Showing papers in "Electric Power Components and Systems in 2014"
TL;DR: In this paper, a firefly algorithm is proposed for load frequency control of multi-area power systems and the optimum gains of the proportional integral/proportional integral derivative controller are optimized employing the firefly technique.
Abstract: —In this article, a firefly algorithm is proposed for load frequency control of multi-area power systems. Initially a two equal area non-reheat thermal system is considered and the optimum gains of the proportional integral/proportional integral derivative controller are optimized employing the firefly algorithm technique. The superiority of the proposed approach is demonstrated by comparing the results with some recently published techniques such as genetic algorithm, bacteria foraging optimization algorithm, differential evolution, particle swarm optimization, hybrid bacteria foraging optimization algorithm-particle swarm optimization, and Ziegler–Nichols-based controllers for the same interconnected power system. Further, the proposed approach is extended to a three-unequal-area thermal system considering generation rate constraint and governor dead-band. Investigations reveal on comparison that proportional integral derivative controller provides much better response compared to integral and p...
152 citations
TL;DR: In this paper, the authors present a review of the literature related to energy management system scheduling with respect to its control, automation, and communication, including a number of price schemes and load models needed for solving related scheduling optimization problems.
Abstract: The increasing interest in smart home technologies has created a need for a comprehensive literature survey. This article reviews the goals of a smart home energy management system, along with related definitions, applications, and information about the manufacturing of its components. The challenges associated with smart home energy management systems and possible solutions are examined, and the energy factors that contribute to a customer's electricity bill are discussed. A number of price schemes and the load models needed for solving related scheduling optimization problems are also presented, including a review of the literature related to energy management system scheduling with respect to its control, automation, and communication.
139 citations
TL;DR: In this article, a real-time energy control approach for a home energy management system, including the electric water heater, air conditioner, clothes dryer, electric vehicle, photovoltaic cell, critical loads, and battery system, is proposed to enable households to participate in demand response services.
Abstract: This article investigates a real-time energy control approach for a home energy management system, including the electric water heater, air conditioner, clothes dryer, electric vehicle, photovoltaic cell, critical loads, and battery system. A demand response mechanism is proposed to enable households to participate in demand response services. Half-hour-ahead rolling optimization and a real-time control strategy are combined to achieve household economic benefits and ability to deal with complex operating environments. A fuzzy logic controller is utilized to determine battery charging/ discharging power; proper rules are proposed to ensure benefits from operating the battery under the real-time electricity price. The simulation test results indicate that the proposed control approach can optimize the schedule for home appliances and battery charging/ discharging behavior, even if the forecasted information is not accurate. A physical test platform has also been established and tested in the lab t...
106 citations
TL;DR: In this paper, a short review of recent advancements and future development trends to support active management of distribution networks is presented, where the authors identify emerging technologies and future developments to support an active network management.
Abstract: Driven by smart distribution technologies, by the widespread use of distributed generation sources, and by the injection of new loads, such as electric vehicles, distribution networks are evolving from passive to active. The integration of distributed generation, including renewable distributed generation changes the power flow of a distribution network from unidirectional to bi-directional. The adoption of electric vehicles makes the management of distribution networks even more challenging. As such, an active network management has to be fulfilled by taking advantage of the emerging techniques of control, monitoring, protection, and communication to assist distribution network operators in an optimal manner. This article presents a short review of recent advancements and identifies emerging technologies and future development trends to support active management of distribution networks.
89 citations
TL;DR: In this paper, a local unimodal sampling optimization algorithm was proposed to obtain proportional-integral-derivative controller parameters for an automatic voltage regulator system based on a local-parameter optimization algorithm.
