Search

The recently stipulated grid codes require wind generators to re-initiate normal power production after grid voltage sag. This paper presents a comparative performance of two commonly employed variable speed wind turbines in today's electricity market, the doubly fed induction generator (DFIG) and the permanent magnet synchronous generator (PMSG) wind turbines. The evaluation of both wind turbines was performed for weak, normal and strong grids, considering the same machine ratings of the wind turbines. Because of the critical situations of the wind turbines during faulty conditions in the weak grids, an analysis was done considering the use of effective series dynamic braking resistor (SDBR) for both wind turbines. The grid voltage variable was employed as the signal for switching the SDBR in both wind turbines during transient state. Additionally, an overvoltage protection system was considered for both wind turbines using the DC chopper in the DC-link excitation circuitry of both wind turbines. Furthermore, a combination of the SDBR over-voltage protection scheme (OVPS) was employed in both wind turbines at weak grid condition in order to improve the performance of the variable speed wind turbines and keep the operation of the power converters within their permissible limits. Furthermore, the performance of the DFIG and PMSG wind turbines in weak grids were further investigated, considering the combination of 75% and 50% effectively sized SDBR and OVPS. It was observed that, even with a 50% reduction in SDBR or OVPS, the performance of both wind turbines is still satisfactory with faulty conditions. Therefore, it is recommended to use a combination of the SDBR and OVPS with DFIG- or PMSG-based variable speed wind turbines to achieve a superior fault ride through performance, especially in weak grids. The system performance was evaluated using the power system computer design and electromagnetic transient including DC (PSCAD/EMTDC) platform. [ABSTRACT FROM AUTHOR]

Concerning the power quality issues in the power distribution network due to load uncertainties and improper impedance matching of the inductances, deep reinforced learning (DRL)-based inductively coupled DSTATCOM (IC-DSTATCOM) is proposed. First, by analyzing the impedance matching principle, the expression of source, load and filter current is derived with the help of inductive filtering transformer. And second, an individual DRL subnet structure is accumulated for each phase using mathematical equations to perform the better dynamic response. A 10-kVA, 230-V, 50-Hz prototype direct coupled distributed static compensator (DC-DSTATCOM) and IC-DSTATCOM experimental setup is buit to verify the experimental performance under uncertainties of loading. The IC-DSTATCOM is augmented better dynamic performance in terms of harmonics curtailment, improvement in power factor, load balancing, potential regulation, etc. The benchmark IEEE-519-2017, IEC-61727 and IEC-61000-1 grid code are used to evaluate the effectiveness of the simulation and experimental study. [ABSTRACT FROM AUTHOR]

This article focuses on the implementation of peer-to-peer (P2P) energy trading and planning of a grid-connected multi-microgrid system based on an advanced optimization approach. The proposed architecture is comprised of three microgrids (MGs) with combinations of distributed energy resources (DERs), including wind turbines, photovoltaic panels, and storage batteries, to meet the load requirement. A game theory technique, Nash equilibrium, is used to structure the proposed model for multiobjective optimization, where the main objectives are used to determine the correct sizing of DERs and optimum payoff values. Due to the variability of DERs, to maintain lower energy costs, the reliability index (IR) and levelized cost of energy are the benchmarks considered for optimization. The proposed model is analyzed, and rigorous comparison is carried out for both peer-to-grid and P2P energy trading schemes, considering the Australian profiles for wind speed, solar irradiation, and residential load. The simulation model is built in MATLAB software, and the particle swarm optimization algorithm is exploited for the optimization. The results illustrate that P2P energy trading reduces the payoff value of the multiobjective function (MOF) to 36%. The robustness of MOF is validated and analyzed with different combinations of constant coefficients K1 and K2. In the end, the most economical and suitable models with DERs are proposed for each MG, and the results are verified with sensitivity analysis. [ABSTRACT FROM AUTHOR]

In this paper, a multi‐objective optimization technique is proposed for the planning of a networked microgrid based on peer‐to‐grid (P2G) and peer‐to‐peer (P2P) energy trading schemes. Two different criteria's including annual profit and energy index of reliability are taken into consideration to form a multi‐objective function. The networked microgrid consists of three individual microgrids containing their own combinations of generation resources, batteries and residential loads. All microgrids are connected together and also to the main grid to meet the energy exchange requirements of P2P energy trading. A cooperative game theory technique based on a particle swarm optimization algorithm is used to model the networked microgrid, and to find the suitable sizes of the players that simultaneously maximize the payoff values of both objective functions. Besides, a comparative analysis is carried out for both P2G and P2P energy trading schemes. The results show that the outcomes are maximum when both criteria are considered in the optimization and P2P energy trading is carried out. The sensitivity analysis is performed on the selected parameters and verified the right change 0.003% and 4.5% in discount rate and electricity prices, respectively. [ABSTRACT FROM AUTHOR]

Summary: With the recent proliferation and penetration of wind farms into existing power grids, it is paramount to conduct numerous studies to counter grid disturbances based on operational grid codes. One of the ways of generating electric power from wind energy is by employing the promising technology of the permanent magnet synchronous generator (PMSG) wind turbine. In order to solve the transient stability intricacies posed by the stochastic nature of wind energy during grid faults, this paper proposes a fault current limiter for a PMSG‐based wind turbine control. The fault current limiter used in this study is a series dynamic braking resistor (SDBR). The best location to place the SDBR on the machine‐side and grid‐side converters (GSCs) of the wind generator was investigated, considering the grid voltage as its switching signal during transient state. Efforts have been given to find a suitable sizing of the SDBR. The performance of the SDBR has been investigated at various network strengths in weak and strong grids. A severe three‐line‐to‐ground fault and asymmetrical faults were used to test the robustness and rigidity of the controllers of the wind generator. The system performance was evaluated using power system computer aided design and electromagnetic transient including DC (PSCAD/EMTDC) platform. The same conditions of operation were used in investigating the various scenarios considered in this study, for effective comparison. [ABSTRACT FROM AUTHOR]

This paper discusses the impact of small dc capacitance in a motor drive using a floating capacitor H-bridge topology. The proposed topology is intended for applications where variable frequency control is not required. Special attention is paid on investigating the second-order dc capacitor voltage ripples, whose influence on the induction motor as well as on the motor drive itself is of importance. This issue is addressed in this paper through rigorous mathematical formulations. It is found that by inverting the second-order dc ripple voltage using the conventional SVPWM, no harmful harmonics will be generated in the motor line voltage. This demonstrates the possibility of drastically reducing the dc capacitance of the proposed system. Induction motor as well as H-bridge performance with respect to different dc capacitance values is demonstrated by experiments, which lays the foundation for cost reduction and reliability enhancement of the proposed system. [ABSTRACT FROM PUBLISHER]

