing methods have yielded marginal improvements in wind power performance. This work presents novel methods to redesign a baseline 15‐kW wind turbine generator with reduced rare‐earth permanent magnets by leveraging cutting‐edge three‐dimensional (3D) printed polymer‐bonded permanent magnets and steel. Symmetric, asymmetric, and multimaterial‐magnet parametrization methods are introduced for shape optimization. We extend the symmetric and asymmetric methods to the back iron in the stator to further investigate the impact and opportunities for performance improvements with lesser active materials. We employ a design‐of‐experiments approach with parametric computer‐aided design for shape generation and evaluate different designs by magneto‐thermal modeling and finite‐element analysis. We use adaptive sampling technique to identify better performing designs with lesser magnet mass, higher efficiency, and lower cogging torque when compared with the baseline generator. Asymmetric pole designs resulted in a magnet mass in the range of 4.77–5.37 kg, which was 27%–35% lighter than the baseline generator, suggesting that a new design freedom exists that can be enabled by advanced manufacturing, such as 3D printing. Shaping the back iron in the stator resulted in material savings in electrical steel of up to 14.62 kg, which was 20% lighter than the baseline stator. We conducted a structural analysis to evaluate an optimized asymmetric rotor design from the point of view of mechanical integrity and air‐gap stiffness. The magnetically optimal shape profile was shown as having a positive impact on the radial stiffness, and an optimal solution was discovered to reduce the structural mass by nearly 30 kg, which was 29% lighter than the baseline. [ABSTRACT FROM AUTHOR]

As the utilization of wind power systems continues to increase, reducing overall system inertia, there is a consequential negative impact on the power system's ability to regulate frequency. Consequently, this study focuses on examining the fast-frequency regulation in high penetration of wind power, especially doubly fed induction generators—the most commonly installed wind turbine type, and an energy storage system installed in the wind farm. This study proposes a coordinated control of wind turbine generators and battery energy storage systems that provides fast-frequency regulation to the system while simultaneously ensuring the safety of the battery. Firstly, the fast-frequency regulation capability of the wind turbine will be studied. Secondly, primary frequency control of the battery energy storage system considering adaptive droop control based on state of charge is proposed to prevent both over-charging and over-discharging of the battery. Finally, this study proposed a coordinated fast-frequency regulation approach for the hybrid wind-storage system, which is evaluated under various wind speed scenarios. This approach involves a detailed analysis of the operational characteristics of the wind turbine generators to ensure optimal performance. The proposed method is validated through simulation using a MATLAB model of the wind-storage system, and comparative results with alternative control methods confirm the effectiveness of the proposed approach in raising the frequency nadir and avoiding the secondary frequency dip. [ABSTRACT FROM AUTHOR]

In the context of multi-criteria decision-making problems within single-valued neutrosophic set environments, this study introduces a simplified version of two similarity measures and develops two aggregation operators to synthesize results based on the proposed measure. Using a turbine generator fault diagnosis problem as a case study, we demonstrate that our proposed aggregation operators effectively generate diagnoses that align with checking reports. Additionally, we conduct a comprehensive examination of two cotangent similarity measures, investigating their properties and uncovering their inherent complexity as transformations of our proposed similarity measures. As a result, we advise researchers to avoid employing these more intricate measures. Our findings provide valuable guidance for practitioners dealing with multi-criteria decision-making problems in single-valued neutrosophic set environments. [ABSTRACT FROM AUTHOR]

Aiming at the problem that it is difficult to detect effective transient impact characteristics of wind turbine generator bearing fault signals due to non-stationary and strong noise, a fault diagnosis method based on adaptive redundant lifting wavelet dictionary and Bayesian biorthogonal sparse representation (SR) algorithm is proposed. First, a Bayesian model is integrated into the biorthogonal matching pursuit (MP) algorithm to improve the use of dictionary atoms in the effective support set. Then, an adaptive redundant lifting wavelet is used to construct a dictionary matching the transient characteristics of the signal. Finally, the SR algorithm is established by integrating the Bayesian biorthogonal MP model and adaptive redundant lifting wavelet dictionary. Simulation and experimental results show that the proposed method can improve the accuracy of signal reconstruction of transient components and effectively extract bearing fault features, thus verifying the effectiveness and robustness of the method. [ABSTRACT FROM AUTHOR]