Abstract: —This article presents an approach for obtaining proportional–integral–derivative controller parameters for an automatic voltage regulator system based on a local unimodal sampling optimization algorithm. A conventional integral time of squared error objective function and modified objective functions in terms of integral time of absolute error, integral of absolute error, integral of squared error, peak overshoot, and settling time with appropriate weighting factors are employed to tune the controller parameters. Different objective functions are employed to obtain optimized proportional–integral–derivative controller gains. Superiority of proposed technique over some recently published modern heuristic optimization techniques, such as artificial bee colony algorithm, particle swarm optimization algorithm, and differential evolution algorithm, for the same automatic voltage regulator system is demonstrated. Simulation results reveal that the proposed proportional–integral–derivative controlled au...
87 citations
TL;DR: In this paper, the optimal placement and sizing of multiple distributed generators to achieve higher overall system reliability in large-scale primary distribution networks using a novel random search algorithm known as cat swarm optimization is presented.
Abstract: This article presents optimal placement and sizing of multiple distributed generators to achieve higher overall system reliability in large-scale primary distribution networks using a novel random search algorithm known as cat swarm optimization. A composite reliability index is used as the objective function in the optimization process. Furthermore, the effect of multiple distributed generator units on power transfer capacity and power loss reduction has been observed. Extensive simulations are carried out based on three practical distribution systems to demonstrate the effectiveness of the proposed method. Further, qualitative comparisons are made with adaptive weight particle swarm optimization, particle swarm optimization with constriction factor, and binary-coded genetic algorithm to show the efficacy of the proposed method for optimal placement and sizing of distributed generators in power distribution networks.
65 citations
TL;DR: In this article, an energy management and control study of an electric vehicle charging station is presented, which consists of an AC/DC converter for grid interface and multiple DC/DC converters for electric vehicle battery management.
Abstract: Charging infrastructure is an important component for the healthy growth of the electric vehicle industry. This article presents an energy management and control study of an electric vehicle charging station. The charging station consists of an AC/DC converter for grid interface and multiple DC/DC converters for electric vehicle battery management. For the grid-side AC/DC converter, a direct-current control mechanism is employed for reactive power, AC system bus voltage, and DC-link voltage control. For the electric vehicle-side DC/DC converters, constant current and constant voltage control mechanisms are developed for electric vehicle charging and discharging management. The article considers energy management needs for charge and discharge of multiple electric vehicles simultaneously in a dynamic price framework. A real-time simulation system is developed to evaluate how the electric vehicle charging station can meet grid-to-vehicle, vehicle-to-grid, and vehicle-to-vehicle charging and dischar...
64 citations
TL;DR: The results show that the proposed approach gives significant improvement in social welfare and decreases congestion rent with distributed generator placement.
Abstract: This article presents an effective methodology for congestion management in deregulated power system networks considering optimal placement of a distributed generator. The novelty of this method is that the optimal placement of a distributed generator in a deregulated power system is decided on the basis of bus impedance matrix (Zbus ) based contribution factors. The Zbus -based contribution factors are independent of slack bus location, which complies with the prevailing competitive environment. The congestion management problem formulation comprises the maximization of social welfare function subject to power balance and transmission congestion constraints. The maximization of the social welfare function causes maximization of consumer benefits and minimization of supplier generation cost and distributed generators. The proposed methodology has been simulated on an IEEE 30-bus system, and comparisons of results are presented with and without distributed generators. The results show that the pro...
54 citations
TL;DR: In this paper, an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using the artificial bee colony algorithm was introduced, where the objective function was adapted to enhance the overall system static voltage stability index and to achieve maximum net yearly savings.
Abstract: This article introduces an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using the artificial bee colony algorithm. The objective function is adapted to enhance the overall system static voltage stability index and to achieve maximum net yearly savings. Load variations have been considered to optimally scope the fixed and switched capacitors required. The numerical results are compared with those obtained using recent heuristic methods and show that the proposed approach is capable of generating high-grade solutions and validated viability.
54 citations
TL;DR: In this article, a new nature-inspired metaheuristic technique called the differential search algorithm is proposed to solve the optimal power flow problem, which has been developed and tested under normal and contingency power system conditions.