This paper presents a robust continuous nonlinear model predictive control (CNMPC) for a grid-connected photovoltaic (PV) inverter system. The objective of the proposed approach is to control the power exchange between the grid and a PV system, while achieving unity power factor operation. As the continuous nonlinear MPC cannot completely remove the steady-state error in the presence of disturbances, the nonlinear disturbance observer-based control is adopted to estimate the offset caused by parametric uncertainties and external perturbation. The stability of the closed-loop system under both nonlinear predictive control and disturbance observer is ensured by convergence of the output-tracking error to the origin. The proposed control strategy is verified using a complete laboratory-scale PV test-bed system consisting of a PV emulator, a boost converter, and a grid-tied inverter. High performance with respect to dc-link voltage tracking, grid current control, disturbance rejection, and unity power factor operation has been demonstrated. [ABSTRACT FROM PUBLISHER]

This study presents a novel adaptive control scheme for variable-speed wind turbine (VSWT) driven permanent magnet synchronous generator (PMSG) to ensure its operation under different operating conditions. The adaptive control scheme is based on the affine projection algorithm (APA) which provides a faster convergence and less computational complexity than the least-mean-square algorithm. The proposed adaptive controller is used to control both the generator-side converter and the grid-side inverter without giving additional tuning efforts. Each vector control scheme for the converter/inverter has four APA-based adaptive proportional-integral (PI) controllers. Detailed modelling and the control strategies of the system under study are demonstrated. Real wind speed data extracted from Hokkaido island, Japan is used in this study. The dynamic characteristics of a grid-connected VSWT-PMSG are investigated in details to ensure the proposed controller operation under different operating conditions. The effectiveness of the proposed adaptive controller is compared with that obtained using optimised PI controllers by Taguchi method. The validity of the adaptive vector control scheme is verified by the simulation results which are performed using PSCAD/EMTDC environment. [ABSTRACT FROM AUTHOR]

Abstract— This article presents a novel application of the particle swarm optimization technique to optimally design all the proportional–integral controllers required to control both the real and reactive powers of the superconducting magnetic energy storage unit for enhancing the low-voltage ride-through capability of a grid-connected wind farm. The control strategy of the superconducting magnetic energy storage system is based on a sinusoidal pulse-width modulation voltage source converter and proportional–integral-controlled DC-DC converter. Control of the voltage source converter depends on the cascaded proportional–integral control scheme. All proportional–integral controllers in the superconducting magnetic energy storage system are optimally designed by the particle swarm optimization technique. The statistical response surface methodology is used to build the mathematical model of the voltage responses at the point of common coupling in terms of the proportional–integral controller parameters. The effectiveness of the proportional–integral-controlled superconducting magnetic energy storage optimized by the proposed particle swarm optimization technique is then compared to that optimized by a genetic algorithm technique, taking into consideration symmetrical and unsymmetrical fault conditions. A two-mass drive train model is used for the wind turbine generator system because of its large influence on the fault analyses. The systemic design approach is demonstrated in determining the controller parameters of the superconducting magnetic energy storage unit, and its effectiveness is validated in augmenting the low-voltage ride-through of a grid-connected wind farm. [ABSTRACT FROM PUBLISHER]

Partial discharge is one of the main reasons for insulation degradation in high‐voltage apparatuses. Partial discharge is an ineluctable phenomenon that happens when a high electrical field is adjacent to an insulator. High‐frequency current transformers are widely used for detecting partial discharge current in high‐voltage equipment. Determination of the apparent charge in pico coulombs is essential for having a common understanding of results and verifying that the measuring system can obtain specified partial discharge magnitude correctly. To this end, a high‐frequency current transformer sensor and a partial discharge calibrator have been prepared to measure the current of the partial discharge (PD) pulses inside mineral oil. The constructed PD calibrator has been evaluated. The high‐frequency current transformer (HFCT) sensor has been simulated using a mathematical model‐based AC analysis and has been characterized and then calibrated using a calibration technique to measure the apparent charge of the PD pulses. Experimental results show the effectiveness of the HFCT sensor and the proposed calibration method. [ABSTRACT FROM AUTHOR]

This study aims at resolving a specific problem in the area of renewable energy, energy storage systems, variable-speed drives, and flexible AC transmission system (FACTS) devices used in the electric power systems. The use of power conversion system (PCS) is very common in the aforementioned areas. A cascaded control scheme based on four proportional-integral (PI) controllers is widely used in the control of the PCS unit. Setting the parameters of the four cascaded PI controllers simultaneously is cumbersome, especially when the application is in the area of electrical power system which is difficult to express using a mathematical model or transfer function due to its nonlinear properties. This paper presents an optimum design procedure for the cascaded controller of the PCS unit using Taguchi method. To apply the design parameters obtained from Taguchi method, a renewable energy application is chosen where a variable-speed wind turbine generator system is connected to the power grid through two back-to-back PCS units. The effectiveness of the designed parameters using Taguchi method is then compared with that obtained using response surface methodology and genetic algorithm (RSM-GA) method under the grid fault condition. [ABSTRACT FROM PUBLISHER]

In this article, stabilization methods of wind farms composed of fixed-speed wind turbines and variable-speed wind turbines are analyzed. A current-controlled voltage source converter scheme for a variable-speed wind turbine driving doubly fed induction generator is proposed. The proposed scheme is then compared with two other doubly fed induction generator control schemes to show the effectiveness of the proposed controller. Different types of symmetrical and unsymmetrical faults are analyzed considering wind farm recent grid codes. Though all of the schemes are able to stabilize the wind farms during transient conditions, the proposed current-controlled voltage source converter scheme offers the advantage of less intricacy of controller design, better performance during grid fault, and omission of DC-link protection scheme, which can reduce the overall cost of the system. Moreover, extensive simulation analyses by using PSCAD/EMTDC (Manitoba HVDC Research Center, Manitoba, Canada) are performed to determine the optimum amount of the fixed-speed wind turbine system that can be stabilized by variable-speed wind turbine system. [ABSTRACT FROM PUBLISHER]