This paper proposes a novel finite speed-set model reference adaptive system (FSS-MRAS) based on the current predictive control (CPC) of a permanent magnet synchronous generator (PMSG) in wind energy turbine systems (WETSs). The mathematical models of wind energy systems (WESs) coupled with a permanent magnet synchronous generator (PMSG) are presented in addition to the implementation of the CPC of PMSGs. The proposed FSS-MRAS is based on eliminating the tuning burden of the conventional MRAS by using a limited set of speeds of the PMSG rotor that are employed to predict the rotor speed of the generator. Consequently, the optimal speed of the rotor is the one resulting from the optimization of a proposed new cost function. Accordingly, the conventional MRAS controller is eliminated and the main disadvantage represented in the tuning burden of the constant-gain proportional-integral (PI) controller has been overcome. The proposed FSS-MRAS observer is validated using MATLAB/Simulink (R2023b) at different operating conditions. The results of the proposed FSS-MRAS have been compared with those of the conventional MRAS, which proved the high robustness and reliability of the proposed observer. [ABSTRACT FROM AUTHOR]

This paper proposes a variable-power-tracking-operation-based frequency regulation scheme for a wind turbine generator (WTG) that employs a frequency-excursion-based control parameter to suppress frequency excursion under various wind speeds and disturbances. To this end, an improved system frequency response model is built, and then the frequency regulation characteristics of the WTG are investigated. The frequency-excursion-based control parameter is determined. Simulations based on the Matlab/Simulink simulator verify the effectiveness of the proposed variable-power-tracking-operation-based frequency regulation strategy. The simulation results clearly indicate that the suggested scheme is beneficial for reducing the maximum frequency deviation. The proposed frequency regulation scheme could enhance the networking capacity of wind farms and improve the capacity of the power grid to absorb renewable energy. [ABSTRACT FROM AUTHOR]

This paper proposes a coordinated frequency regulation strategy for grid‐forming (GFM) type‐4 wind turbine (WT) and energy storage system (ESS) controlled by DC voltage synchronous control (DVSC), where the ESS consists of a battery array, enabling the power balance of WT and ESS hybrid system in both grid‐connected (GC) and stand‐alone (SA) modes. The newly developed GFM framework, i.e., DVSC, is adopted in both WT and ESS, which utilizes DC voltage dynamics for synchronization purposes. In this paper, the GC mode and SA mode are transferred by changing the status of the series‐connected switch, and it is necessary to meet the grid connection conditions when the system is transferred to the GC mode, namely, voltage, frequency, and phase sequence. For the GC mode, the inertia response from WT can be realized using the reserved energy of the DC capacitor, while the ESS serves to eliminate the steady‐state frequency deviation and reduce the DC voltage fluctuation of WT using the designed secondary frequency regulation scheme. For the SA mode, the proposed strategy can keep the power balance without external power sources. The small‐signal model of the WT and ESS hybrid system is derived. The stability analysis in both GC and SA modes is fully conducted utilizing the modal analysis method, where the impacts of control parameters on stability are assessed. The performance of the proposed strategy in a weak system is evaluated. Simulation studies are carried out under various power system contingencies to verify the effectiveness of the proposed strategy and validate the correctness of the theoretical analysis. [ABSTRACT FROM AUTHOR]