Abstract: —In this article, a new nature-inspired metaheuristic technique called the differential search algorithm is proposed to solve the optimal power flow problem. The proposed differential search algorithm has been developed and tested under normal and contingency power system conditions. To show the effectiveness of the proposed method, it has been demonstrated on the standard IEEE 30-bus and IEEE 118-bus test systems with different objectives that reflect performance indices of the power system. Obtained results using the proposed technique indicate that the proposed differential search algorithm provides an effective, a robust, and a high-quality solution for the optimal power flow problem. The comparisons of the proposed differential search algorithm results with those reported in the literature reveal the potential and superiority of the proposed algorithm in terms of the optimal solution quality and robustness.
51 citations
TL;DR: In this article, the authors provide an overview of the governmental policy and strategy that drives smart grid development, followed by detailed descriptions of research activities with respect to the implementation of China's smart grid vision.
Abstract: China's 12th Five-Year Plan (2011–2015) identifies smart grid development as a national priority in the energy sector. It is expected that through development of a strong smart grid across the nation, overall power grid security and efficiency can be largely improved and significant growth of relevant industrial sectors can be achieved. Consequently, different research and development programs are taking place, many of which have pilot activities involved to validate and demonstrate the technical and social–economic effectiveness of new technologies. This article gives an overview of the governmental policy and strategy that drives smart grid development, followed by detailed descriptions of research activities with respect to the implementation of China's smart grid vision. Based on the analysis and evaluation of difficulties and problems in the current system, the remaining gaps are identified for future activities to enable a smooth transition toward a strong and smart power grid in China.
TL;DR: In this article, the performance of two controllers, an H ∞ design via linear matrix inequalities and an iterative proportional-integral-derivative controller via linear matrices inequalities, is assessed to maintain frequency deviation profile in acceptable limits.
Abstract: This study considers frequency regulation in a hybrid power system consisting of conventional and distributed generation resources. The performance of two controllers—an H ∞ design via linear matrix inequalities and an iterative proportional-integral-derivative H ∞ via linear matrix inequalities—is assessed to maintain frequency deviation profile in acceptable limits. In the latter control design, the iterative linear matrix inequality approach is used to tune proportional-integral-derivative controller parameters subjected to H∞ constraints in terms of the iterative linear matrix inequality. The efficacy of the control law and disturbance accommodation properties is shown. The robustness of these controllers is demonstrated in the hybrid power system with different load disturbance conditions, wind power, and parameter variations. Controller performance is compared with a suboptimal controller to demonstrate its superiority. It is found that the second controller design has satisfactory disturba...
TL;DR: In this paper, a weighting factor optimization for reducing the torque ripple of induction machine fed by an indirect matrix converter is introduced and presented and an optimization method is adopted to calculate the optimum weighting factors corresponding to minimum torque ripple.
Abstract: —Model predictive control has emerged as a powerful control tool in the field of power converter and drive's system. In this article, a weighting factor optimization for reducing the torque ripple of induction machine fed by an indirect matrix converter is introduced and presented. Therefore, an optimization method is adopted here to calculate the optimum weighting factor corresponding to minimum torque ripple. However, model predictive torque and flux control of the induction machine with conventionally selected weighting factor is being investigated in this article and is compared with the proposed optimum weighting factor based model predictive control algorithm to reduce the torque ripples. The proposed model predictive control scheme utilizes the discrete phenomena of power converter and predicts the future nature of the system variables. For the next sampling period, model predictive method selects the optimized switching state that minimizes a cost function based on optimized weighting fact...
TL;DR: In this paper, a methodology for allocating dispatchable distributed generation units in distribution systems to economically improve system reliability is proposed, where distributed generation installation and operation costs are optimized against the reliability value, expressed as customers' willingness to pay (WTP) to avoid power interruptions.