This paper presents a new operational strategy for a small scale wind farm which is composed of both fixed and variable speed wind turbine generator systems (WTGS). Fixed speed wind generators suffer greatly from meeting the requirements of new wind farm grid code, because they are largely dependent on reactive power. Integration of flexible ac transmission systems (FACTS) devices is a solution to overcome that problem, though it definitely increases the overall cost. Therefore, in this paper, we focuses on a new wind farm topology, where series or parallel connected fixed speed WTGSs are installed with variable speed wind turbine (VSWT) driven permanent magnet synchronous generators (PMSG). VSWT-PMSG uses a fully controlled frequency converter for grid interfacing and it has abilities to control its reactive power as well as to provide maximum power to the grid. Suitable control strategy is developed in this paper for the multilevel frequency converter of VSWT-PMSG. A real grid code defined in the power system is considered to analyze the low voltage ride through (LVRT) characteristic of both fixed and variable speed WTGSs. Moreover, dynamic performance of the system is also evaluated using real wind speed data. Simulation results clearly show that the proposed topology can be a cost effective solution to augment the LVRT requirement as well as to minimize voltage fluctuation of both fixed and variable speed WTGSs. [ABSTRACT FROM AUTHOR]

This paper presents a system using an energy capacitor system (ECS) to smoothen the output power fluctuation of a variable-speed wind farm. The variable-speed wind turbine driving a permanent-magnet synchronous generator is considered to be connected to the ac network through a fully controlled frequency converter. The detailed modeling and control strategy of the frequency converter as well as variable-speed operation of a wind turbine generator system are demonstrated. Afterward, a suitable and economical topology of ECS composed of a current-controlled voltage-source inverter, dc-dc buck/boost converter, and an electric double layer capacitor (EDLC) bank is presented, including their control strategies. Exponential moving average is used to generate the real input power reference of ECS. Another novel feature of this paper is the incorporation of a fuzzy-logic-controlled reference signal adjuster in the control of the dc-dc buck/boost converter, in which the stored energy of the EDLC bank is utilized in an efficient way. Due to this controller, the energy storage capacity of the EDLC bank can be reduced in size, thus resulting in reduction of the overall cost of the ECS unit as well as decrease in irrepressible operations during high and low energy levels of the EDLC bank. Finally, extensive simulation results are presented that validate the effectiveness of the proposed system to smoothen the output power fluctuation of the variable-speed wind farm. [ABSTRACT FROM AUTHOR]

In this work, dynamic and transient characteristics of a multimachine power system connected with two wind farms composed of fixed speed wind turbine generator systems (WTGS) are analyzed. At each wind farm the terminal one space vector pulse width modulation controlled voltage source converter based static synchronous compensator (STATCOM) is considered to be connected. The capacitor bank capacity of fixed speed wind generator is reduced by certain percentages when a STATCOM is integrated at a wind farm terminal. As wind speed is always fluctuating, the terminal voltage of a fixed speed wind generator also fluctuates randomly, which has an adverse effect on the rest of the power system. It is reported that the STATCOM with a reduced capacitor bank can decrease the voltage fluctuations of the multimachine power system as well as wind generator terminals. Moreover, it is shown that a STATCOM can also enhance the transient stability of induction and synchronous generators when a network disturbance occurs in the power system. Since shaft system modeling of a wind turbine has a significant effect on the transient stability analysis of WTGS, a two-mass shaft model is adopted in this study. Both of the symmetrical and the unsymmetrical faults are analyzed in light of the real wind farm grid code. The transient performance of a STATCOM on the network is evaluated by the transient stability index based on the total kinetic energy of generators. For dynamic performance evaluation, real wind speed data are used in the simulation. Finally, it is concluded that the STATCOM can enhance both dynamic and transient stability of wind farms connected with a multimachine power system. [ABSTRACT FROM AUTHOR]

This paper presents a new method to enhance the transient stability of multimachine power system including wind farms, when a severe network disturbance occurs in the power system. For this purpose, the energy capacitor system (ECS) composed of power electronic devices and electric double layer capacitor (EDLC) is proposed. The control scheme of ECS is based on a sinusoidal PWM voltage source converter (VSC) and fuzzy logic controlled dc-dc buck/boost converter using insulated gate bipolar transistors (IGBT). Two wind farms are considered to be connected to the power system. Two-mass drive train model of wind turbine generator system (WTGS) is used in the analyses as the drive train modeling has great influence on the dynamic characteristics of WTGS. Real wind speed data are used in the analyses to obtain realistic responses. Different types of symmetrical and unsymmetrical faults are considered as the network disturbance. Simulation results clearly show that the proposed ECS can enhance the transient stability of wind generators in multimachine power system as well as their low voltage ride through (LVRT) capability. [ABSTRACT FROM AUTHOR]

In this article, the blade and shaft torsional oscillations of wind turbine generator system (WTGS) when a network disturbance occurs in the power system are analyzed. Several reports are available in the literature, where the damping of shaft torsional oscillations of steam turbine generator system is discussed. Though a huge number of wind generators are going to be connected with the existing network, the damping of blade-shaft torsional oscillations of WTGS has so far not been reported. In this work, for the damping of blade-shaft torsional oscillations of WTGS, the voltage source converter (VSC) based three-level STATCOM is proposed. The six-mass drive train model of WTGS is used for the sake of precise analysis. Moreover, the damping of blade-shaft torsional oscillations of WTGS by using pitch controller is analyzed also, since a pitch controller is attached with most of the recent wind turbines. Both symmetrical and unsymmetrical faults are considered as the network disturbances. Simulation results clearly show that the pitch controller can somewhat, and the STATCOM can significantly, decrease the blade and shaft torsional oscillations of WTGS, where the simulations have been done by PSCAD/EMTDC. [ABSTRACT FROM AUTHOR]

In order to investigate the impacts of the integration of wind farms into utilities networks, it is necessary to analyze the transient characteristic of wind turbine generator system (WTGS). In most of the cases, the simple one mass lumped model is considered for stability analysis of wind generator. It is not analyzed yet which order shaft model is sufficient for transient stability analysis of WTGS. In this study, a detailed transient analysis has been done with the consideration of two mass and three mass shaft models of WTGS. Finally, it is concluded that two mass shaft model is sufficient enough for transient stability analysis of grid connected WTGS. [ABSTRACT FROM AUTHOR]