This paper investigates the use of fractional-slot concentrated windings (FSCWs) in large-scale (MW level) offshore wind generators. It focuses specifically on a power rating of 3 MW and uses an existing direct-drive synchronous PM machine (DD-SPM) with 480s/160p and dual three-phase integer-slot winding (ISW) as a baseline. A multiple of the common 12s/10p FSCW machine is used that matches the electrical frequency of the ISW machine, yielding a 192s/160p dual three-phase machine. The hybrid star–delta connection has grown increasingly popular owing to its unique harmonic cancellation properties, which can help reduce rotor and PM eddy current losses in FSCW machines. In this paper, two dual three-phase star–delta-wound machines are scaled to 3 MW and included in the investigation. Specifically, a 384s/160p dual three-phase and dual star–delta winding machine, which is a multiplication of the 24s/10p machine, and a 192s/176p dual three-phase and dual star–delta winding machine, which is a multiplication of the 24s/22p machine, are used. These machines are investigated using finite element analysis (FEA) and compared on the basis of their air-gap flux density harmonics, open-circuit electro-motive force (EMF), torque performance, and losses and power. It is found that the proposed 384s/160p dual star–delta winding machine has the best electromagnetic performance of all, with a stator power that is 1.2% greater than that of the baseline ISW machine. However, this machine has a coil pitch of 2 and so loses the manufacturing and fault-tolerant advantage of having concentrated windings. If concentrated windings are desired, then the proposed 192s/176p dual star–delta winding machine is the best choice, with the stator power only 2.6% less than that of the baseline ISW machine, but unfortunately still has significant rotor and PM eddy current losses. [ABSTRACT FROM AUTHOR]

The rotational speed of the hydraulic turbine generator set will change with the load change of the power system, therefore, the speed control system of the unit needs to adjust its operating parameters in time according to the load change. The conventional PID control algorithm is widely used in the current hydraulic turbine speed control system, but it is unable to self-tune the parameters, which makes it difficult to achieve the desired control effect. In order to solve the above problems, this paper combines the neural network and fuzzy control to optimize the PID control parameters, and through the Matlab simulation experiments, it is verified that the control described in this paper can make the hydraulic turbine speed control system have satisfactory control effects in different operating conditions. [ABSTRACT FROM AUTHOR]

Hydraulic turbine control system is a complex system with strong nonlinearity and multiple variables. Therefore, in order to better control the turbine system, it is necessary to obtain the parameters of key components. Aiming at the limitation of the traditional particle swarm optimization algorithm in global search ability, mutation operator and dynamic inertia weight coefficient are introduced to enhance the search ability of the algorithm. In addition, in order to further improve the global search performance of the algorithm, this paper combines the optimized particle swarm optimization algorithm with genetic algorithm to form a hybrid parameter identification algorithm. The hybrid algorithm not only uses the fast convergence of particle swarm optimization (PSO), but also uses the global search advantage of genetic algorithm (GA) to realize efficient and accurate identification of turbine torque and load parameters. Through MATLAB2021a/Simulink simulation experiments, the application effect of the algorithm in the identification of turbine torque and generator load parameters is verified. The simulation results show that the optimized particle swarm optimization algorithm has significant advantages in the accuracy and robustness of parameter identification, and the identified parameters have a high degree of fitting with the actual measured torque and speed. This study not only provides a new optimization strategy for the parameter identification of turbine regulation system, but also provides an effective intelligent algorithm solution for the parameter identification of nonlinear system. [ABSTRACT FROM AUTHOR]

New advances in structural optimization techniques and manufacturing methods, such as generative design (GD) and additive manufacturing (AM), are revolutionizing the capabilities to generate high-efficiency and lightweight models in comparison with conventional processes. This study addresses a structural optimization strategy for offshore wind turbine direct-drive generator structures using generative design (GD) and additive manufacturing (AM) techniques. The use of multi-objectives structural optimization processes using GD techniques allows for the exploration of a wide number of unconventional topologies on a tailored, fit-for-purpose strategy, and the implementation of AM methods makes possible the fabrication of complex designs with metallic and composite materials. GD and AM represent a revolution in the field of design optimization, offering flexibility and adaptability while collecting a vast amount of structural analysis data, crucial for a cost-effective approach in the early stages of design projects. The implementation of these techniques demonstrated over 7% weight reduction, a 40% increase in operational range, and a decrease in the cost of manufacturing. [ABSTRACT FROM AUTHOR]