Abstract: Recent deployment of distributed generation has led to a revolution in distribution systems and the emergence of “smart grid” concepts. The smart grid mainly intends to facilitate integration of renewable energy sources and to achieve higher system reliability and efficiency. Different distributed generation types found in modern distribution systems can be classified into two main categories: intermittent- and dispatchable-based distributed generation; the latter has a unique capability of enabling successful islanding operation, thus improving system reliability. This article proposes a methodology for allocating dispatchable distributed generation units in distribution systems to economically improve system reliability. Distributed generation installation and operation costs are to be optimized against the reliability value, expressed as customers’ “willingness to pay” (WTP) to avoid power interruptions. Therefore, the main goal of this research work is to determine the optimal combination betw...
TL;DR: In this paper, the authors presented a new islanding detection scheme based on the rate of change of impedance (dz/dt) of each phase, which is calculated using a half-cycle modified discrete Fourier transform algorithm.
Abstract: —Integration of distributed generation with utility network demands satisfactory operation of an islanding detection scheme, as it can otherwise lead to such problems such enhancement in non-detection zone, out-of-phase reclosing, personnel safety, and degradation of power quality. This article presents a new islanding detection scheme based on the rate of change of impedance (dz/dt) of each phase. To calculate dz/dt, phasor computation is carried out using a half-cycle modified discrete Fourier transform algorithm. Test data are generated using the PSCAD/EMTDC software package (HVDC Research Center, Inc., Manitoba). Various islanding conditions have been simulated by disconnecting the main circuit breaker with different values of active and reactive power mismatch. At the same time, different non-islanding conditions have also been simulated through switching (ON/OFF) of load, energization/de-energization of medium transmission lines, short-circuit on an adjacent feeder, and switching (ON/OFF) of...
TL;DR: In this paper, a MATLAB Simulink model for direct torque control with type-2 fuzzy logic control is developed to simulate the response of an induction motor drive with different operating modes.
Abstract: The conventional proportional integral controlled direct torque control of an induction motor using the space vector pulse-width modulation technique may provide satisfactory dynamic response. However, the proportional integral controller (PIC) does not provide efficient dynamic performance in the induction motor drive during sudden changes in the load or speed. To improve dynamic performance of the induction motor drive, the PICs are replaced by type-2 fuzzy logic control. The type-2 fuzzy improves the starting transient performance as well as the steady-state response. In addition, the type-2 fuzzy direct torque control provides lesser current total harmonic distortion, flux distortion, and torque pulsation of the induction motor drive compared to conventional direct torque control. A MATLAB Simulink (The MathWorks, Natick, Massachusetts, USA) model for direct torque control with type-2 fuzzy logic control is developed to simulate the response of an induction motor drive with different operating...
TL;DR: In this paper, normal behavior models are used for condition assessment of wind turbine generator systems, and health degrees are calculated based on the fitted probability density functions of the normal distribution, which is a common non-parametric estimation method.
Abstract: —This article uses normal behavior models to present an integrated approach for condition assessment of wind turbine generator systems. Monitoring parameters selected from the supervisory control and data acquisition systems of wind farms are used to establish an assessment index system. Health degree is defined to quantify indices. A neural network is used to establish normal behavior models for the parameters closely related to the natural environment. Estimation errors of the neural network models follow a normal distribution. Thus, health degrees can be calculated based on the probability density function of normal distribution. For other monitoring parameters, normal behavior models are developed based on the Parzen estimation, a common non-parametric estimation method. Health degrees are calculated based on the fitted probability density functions. Fuzzy synthetic evaluation is employed, and an assessment process is designed. Finally, the proposed method is performed on actual 1.5-MW wind tu...
TL;DR: In this paper, a multi-stage mixed-integer stochastic programming model for optimal operation of energy-efficient building systems considering controllable electric and thermal loads is presented.