The rapid introduction of electric vehicles (EVs) in the transportation market has initiated the concept of vehicle-to-grid (V2G) technology in smart grids. However, where V2G technology is intended to facilitate the power grid ancillary services, it could also have an adverse effect on the aging of battery packs in EVs. This is due to the instant depletion of power during the charge and discharge cycles, which could eventually impact the structural complexity and electrochemical operations in the battery pack. To address this situation, a median expectation-based regression approach is proposed for parameter estimation of vehicle batteries in V2G systems. The proposed method is built on the property of uncertainty prediction of Gaussian processes for parameter estimation while considering the cell variations as an exogenous function. First, a median expectation-based Gaussian process model is derived to predict the fused and individual cell variations of a battery pack. Second, a magnitude-squared coherence model is developed by the error matrix to detect and isolate each variation. This is obtained by extracting the cross-spectral densities for the measurements. The proposed regression-based approach is evaluated using experimental measurements collected from lithium-ion battery pack in EVs. The parametric analysis of the battery pack has been verified using D-SAT Chroma 8000ATS hardware platform. Performance evaluation shows an accurate estimation of these dynamics even in the presence of injected faults. [ABSTRACT FROM AUTHOR]

The electrification of transportation has been developed to support energy efficiency and CO2 reduction. As a result, electric vehicles (EVs) have become more popular in the current transport system to create more efficient energy. In recent years, this increase in EVs as well as renewable energy resources (RERs) has led to a major issue for power system networks. This paper studies electrical vehicles (EVs) and their applications in the smart grid and provides practical solutions for EV charging strategies in a smart power system to overcome the issues associated with large-scale EV penetrations. The research first reviews the EV battery infrastructure and charging strategies and introduces the main impacts of uncontrolled charging on the power grid. Then, it provides a practical overview of the existing and future solutions to manage the large-scale integration of EVs into the network. The simulation results for two controlled strategies of maximum sensitivity selection (MSS) and genetic algorithm (GA) optimization are presented and reviewed. A comparative analysis was performed to prove the application and validity of the solution approaches. This also helps researchers with the application of the optimization approaches on EV charging strategies. These two algorithms were implemented on a modified IEEE 23 kV medium voltage distribution system with switched shunt capacitors (SSCs) and a low voltage residential network, including EVs and nonlinear EV battery chargers. [ABSTRACT FROM AUTHOR]

In this paper, two techniques of game theory are considered for sizing and comparative analysis of a grid-connected networked microgrid, based on a multi-objective imperialistic competition algorithm (ICA) for system optimization. The selected networked microgrid, which consists of two different grid-connected microgrids with common electrical load and main grid, might have different combinations of generation resources including wind turbine, photovoltaic panels, and batteries. The game theory technique of Nash equilibrium is developed to perform the effective sizing of the networked microgrid in which capacities of the generation resources and batteries are considered as players and annual profit as payoff. In order to meet the equilibrium point and the optimum sizes of generation resources, all possible coalitions between the players are considered; ICA, which is frequently used in optimization applications, is implemented using MATLAB software. Both techniques of game theory, Shapley values and Nash equilibrium, are used to find the annual profit of each microgrid, and results are compared based on optimum sizing, and maximum values of annual profit are identified. Finally, in order to validate the results of the networked microgrid, the sensitivity analysis is studied to examine the impact of electricity price and discount rates on maximum values of profit for both game theory techniques. [ABSTRACT FROM AUTHOR]

Although the use of a series capacitor increases the transmission line (TL) capacity, it inverts the voltage/current and creates a sub-harmonic frequency that results in unintended operation of the protection devices, which further decreases the transient stability under fault conditions. Restoring the transient stability requires an accurate diagnosis of faults in TLs, which further requires exploration of in-depth features. This imposes challenges for the existing approaches as they demand a large amount of data. In this paper, a self-attentive weight-sharing capsule network (WSCN) is proposed to achieve robust and high classification performance while utilizing a limited amount of data. The capsule network, with the weight-sharing mechanism delivers robust performance in detecting and classifying the faults in the TL domain. Simultaneously, the self-attention layer highlights the more dominant features that make the network work upon the limited data effectively. A Western-System-Coordinating-Council WSCC 9-bus and 3-machine test model, which was modified with the series capacitor was studied to quantify the robustness of the self-attention WSCN. The results were compared with those of others networks to confirm the explicit classification ability of the proposed network. A study on real-world data obtained from power network was also conducted to validate the proposed self-attention WSCN. [ABSTRACT FROM AUTHOR]

Data-driven condition monitoring reduces downtime of wind turbines and increases reliability. Wind turbine operation and maintenance (O&M) cost is a significant factor that calls for automated fault detection systems in wind turbines. In this manuscript, the anomaly detection problem for wind turbine gearbox is formulated based on adaptive threshold and twin support vector machine (TWSVM). In this work, SCADA data from wind farms located in the U.K. is considered with samples from twelve months before failure, and from one month before failure. Gearbox oil and bearing temperatures are used as two univariate time-series for analyzing adaptive threshold. The effectiveness of the proposed method is compared with standard classifiers like support vector machines (SVM), k-nearest neighbors (KNN), multi-layer perceptron neural network (MLPNN), and decision tree (DT). Anomaly detection of wind turbine gearbox using TWSVM and adaptive threshold results in an accurate performance, thus increasing the reliability. The missed failure and false positive rate that indicate the proposed methodology’s ability is also investigated to discriminate between false alarms, and comparison with previous studies shows superior performance. [ABSTRACT FROM AUTHOR]

The significant penetration of renewable energy resources and ever-rising load demand has gradually aggravated the safe operation of the interconnected power system. A generalized extended state observer and fractional-order theory based integral sliding mode control strategy is introduced in the interconnected power system to minimize the frequency deviation by controlling the governor of the generation unit. The generalized extended state observer is designed to estimate the disturbance from system uncertainty, load demand, and wind power fluctuation to improve the robustness of the interconnected power system. The fractional-order integral sliding mode control relieves the chattering of frequency deviation and tie-line power deviation. Besides, the superconducting magnetic energy storage and the wind model, as the ancillary frequency regulation devices, are implemented in the interconnected power system. The novel sliding mode controller based on generalized extended state observer is designed for the interconnected power system with the addition of the superconducting magnetic energy storage and the wind model. Stability proof and simulation comparison with the integer-order sliding mode control and other three control schemes are carried out as well. [ABSTRACT FROM AUTHOR]

Summary: Modern‐day hybrid wind farm operation is fundamentally dependent on the accuracy of short‐term wind power forecasts. However, the inevitable error in wind power forecasting limits the power transfer capability to the utility grid, which calls for battery energy storage systems to furnish the deficit power. This manuscript addresses a wind forecasting based penalty cost minimization solution for hybrid wind‐battery farms. We choose six wind farm sites (three offshore and the other three onshore) to study machine intelligent forecasting based solutions and compare the performance of a wavelet‐Twin support vector regression (TSVR) based wind power forecasting model with ε‐Twin support vector regression, Random forest, and Gradient boosted machines, for penalty cost minimization. We access the penalties that arise as power imbalances along with the battery system's cost. We find that TSVR based wind power forecasting method results in a minimum global operational cost for all the wind farm sites under study. [ABSTRACT FROM AUTHOR]