This paper presents the development of a full turbine model and subsequent aero-servo-elastic simulation of the IEA 15MW Reference Wind Turbine, such that aerodynamic loads can be obtained and then applied to a simplified drivetrain in Finite-Element Analysis. This approach facilitates the quantification, through a computationally efficient method, of airgap deflections within the direct-drive generator caused by the shaft eccentricity that arises from aerodynamic loads. Shaft deflections were found to be higher under rated wind speeds than higher operating speeds, and the aero-servo-elastic model presented here performs favourably compared to later-published models. [ABSTRACT FROM AUTHOR]

The occurrence of Sub-Synchronous Resonance (SSR) phenomena can be attributed to the interaction that takes place between wind turbine generators and series-compensated transmission lines. The Doubly-Fed Induction Generator (DFIG) is widely recognized as a prevalent generator form employed in wind energy conversion systems. The present paper commences with an extensive exposition on modal analysis techniques employed in a series of compensated wind farms featuring Doubly Fed Induction Generators (DFIGs). The system model encompasses various components, including the aerodynamics of a wind turbine, an induction generator characterized by a sixth-order model, a secondorder two-mass shaft system, a series compensated transmission line described by a fourth-order model, controllers for the Rotor-Side Converter (RSC) and the Grid-Side Converter (GSC) represented by an eighth-order model, and a first-order DC-link model. The technique of eigenvalue-based SSR analysis is extensively utilized in various academic and research domains. The eigenvalue technique depends on the initial conditions of state variables to yield an accurate outcome. The non-iterative approach, previously employed for the computation of initial values of the state variables, has exhibited issues with convergence, lack of accuracy, and excessive computational time. The comparative study evaluates the time-domain simulation outcomes under different wind speeds and compensation levels, along side the eigenvalue analysis conducted using both the suggested and non-iterative methods. This comparative analysis is conducted to illustrate the proposed approach efficacy and precision. The results indicate that the eigenvalue analysis conducted using the proposed technique exhibits more accuracy, as it aligns with the findings of the simulations across all of the investigated instances. The process of validation is executed with the MATLAB program. Within the context of the investigation, it has been found that increasing compensation levels while simultaneously decreasing wind speed leads to system instability. Therefore, modifying the compensation level by the current wind speed is advisable. [ABSTRACT FROM AUTHOR]

This paper presents a case study on condition monitoring of power generators at offshore wind turbines. Two fault detection models are proposed for detecting sudden changes in the sensed value of metallic debris at the generator. The first model uses an exponentially weighted moving average, while the second monitors first-order derivatives using a fixed threshold. This is expected to improve the maintenance activities by avoiding late or early part replacement. The economic impact of the proposed approach is also provided with a realistic depiction of the cost structure associated with the corresponding maintenance plan. While the specifics of the case study are supported by real-life data, considering the prevalence of the use of generators not only in offshore wind turbines but also in other production environments, we believe the case study covered in this paper can be used as a blueprint for similar studies in other applications. • Large scale condition monitoring demonstrates economic benefits. • Case study from real wind turbine population with economic impact assessment. • Sensor for monitoring fault mode results in lead time for maintenance planning. • Sensitivity analysis assesses results despite downtime and power price uncertainty. [ABSTRACT FROM AUTHOR]

The joint probability density function of wind speed and wind direction serves as the mathematical basis for directional wind energy assessment. In this study, a nonparametric joint probability estimation system for wind velocity and direction based on copulas is proposed and empirically investigated in Inner Mongolia, China. Optimal bandwidth algorithms and transformation techniques are used to determine the nonparametric copula method. Various parameter copula models and models without considering dependency relationships are introduced and compared with this approach. The results indicate a significant advantage of employing the nonparametric copula model for fitting joint probability distributions of both wind speed and wind direction, as well as conducting correlation analyses. By utilizing the proposed KDE-COP-CV model, it becomes possible to accurately and reliably analyze how wind power density fluctuates in relation to wind direction. This study reveals the researched region possesses abundant wind resources, with the highest wind power density being highly dependent on wind direction at maximum speeds. Wind resources in selected regions of Inner Mongolia are predominantly concentrated in the northwest and west directions. These findings can contribute to improving the accuracy of micro-siting for wind farms, as well as optimizing the design and capacity of wind turbine generators. [ABSTRACT FROM AUTHOR]