Abstract: Due to the integration of volatile renewable energy and random energy consumption in the building grid, uncertainties have become a big concern for the operation of energy-efficient buildings. To minimize energy usage expenses under uncertainty, it is necessary to determine the optimal power production for a building from various energy sources, including the electric grid, battery, and combined heat and power with a boiler unit. This article presents a multi-stage mixed-integer stochastic programming model for optimal operation of energy-efficient building systems considering controllable electric and thermal loads. Taking into account the randomness of non-controllable electric and thermal loads, as well as solar power generations through the multi-stage scenario tree, the operation of energy-efficient buildings will be more robust against changes in uncertain variables. With information of uncertainties updated hourly, the rolling scheduling method is introduced to determine an adaptive power ...
TL;DR: An innovative technique for solving network reconfiguration problems with an objective of minimizing network I2R losses for an explicit set of loads is presented, and it is seen that network losses are reduced when voltage stability is enriched through network Reconfiguration.
Abstract: This article presents an innovative technique for solving network reconfiguration problems with an objective of minimizing network I2R losses for an explicit set of loads. Amid many performance standards considered for optimal network reconfiguration, voltage constraint is an important one. This problem calls for determining the best combination of feeders to be opened in the radial distribution system so it provides optimal performance in the preferred settings. In solving this problem, the gravitational search algorithm is used to reconfigure the radial distribution system; this algorithm practices an optimal pattern for sustaining the radial nature of the network at every stage of the solution, and it further allows proficient exploration of the solution space. The anticipated scheme minimizes the objective function, which has been given in the problem formulation to reduce I2R losses in addition to balancing loads in the feeders. The solution technique involves determination of the best switch...
TL;DR: In this article, the authors discuss the operational stability concerns in a smart grid with distributed generation technologies and propose a solution to solve these issues by considering the diverse characteristics of renewable energy based distributed generation technology compared to conventional power plants.
Abstract: The environmental concerns due to conventional power plants have given impetus for widespread utilization of renewable energy based distributed generation technologies. As a consequence, the concepts pertaining to a smart grid with advanced functional architecture are evolving to incorporate these technologies. Many such smart grid strategies are focused on maximum utilization of renewable energy sources compared to conventional fossil or nuclear fuels for meeting real-time load demand. The diverse characteristics of renewable energy based distributed generation technologies compared to conventional power plants have led to many operational stability concerns for the smart grid. This article discusses these stability concerns in smart grid with distributed generation technologies.
TL;DR: In this paper, the economic operation of the micro-sources employed in different topologies and the reliability of the end-users is investigated and compared with various types of microgrids in the literature.
Abstract: This article investigates and compares various types of microgrids in the literature. The comparison is concerned with the economic operation of the micro-sources employed in different topologies and the reliability of the end-users. Also, the effect of each component on the performance of the overall microgrid is discussed in detail, e.g., the individual and centralized power converters, etc. The numerical simulation of a case study shows that the single AC and three wire network microgrid types are predominant over two others, namely single DC and hybrid AC-DC networks. The AC microgrid shows its benefits in market operations, while the three-wire network takes advantage of customizing loads as its reliability preferences. The DC microgrid is the worst case, suffering from high power losses and poor reliability.
TL;DR: An improved topology for a low-speed permanent magnet vernier machine, called a dual-stator interior permanent magnet engine, is introduced to significantly increase torque density and power factor as mentioned in this paper.
Abstract: —An improved topology for a low-speed permanent magnet vernier machine, called a dual-stator interior permanent magnet vernier machine, is introduced to significantly increase torque density and power factor. A dual-stator is adopted in the design for more torque and improving space utilization. An interior spoke-type magnet array in the rotor is designed for magnet flux focusing, which can effectively increase useful flux and force flux lines to pass through the entire machine during operation as opposed to two separate torque components as in a normal dual-stator permanent magnet machine. To clearly place the advantages of the proposed topology in perspective, the proposed dual-stator interior permanent magnet vernier machine is compared to a well-known dual-stator surface-mounted permanent magnet vernier machine. This article discusses the operation principle and magnetic field analysis of the proposed machine and reports comparison simulation results taken from the finite-element method. In ad...