At present, fossil fuel-based power generation systems are reducing drastically because of their less availability in nature. In addition, it produces hazardous gasses and high environmental pollution. So, in this work, the solar natural source is selected for generating the electricity. Due to the nonlinear behavior of PV, achieving maximum voltage from the Photovoltaic (PV) system is a more tough job. In this work, various hybrid optimization controllers are studied for tracing the working power point of the PV under different Partial Shading Conditions. The studied hybrid optimization MPPT methods are equated in terms of oscillations across MPP, output power extraction, settling time of the MPP, dependency on the PV modeling, operating duty value of the converter, error finding accuracy of MPPT, algorithm complexity, tracking speed, periodic tuning required, and the number of sensing parameters utilized. Based on the simulative comparison results, it has been observed that the modified Grey Wolf Optimization based ANFIS hybrid MPPT method provides good results when equated with the other power point tracking techniques. Here, the conventional converter helps increase the PV source voltage from one level to another level. The proposed system is investigated by using the MATLAB/Simulink tool. [ABSTRACT FROM AUTHOR]

Due to the non-renewable nature and pollution associated with fossil fuels, there is widespread research into alternative energy sources. As a novel energy device, a proton exchange membrane fuel cell (PEMFC) is considered a promising candidate for transportation due to its advantages, including zero carbon emissions, low noise, and high energy density. However, the commercialization of fuel cells faces a significant challenge related to aging and performance degradation during operation. In order to comprehensively address the issue of fuel cell aging and performance decline, this paper provides a detailed review of aging mechanisms and influencing factors from the perspectives of both the PEMFC system and the stack. On this basis, this paper offers targeted solutions to degradation issues stemming from various aging factors and presents research on aging prediction methods to proactively mitigate aging-related problems. Furthermore, to enhance prediction accuracy, this paper categorizes and analyzes the degradation index and accuracy evaluation criteria commonly employed in the existing fuel cell aging research. The results indicate that specific factors leading to aging-related failures are often addressed via targeted solving methods, corresponding to specific degradation indexes. The significance of this study lies in the following aspects: (1) investigating the aging factors in fuel cells and elucidating the multiple aging mechanisms occurring within fuel cells; (2) proposing preventive measures, solutions, and aging prediction methods tailored to address fuel cell aging issues comprehensively, thereby mitigating potential harm; and (3) summarizing the degradation index and accuracy evaluation standards for aging prediction, offering new perspectives for resolving fuel cell aging problems. [ABSTRACT FROM AUTHOR]

This paper proposes a robust control scheme to involve the distributed Battery Energy Storage Systems (BESSs) in Load Frequency Control (LFC) through BESS aggregators with sparse communication networks. In order to cope with the uncertainties associated with system operation, a two-layer Model Predictive Control (MPC) is developed so that more efficient control signals are provided to improve the response of BESSs to make larger contribution to the LFC. The outer layer in the proposed structure produces the command signal for the aggregator based on signals which are produced by the inner layer as well as the signal provided from the actual system. These command signals are provided so as to achieve the least value of error in Area Control Error (ACE) with a minimum control effort taking a variety of operational and physical constraints into consideration. Optimization procedures are also carried out to compute the optimal value of weighting coefficients contained in the objective functions. The capability of controller to cope with uncertainties is compared with a conventional single-layer MPC. In addition, the delay caused by propagation channels in delivering control signals to BESSs is modeled, and its impact on the performance of frequency regulation is evaluated. An intelligent fuzzy coordination control is then developed to coordinate the BESS aggregator and conventional power plants to avoid extra power injection/withdrawal by the conventional power plants in case of long delays. Case studies are conducted to illustrate the effectiveness of the proposed structure in controlling distributed BESSs with diverse energy capacities, rated powers, charging/discharging coefficients and time constants; and State of Charges (SoCs). [ABSTRACT FROM AUTHOR]

This paper proposes a generalized 3-phase cascaded multilevel inverter (CMLI) along with a simplified space vector pulse width modulation (SVPWM) based on 2-level inverter (2LI) topology. While conventional cascaded H-bridge inverters (CHBIs) call for a number of DC sources which increase the cost and complexity of their implementation, the proposed CMLI requires one DC source only. On the other hand, the complexity of SVPWM lies in the switching diagram that consists of a large number of triangles comprising uneven numbers of switching vectors. The generalized 3-phase CMLI proposed in this paper is aimed at reducing the number of switching vectors of each triangle. The hypothesis of the proposed CMLI-SVPWM is firstly illustrated through extensive simulation analysis using MATLAB/SIMULINK software. Feasibility of the proposed inverter is then validated through experimental measurements on a hardware prototype. Results reveal the superiority of the proposed inverter over existing ones in terms of the quality of the output voltage and current waveforms and the overall efficiency. [ABSTRACT FROM AUTHOR]

To provide continuity of balancing demand and generation, renewable sources will be more active than today in near future due to the tendency of massive investment on renewable energy sources (RESs) by countries. However, due to the uncertain and intermittent nature of RESs, RESs would create problems on power system operations such as power quality, efficiency, stability and reliability. Owing to having problems with RESs integration, virtual power plant (VPP) has introduced to make this integration smooth without compromising the grid stability and reliability along with offering many other technoeconomic benefits. This study reviews structures, types, architecture and operations of VPP along with the status of present implementations worldwide. The types of VPP are introduced in details with the optimisation algorithm used with each type. In addition, VPP is linked with the most of the components in power systems such as distributed generation, active prosumers, transmission system operator and distribution system operator, grid services such as fault ride through, reactive power control as well as with the help of technology such as communications, control and optimisations. This study gives a comprehensive outline of transforming microgrid to VPP that is useful for researchers, consumers, prosumers and utility operators. [ABSTRACT FROM AUTHOR]