Generative design techniques together with the rapid development of additive manufacturing represent a revolution in the field of structural optimisation processes. In this study, a static structural and modal analysis was integrated to drive a multi-objective generative design optimisation process for a 3 MW direct-drive offshore wind turbine electrical generator rotor structure. This novel optimisation approach implements an automated fittest-for-purpose process including a static structural analysis and a modal analysis as the input for the optimisation strategy algorithm, allowing the exploration of a wide range of non-conventional topologies. If compared with the simple generator rotor disc structure, the results obtained using this innovative method achieved over 7% of weight reduction and a 39% increment in the generator operational range with the consequent growth in the wind turbine energy capture capability. Moreover, this approach generates a vast amount of structural analysis information, crucial at an early stage of the development of large-scale projects for a cost-effective scheme. [ABSTRACT FROM AUTHOR]

The development of fault detection methods in wind turbine (WT), especially for single fault detection, is continuously increasing. However, the rapid growth of fault detection in WT leads to another challenge where multiple faults can occur. The single fault detection method in WT is no longer reliable, especially when multiple faults occur simultaneously. Therefore, multiple faults detection in doubly-fed induction generators (DFIG) WT was proposed using an artificial neural networks (ANN) model. These multiple faults include internal and external stator faults happening simultaneously. Internal stator faults cover inter-turn short circuit faults and open circuit faults, while external stator faults cover loss of excitation and external short circuit faults. The performance of the developed multiple faults detection model was measured using accuracy and the root mean square error (RMSE) value. The results show that the developed model performs well with high accuracy and a low RMSE value. Thus, the developed model can accurately detect the coexistence of multiple faults in DFIG WT. [ABSTRACT FROM AUTHOR]

This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system. [ABSTRACT FROM AUTHOR]

A small-scale experimental set-up was designed and built, consisting of a Tesla turbine and electric generator, with casing, consumer and measurement devices. Experimental measurements were carried out, regarding the working performance of the turbine at different air inlet pressures. The other parameters measured were the inlet air velocity, the rotational speed and the output electrical power. The results were discussed and explained through graphs, and conclusions were drawn. [ABSTRACT FROM AUTHOR]

In large-scale wind farms, the voltage fluctuations caused by the uncertainty of wind speed at the turbine terminals pose a pressing challenge. This article presents a localized voltage control strategy tailored toward rapid adjustments in turbine terminal voltage in wind turbine generators. Based on relative voltage observation, this strategy achieves voltage coordination between the high and low ends of the transformer in wind turbine generators. Firstly, the overall structure of the wind farm and the characteristics of terminal voltage are analyzed. Secondly, the principles and feasibility of the relative voltage control strategy are examined. Finally, the effectiveness of the proposed control strategy is validated through simulation results from a specific wind farm. The results demonstrate its capability to achieve a fast and stable voltage dynamic response within the wind farm based on local information, thus mitigating the risk of voltage out of limit. [ABSTRACT FROM AUTHOR]

This paper presents a novel multiphase hybrid matrix converter topology dedicated to grid-connected five-phase wind generation. The proposed converter, named Five-phase Ultra-Sparse Series Z-source Matrix Converter (FUSSZMC), aims to facilitate the integration of the five-phase wind turbine generators. This is done by taking into account the improvement of the injected power quality and allowing the fixed output converter voltage level to that of the grid, thanks to the use of the series Z-source, under the variable voltage magnitude of the wind turbine generator, which depends on the wind speed. The proposed space vector modulation as a control strategy for FUSSZMC was detailed, where it was demonstrated that a suitable use of both large and small current vectors improves the input current waveforms. The global model of the proposed system was tested by simulation under Matlab/Simpowersys environment. The obtained results demonstrate clearly the advantages of using FUSSZMC and its modulation strategie. These benefits includea good input and output current waveforms, as reflected by the obtained total harmonic distortion (THD) values, that fall within the range prescribed by international standards. Additionally, FUSSZMC is capable of operating with unity input power factor, regulating input voltages and improving the quality of injected power into the grid. [ABSTRACT FROM AUTHOR]