TL;DR: In this article, a firefly algorithm is proposed to solve the optimal power flow problem incorporating a thyristor-controlled series capacitor, which is considered to find the optimal location in transmission lines to enhance the power transfer capability of the transmission line.
Abstract: —The optimal power flow problem seeks to find an optimal profile of active and reactive power generations along with voltage magnitudes in such a manner as to minimize the total operating costs of a power system while satisfying network security constraints. This article presents a firefly algorithm to solve the optimal power flow problem incorporating a thyristor-controlled series capacitor. A thyristor-controlled series capacitor is considered to find the optimal location in transmission lines to enhance the power transfer capability of the transmission line. To assess the effectiveness of the proposed algorithm, it was tested on a 5-bus test system, an IEEE 14-bus system, and a modified IEEE 30-bus system, and it was compared with the genetic algorithm and differential evolution with and without a thyristor-controlled series capacitor. It has also been observed that the proposed algorithm can be applied to larger systems and does not suffer with computational difficulties. The results show that...
TL;DR: In this article, the secondary proportional-integral controller has been tuned using Ziegler-Nichols, genetic algorithm, and fuzzy gain scheduling methods for a multi-source multi-area hydro thermal system.
Abstract: This article describes the load frequency control of a multi-area system. Each control area contains both a hydro and thermal power plant to form a multi-source multi-area hydro thermal system. The secondary proportional-integral controller has been tuned using Ziegler–Nichols, genetic algorithm, and fuzzy gain scheduling methods. On comparing the controller performance based on various performance indices, it is found that a fuzzy gain scheduling tuned proportional-integral controller is suitable for a multi-source multi-area hydro thermal system. Further improvement on the load frequency dynamics has been achieved by connecting superconducting magnetic energy storage unit in each control area and a static synchronous series compensator unit on a tie-line.
TL;DR: Compared results shows that gene expression programming gives better results than the artificial neural network, fuzzy logic, and support vector machine with accuracy variation from 98.15 to 100%, proving the gene expression Programming method can be used in transformer fault diagnosis research.
Abstract: The diagnosis of incipient fault is important for power transformer condition monitoring. Incipient faults are monitored by conventional and artificial intelligence based models. Key gases, percentage value of gases, and ratio of the Doernenburg, Roger, IEC methods are input variables to artificial intelligence models, which affects the accuracy of incipient fault diagnosis, so selection of the most influencing relevant input variable is an important research area. With this main objective, Waikato Environment for Knowledge Analysis software is applied to 360 simulated samples having different operating lives to find the most influencing input parameters for incipient fault diagnosis in the gene expression programming model. The Waikato Environment for Knowledge Analysis identifies%C2H2,%C2H4,%CH4, C2H6/C2H2, C2H2/C2H4, CH4/H2, C2H4/C2H6, and C2H2/CH4 as the most relevant input variables in incipient fault diagnosis, and it is used for fault diagnosis using different artificial intelligence method...
TL;DR: In this paper, a new permutation-based model for power system restoration within an optimized flexible duration considering available generator capability and load prioritization is proposed, and an action-by-action flexible time schedule is obtained for generator startup.
Abstract: In the smart grid environment, a power system restoration plan with flexibility is needed to improve reliability and efficiency in an automated way. Traditional system restoration methods based on fixed time intervals may not meet the requirement. This article proposes a new permutation-based model for power system restoration within an optimized flexible duration considering available generator capability and load prioritization. By utilizing this new model, power system restoration is formulated as a permutation-based combinatorial optimization problem to maximize the restored load per unit time. Finally an action-by-action flexible time schedule is obtained for generator startup. A novel quantum-inspired evolutionary algorithm, called the quantum-inspired differential evolutionary algorithm, has been applied to solve this problem due its to high population diversity and fast convergence. The effectiveness of the proposed restoration approach has been validated using IEEE 39- and 57-bus systems.