Electrical vehicles (EVs) enjoying the new technology known as vehicle-to-grid have presented new opportunities to control and planning of power grids. Bidirectional connection capability of converters in EVs' structure makes them a secure backup for frequency support. This paper applies EVs as one of the foremost controllable loads along with other conventional generation units for frequency control after disturbances in a multi-area power system. Application of tilt-integral-derivative (TID) controller for EVs has been addressed for the first time in this paper. In this regard, artificial bee colony optimization algorithm is employed for optimal tuning parameters of TID controllers in EV and automatic generation control structures. In order to achieve accurate and realistic results, physical limitations of generation rate constraint, non-linearity, and governor dead-band effect are included in the analysis. Eventually, three scenarios including step and random load changes, and sensitivity analysis are selected to illustrate the efficiency of the proposed coordinated control in terms of settling time, peak time, peak overshoot, and the integral of time multiplied squared error performance index in frequency and tie-line power deviations. The results are compared with particle swarm optimization and genetic algorithm based TID controllers. [ABSTRACT FROM AUTHOR]

This paper proposes a novel unified expandable low switch power electronic converter architecture for grid integration of direct drive variable speed wind turbine (VSWT) system using permanent magnet synchronous generator (PMSG). The proposed unified expandable power converter can interface two or more bidirectional output ports, such as wind generators, energy storages, and grid. The size of the power converter is compact because of fewer number of power electronic switches and protection devices, and its architecture is easily expandable to accommodate more outputs, i.e., in this case, the wind turbines. A generalized sequential space-vector modulation technique is developed based on the operational principle of the proposed converter to control the outputs autonomously in order to track the maximum power point for individual VSWTs-driven PMSGs. It is expected that the proposed approach will reduce the cost of power electronic converters in a wind farm, compared to both ac- and dc-link-based topologies, which are available for the moment. [ABSTRACT FROM AUTHOR]

This paper comprehensively analyzes the stability of a grid-interfacing inverter with the LCL -filter in the discrete domain, where the LCL-filter, along with the controller, is modeled in a polar coordinate. System open-loop and closed-loop poles are analytically studied and expressed in the z -domain. Through the poles movement and distribution analysis, the relationship between system stability and the ratio of resonance frequency over sampling frequency is mathematically revealed and calculated as well as the system control gain limit. Moreover, this paper demonstrates that a grid-voltage feedforward regulator would significantly alter the inverter stability in a weak power system. By means of Jury stability criterion, the stability status under different filter resonance frequency is given. The selection of resonance frequency and filter parameters makes a considerable difference on system behavior. Finally, to improve the robustness against grid inductance variation, a conservative design recommendation of filter parameters and control gain is given. Through the tests on a laboratory-scale prototype, the theoretical analysis is validated by experimental results. [ABSTRACT FROM AUTHOR]

Virtual power plants (VPPs) are an effective platform for attracting private investment and customer engagement to speed up the integration of green renewable resources. In this paper, a robust bidding strategy to participate in both energy and ancillary service markets in the wholesale electricity market is proposed for a realistic VPP in Western Australia. The strategy is accurate and fast, so the VPP can bid in a very short time period. To engage customers in the demand management schemes of the VPP, the gamified approach is utilized to make the exercise enjoyable while not compromising their comfort levels. The modelling of revenue, expenses, and profit for the load-following ancillary service (LFAS) is provided, and the effective bidding strategy is developed. The simulation results show a significant improvement in the financial indicators of the VPP when participating in both the LFAS and energy markets. The payback period can be improved by 3 years to the payback period of 6 years and the internal rate of return (IRR) by 7.5% to the IRR of 18% by participating in both markets. The accuracy and speed of the proposed bidding strategy method is evident when compared with a mathematical method. [ABSTRACT FROM AUTHOR]

Energy consumption is increasing rapidly; hence, the energy demand cannot be fulfilled using traditional power resources only. Power systems based on renewable energy, including solar and wind, are effective and friendly for the environment. Islanded hybrid microgrid systems (IHMS) are relatively new in this industry and combine two or more sustainable sources, such as wind turbines, solar photovoltaic (PV), and other renewable alternatives, ocean, wave, and geothermal energy, etc. While sustainable, long-lasting power sources are the best choice to satisfy the growing energy demands, they are still not yet ready to be used on a large scale due to their stochastic characteristics. Furthermore, integrating these sources into the existing energy system can cause high technical difficulties, due to the stochastic nature of solar and wind in the conventional grid system and common stand-alone framework. A review of research and applications of the effective hybridization of renewable energy sources is therefore essential to address those technical and economic issues and ensure system stability, reliability, and cost-effectiveness. This article discusses the challenges that might arise when a PV plant and a wind power station are combined to produce power for the conventional main grid or in a stand-alone system. In addition, this analysis provides light on optimization approaches for improving power quality and cost-effectiveness in a solar and wind integrated IHMS. Voltage fluctuation, frequency deviation, and the uncertain nature of solar irradiation and wind sources are significant challenges for both grid-connected and standalone hybrid systems. This study then provides an overview of the control strategies which might help enhance the integration of the IHMS in producing electricity for distribution to the grid-connected load and the islanded load. In this study, the possible issues that can hinder the smooth integration of these renewable sources have been discussed. Finally, this study discusses the recent platforms being used in IHMS as well as the potential of dispatch strategies on solar and wind-integrated IHMS. [ABSTRACT FROM AUTHOR]

The design and the experimental validation of a continuous-time model predictive control (CTMPC) for a permanent magnet synchronous motor (PMSM) drive with disturbance decoupling is discussed. The CTMPC approach uses Taylor series expansion to derive a closed-form solution to the problem of model predictive control even though the system behaviour is described by a non-linear model. This type of controller requires an exact knowledge of the system model to guarantee an accurate prediction of the system behaviour, while the PMSM is usually subjected to model uncertainties and external disturbances such as the load torque. Moreover, in the proposed approach, the predicted speed tracking error is directly used to determine the required voltage command without the need for a cascaded control scheme. As a result, the load torque is seen as unmatched disturbance which makes exact disturbance decoupling more challenging. To overcome such a problem, a non-linear disturbance observer is designed and combined with the CTMPC method to enhance the prediction accuracy under parameter variation and unknown load torque. The feasibility of the proposed approach is experimentally investigated, and good transient and steadystate performances are obtained. [ABSTRACT FROM AUTHOR]

The modern electric power systems are going through a revolutionary change because of increasing demand of electric power worldwide, developing political pressure and public awareness of reducing carbon emission, incorporating large scale renewable power penetration, and blending information and communication technologies with power system operation. These issues initiated in establishing microgrid concept which has gone through major development and changes in last decade, and recently got a boost in its growth after being blessed by smart grid technologies. The objective of this paper is to presents a detailed technical overview of microgrid and smart grid in light of present development and future trend. First, it discusses microgrid architecture and functions. Then, smart features are added to the microgrid to demonstrate the recent architecture of smart grid. Finally, existing technical challenges, communication features, policies and regulation, etc. are discussed from where the future smart grid architecture can be visualized. [ABSTRACT FROM AUTHOR]