TL;DR: In this paper, a short-term multi-objective framework for the combined heat and power economic/emission dispatch problem is proposed, where the non-linear forms of fuel cost functions and valve-point loading along with power transmission loss are considered.
Abstract: —In recent years, combined heat and power units have become significant elements in conventional power stations due their numerous merits, including operational cost savings and reduced emissions. In this regard, this article proposes a short-term multi-objective framework for the combined heat and power economic/emission dispatch problem. In addition, to more precisely model the problem, the non-linear forms of fuel cost functions and valve-point loading along with power transmission loss are considered. The objectives of the problem are total cost minimization as well as minimization of pollutant emissions; lexicographic optimization and the augmented epsilon-constraint technique are employed to solve the multi-objective problem. Also, a fuzzy decision making technique has been used to select the most preferred solution among the Pareto solutions. Afterward, a comprehensive comparison is performed between the results obtained from the proposed method and those derived from the non-dominated sort...
TL;DR: In this paper, the robust extended complex Kalman filter exploits a new weighted exponential function to handle these grid perturbations to estimate the reference signal in shunt active power filter system.
Abstract: —This article presents the design of a new shunt active power filter that employs a modified robust extended complex Kalman filter approach with an exponential robust term embedded for reference current estimation together with a current controller based on the sliding-mode control concept. The robust extended complex Kalman filter exploits a new weighted exponential function to handle these grid perturbations to estimate the reference signal in shunt active power filter system. The current controller in the proposed shunt active power filter has been designed using a sliding-mode control strategy because of its ability to handle parameter uncertainties and ease in implementation. To test the effectiveness of the proposed shunt active power filter, extensive simulations were performed using MATLAB/Simulink (The MathWorks, Natick, Massachusetts, USA), and real-time studies were made using OPAL-RT (Montreal, Quebec, Canada). Results obtained from the above studies using the proposed shunt active pow...
TL;DR: The Chebyshev neural network is presented as network-growing technique for protective classification, the single-layer structure of which is a more powerful classifier that eliminates the need for complicated network design.
Abstract: A new transmission line fault-classification algorithm based on half-cycle post-fault current data is presented for an advanced series-compensated transmission line equipped with a thyristor-controlled series compensator. The proposed scheme was developed with the signal feature enhancement tool of discrete wavelet packet entropy measures. The Chebyshev neural network is presented as network-growing technique for protective classification, the single-layer structure of which is a more powerful classifier that eliminates the need for complicated network design. A comparative implementation study of the multi-layer perceptron and Chebyshev neural network authenticates benefits gained by the Chebyshev neural network. To demonstrate the advantage gained by Chebyshev neural networks compared to support vector machines, a comparative study is presented with a support vector machine based classification technique. The fault datawere obtained by dynamic simulation of a sample system using the real-time po...
TL;DR: In this paper, a three-mass shaft model based on small-signal stability analysis is used to study the wind turbine shaft torsional vibration, and the model includes the mechanical system and electrical system.
Abstract: —One critical task in wind turbine shaft torsional vibration study involves the modeling of a wind turbine and power grid. With a focus on the mechanical rotational system of wind turbine, this article provides a three-mass shaft model upon which one wind turbine to infinite bus model can be developed. The model, based on small-signal stability analysis, is used to study the wind turbine shaft torsional vibration. For this reason, this article concentrates on the union model of stall wind turbine and power grid. The small-signal stability model includes the mechanical system and electrical system. Data for the turbine's blades and shaft as well as electrical generator are given to allow replication of the model in its entirety. Each of the component blocks of the wind turbine and power grid is modeled separately so that one can easily expand and modify the model to simulate variable-speed wind turbines or multi-turbines system to suit their needs. This is then followed by a case study that explain...