Direct-driven ironless-stator machines have been reported to have low requirements on the strength of the supporting structures. This feature is attractive for offshore wind turbines, where lightweight generators are preferred. However, to produce sufficient torque, ironless generators are normally designed with large diameters, which can be a challenge to the machine’s structural reliability. The ironless multi-stage axial-flux permanent magnet generator (MS-AFPMG) has the advantages of ironless machines but a relatively small diameter. The objective of this article is to present the design optimization and performance investigation of the ironless MS-AFPMG. An existing design strategy, which employs two- and three-dimensional static finite element analyses and genetic algorithm for machine optimization, is improved with the aim of reducing the calculation load and calculation time. This improved design strategy is used to investigate the optimal ironless MS-AFPMG. Some intrinsic features of this kind of machine are revealed. [ABSTRACT FROM AUTHOR]

This paper presents a robust continuous-time model predictive direct power control for doubly fed induction generator (DFIG). The proposed approach uses Taylor series expansion to predict the stator current in the synchronous reference frame over a finite time horizon. The predicted stator current is directly used to compute the required rotor voltage in order to minimize the difference between the actual stator currents and their references over the predictive time. However, as the proposed strategy is sensitive to parameter variations and external disturbances, a disturbance observer is embedded into the control loop to remove the steady-state error of the stator current. It turns out that the steady-state and the transient performances can be identified by simple design parameters. In this paper, the reference of the stator current is directly calculated from the desired stator active and reactive powers without encompassing the parameters of the machine itself. Hence, no extra power control loop is required in the control structure to ensure smooth operation of the DFIG. The feasibility of the proposed strategy is verified by the experimental results of the grid-connected DFIG and satisfactory performances are obtained. [ABSTRACT FROM PUBLISHER]

This paper presents the design, implementation, and performance testing of a nonlinear proportional-integral (PI) predictive controller for a grid-tied inverter used in photovoltaic systems. A conventional cascade structure is adopted to design the proposed controller, where the outer loop is used to regulate the dc-link voltage, and the inner loop is designed as a current controller for adjusting the active and reactive powers injected into the grid. For each loop, the controller is derived based on combining a continuous-time nonlinear model predictive control and nonlinear disturbance observer techniques. It turns out that the composite controller reduces to a nonlinear PI controller with a predictive term that plays an important role in improving tracking performance. The salient feature of the proposed approach is its ability to approximately preserve the nominal tracking performance during the startup phase. Both simulation and experimental results are provided to demonstrate the effectiveness of the proposed approach in terms of nominal performance recovery, disturbance rejection, and current control. [ABSTRACT FROM AUTHOR]

This article presents fault ride-through schemes for a three-phase quasi Z source single-stage photovoltaic (PV) inverter that is connected to the grid after the distribution network. The quasi Z source inverter employs a unique LC network to couple the inverter main circuit to the input of the PV panel. By controlling the shoot-through duty cycle, the quasi Z source inverter can theoretically produce any desired output AC voltage, even greater than the line voltage. Three different control strategies to improve the low-voltage ride-through capability are proposed when there is voltage sag from the grid side so that the grid fault ride-through requirements can be fulfilled. Scheme A involves control modification in the system; Schemes B and C involve hardware modification in the circuit topology by adding a chopper circuit across the DC link in Scheme B and across the quasi Z source inverter capacitor in Scheme C. A comparative study among the different control schemes is carried out to see the effectiveness of the control schemes under different types of symmetrical and unsymmetrical fault conditions. Observations based on comparing simulations and recommendations are reported. [ABSTRACT FROM AUTHOR]

Open circuit faults of island distribution lines account for more than 70% of the total number of faults in the distribution network. Failure assessment of lines plays a crucial role in the operational safety of the island distribution network. Aiming at the problems of multiple operational failure factors and difficulty in failure assessment, a failure assessment method of island distribution lines based on model‐data hybrid drive is proposed in this paper. Specifically, in order to accurately describe the actual operating status and failure mechanism of distribution lines in the typical island environment, model‐driven method is used to formulate a comprehensive operational failure index of distribution lines, which combines with the impact of strong wind and corrosion operation scenarios and the operating characteristics of lines. On this basis, to improve the accuracy of failure assessment under the influence of multiple factors in the island environment, an improved light gradient boosting machine model is constructed in a data‐driven manner. Finally, based on actual data from distribution network in Zhoushan, China, the case study reveals that the proposed method could effectively assess the operational failure of island distribution lines. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) energy systems have found diverse applications in fulfilling the increasing energy demand worldwide. Transformer-less PV inverters convert the DC energy from PV systems to AC energy and deliver it to the grid through a non-isolated connection. This paper proposes a new transformer-less grid-connected PV inverter. A closed-loop control scheme is presented for the proposed transformer-less inverter to connect it with the power grid. The proposed transformer-less inverter reduces extra leakage current and holds the common-mode voltage at a constant point. To eliminate extra leakage current, as well as achieve constant common-mode voltage, a midpoint clamping method is utilized to operate the inverter. The proposed transformer-less inverter is formed of seven insulated gate bipolar transistors (IGBTs) employing a unipolar sinusoidal pulse width modulation (SPWM) technique for switching purposes. An LCL filter is employed to reshape the two-level inverter output voltage and current to obtain closer sinusoidal waveforms. The output voltage and current total harmonic distortion (THD) of the proposed transformer-less inverter were found to be 1.25% and 0.94%, respectively, in the grid-connected mode. The leakage current elimination mechanism with the proposed transformer-less inverter is deeply analyzed in this paper. The performances of the proposed transformer-less inverter were evaluated with MATLAB/Simulink simulation and validated in a laboratory scale experiment. [ABSTRACT FROM AUTHOR]

In this article, a community integrated energy system (CIES) coupled with electricity, gas and heat is investigated, which integrates with renewable energies such as photovoltaic and wind turbine. The main goal is to seek an optimal scheduling scheme, including reducing the operating costs and fully exploiting the demand response potential. Firstly, given the structure of CIES, the system equipment and loads are modeled and analyzed. Moreover, considering the user controllable degree, a comprehensive user satisfaction method is established based on the combination of subjective weight and objective weight method. This paper concerns the user controllable degree in the process of flexible load optimization so that some amounts of loads are transferred from peak periods to off‐peak periods to flatten the load curve. Three cases studies in the article show the influence of user controllable degree and satisfaction on CIES. Finally, the system model is solved using CPLEX solver in MATLAB optimization software. The results show that the operating costs and environmental costs are reduced by 9.31% and 3.24% due to the presence of user controllable degree and satisfaction. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Cloud energy storage system (CESS) technology is a novel idea to eliminate the distributed energy storage systems from the consumers into a cloud service centre, where CESS acts as a virtual energy storage capacity instead of the actual devices. This combination forms a grid-forming battery-supercapacitor cloud hybrid energy storage system (CHESS) which is responsible for maintaining the voltage stability and power balance at the common DC bus of the multiple NG system. By establishing such an access to CESS, the proposed model allocates optimal shares of charge/discharge capacities for home owners, minimizes the daily operation cost of each home and grants an optimal operation of household appliances. [Extracted from the article]

With the rapid increase of renewable energy generation worldwide, real‐time information has become essential to manage such assets, especially for systems installed offshore and in remote areas. To date, there is no cost‐effective condition monitoring technique that can assess the state of renewable energy sources in real‐time and provide suitable asset management decisions to optimize the utilization of such valuable assets and avoid any full or partial blackout due to unexpected faults. Based on the Internet of Things scheme, this paper represents a new application for the Supervisory Control and Data Acquisition (SCADA) system to monitor a hybrid system comprising photovoltaic, wind, and battery energy storage systems. Electrical parameters such as voltage, current, and power are monitored in real‐time via the ThingSpeak website. Network operators can control components of the hybrid power system remotely by the proposed SCADA system. The SCADA system is interfaced with the Matlab/Simulink software tool through KEPServerEX client. For cost‐effective design, low‐cost electronic components and Arduino Integrated Development Environment ATMega2560 remote terminal unit are employed to develop a hardware prototype for experimental analysis. Simulation and experimental results attest to the feasibility of the proposed system. Compared with other existing techniques, the developed system features advantages in terms of reliability and cost‐effectiveness. [ABSTRACT FROM AUTHOR]

Summary: In this paper, an innovative switching scheme named simultaneous space vector modulation (SSVM) is proposed for integrating various AC sources in the energy industry using a unified multiport converter. The proposed SSVM technique is applied to the multileg topology of a multiport converter, which is an encouraging option for the grid integration of renewable energy sources and multimachine drives. Considering the shared leg in the multileg converter, the proposed SSVM can utilize the utmost simultaneous switching states between different ports, resulting in lower switching loss and better DC‐link voltage utilization compared with the conventional sequential space vector modulation approach. A novel decision matrix concept is introduced to identify the simultaneous switching states. For this aim, according to the number of ports of the multileg converter, decision matrices containing valid simultaneous switching states are first calculated. Then, they are defined as look‐up tables in the proposed SSVM to be retrieved and exploited in every sampling period. The effectiveness of the proposed SSVM for a seven‐leg version of the multileg converter is assessed using the simulation analysis and real‐time validation. The capability of the proposed SSVM‐based multiport converter in grid integration of AC renewable energy sources is also verified considering two permanent magnet synchronous generator (PMSG)‐based wind turbines with real wind speed patterns. The simulation results confirm that the proposed SSVM is properly able to manage the power flow between different ports and improve the DC voltage utilization and switching loss compared with the sequential SVM. [ABSTRACT FROM AUTHOR]

A bidirectional dc-dc power converter is an essential part of a HFCEV (Hybrid Fuel Cell Electric Vehicle) and renewable energy hybrid system. This paper presents a new bidirectional dc-dc power converter for HFCEV and renewable energy hybrid systems. The proposed converter is called four phases floating interleaved boost converter. Two control strategies of the dc-bus voltage are discussed. In the first one, a dual loop with linear current and voltage controllers is developed, based on the frequency response of the system. In the second one, the linear current controller is replaced by a non-linear sliding mode current controller, to improve the system performance from the robustness point of view. The non-linear sliding mode controller is designed based on the average model of the proposed topology. The proposed control strategies have been validated by simulation and experimental results. [ABSTRACT FROM AUTHOR]

Microgrid control and operation depend on fault detection and classification because it allows quick fault separation and recovery. Due to their reliance on sizable fault currents, classic fault detection techniques are no longer suitable for microgrids that employ inverter-interfaced distributed generation. Nowadays, deep learning algorithms are essential for ensuring the reliable, safe, and efficient operation of these complex energy systems. They enable quick responses to faults, reduce downtime, enhance energy efficiency, and contribute to the overall sustainability and resilience of microgrids. With this intent, this work proposes a “Discrete Wavelet Transform with Deep Neural Network (DWT-DNN)” for detecting and classifying the various faults that occurred in hybrid energy-based multi-area grid-connected microgrid clusters. The proposed DWT-DNN first extracts the input features from the point of common coupling of the cluster system using DWT, and then, these decomposed features are applied as input variables to train the DNN for the detection and classification of various faults. All the investigations are performed in the “MATLAB/Simulink 2022a” environment. To validate the effectiveness of the proposed DWT-DNN, the results are compared with wavelet packet transforms (WPT) in terms of accuracy in detecting and classifying the faults. From the simulation findings and observations, it is evident that the proposed DNN produced fruitful results. [ABSTRACT FROM AUTHOR]

Accurate fault classification and detection for the microgrid (MG) becomes a concern among the researchers from the state-of-art of fault diagnosis as it increases the chance to increase the transient response. The MG frequently experiences a number of shunt faults during the distribution of power from the generation end to user premises, which affects the system reliability, damages the load, and increases the fault line restoration cost. Therefore, a noise-immune and precise fault diagnosis model is required to perform the fast recovery of the unhealthy phases. This paper presents a review on the MG fault diagnosis techniques with their limitations and proposes a novel discrete-wavelet transform (DWT) based probabilistic generative model to explore the precise solution for fault diagnosis of MG. The proposed model is made of multiple layers with a restricted Boltzmann machine (RBM), which enables the model to make the probability reconstruction over its inputs. The individual RBM layer is trained with an unsupervised learning approach where an artificial neural network (ANN) algorithm tunes the model for minimizing the error between the true and predicted class. The effectiveness of the proposed model is studied by varying the input signal and sampling frequencies. A level of considered noise is added with the sample data to test the robustness of the studied model. Results prove that the proposed fault detection and classification model has the ability to perform the precise diagnosis of MG faults. A comparative study among the proposed, kernel extreme learning machine (KELM), multi KELM, and support vector machine (SVM) approaches is studied to confirm the robust superior performance of the proposed model. [ABSTRACT FROM AUTHOR]