Grid-connected Distributed Generation System Research Articles

Islanding Event Detection in Grid-Connected Distributed Generation Systems Using Unscented Kalman Filter

A pressing concern in modern smart grid systems revolves around islanding, leading to unpredictable system parameters and a decline in power quality. In response to this concern, we introduce a novel passive method for identifying islanding in grid-connected distributed generation units. This method utilizes the unscented Kalman filter (UKF) to assess the voltage signal captured at the DG position. The triphase voltage signal observed at the point of common coupling (PCC) is used as the test signal. The UKF extracts and filters the harmonic content of the voltage signal to produce a residual signal, which detects changes in the power system. The estimation of total harmonic distortion (THD) follows, and its fluctuations help discern between islanding and typical events. This suggested approach undergoes assessment through a test system simulated in MATLAB/Simulink across different situations. Outcome findings underscore the efficacy of the suggested approach in distinguishing between islanding and regular occurrences, ensuring enhanced reliability and resilience against incorrect operations by removing the zone of nondetection. In our detailed experiments, we found that the proposed unscented Kalman filter (UKF) technique improved islanding detection accuracy by approximately 90% over traditional methods, under varied conditions. Specifically, the nondetection zone (NDZ) was reduced by 95% when compared to the most commonly used passive methods. Furthermore, in scenarios with high harmonic content and noise, the UKF showcased a 90% improvement in reliability over conventional techniques.

Performance Analysis of a PEMFC-Based Grid-Connected Distributed Generation System

Less energy consumption and more efficient use of renewables are among the sustainable energy targets of modern societies. The essential activities to be achieved under these objectives are to increase distributed generation (DG) structures’ applicability. DG systems are small-scale versions of the traditional power grid; they are supported by micro turbines, photovoltaics (PV) modules, hydrogen fuel cells, wind turbines, combined heat and power systems, and energy storage units. The aim of this research is to detail the performance analysis of a proton-exchange membrane fuel cell (PEMFC)-based grid-connected distributed generation system with the help of empirical calculations. To this end, we aimed to establish the system and analyze the performance of the reliable operation of the system with experimental verifications. The findings demonstrate how much power can be generated annually, through real meteorological data, to dispatch to constantly variable loads. While 53.56% of the total energy demand is met by the utility grid, 46.44% of the demand is met by the produced energy i.e., from the DG. The PEMFC-based DG system analyzed in detail in this study was located at Marmara University. According to the results of the performance analysis, significant points of this study will be highlighted to assist the researchers working in this field. Our results are encouraging and can be certified by a larger sample size with neat weather conditions in terms of the percentage of procurement of energy.

A Data-Driven Hybrid Methodology Using Randomized Low-Rank DMD Approximation and Flat-Top FIR Filter for Voltage Fluctuations Monitoring in Grid-Connected Distributed Generation Systems

The voltage fluctuations are caused by variations in renewable energy source outputs, increased usage of nonlinear loads, high reactive power consumption of loads, etc. This results in damage to electric components and enormous economic losses. It is necessary to measure the parameters of voltage fluctuations and flicker levels to achieve a secure supply of power. However, higher-order harmonics and noises in voltage waveform make such assessment a burdensome task. The traditional techniques fail to provide exact monitoring due to the uncharacteristic variations in the input voltage signal. Nowadays, data-driven methods have become a prominent choice for non-stationary, nonlinear signal analysis as it efficiently tackles atypical changes by its capability to identify spatio-temporal information from given data. The present paper proposes a data-driven hybrid methodology for monitoring voltage fluctuations using the low-rank approximation of dynamic mode decomposition (DMD) and flat-top finite impulse response (FIR) filter. The low-rank approximation of DMD enables to identify the spatio-temporal coherent structures from the data by mapping the data into a lower-dimensional space. Adaptive flat-top FIR filter tracks the fundamental dynamic phasor by identifying the instantaneous frequency, magnitude and phase variations. The performance of the proposed hybrid methodology is assessed using different test cases, and is compared with various existing approaches. The promising results suggest that the proposed methodology can be used for accurate parameter identification and monitoring voltage fluctuations in smart grid scenarios. It can also be used as an accurate tool in distribution grids to detect higher-order harmonics.

Performance of a new hybrid approach for detection of islanding for inverter-based DGs

This paper proposes a new hybrid method for islanding detection and minimizes the Non-Detection Zone (NDZ), for an inverter-based grid-connected distributed generation (DG) system. The proposed hybrid method is an integration of the modified active Sandia Frequency Shift (SFS) method and the passive reactive power variation technique. The modified active SFS method is obtained by adaptive tuning of the gain parameter Ksfs, using the Adaptive Particle Swarm Optimization (APSO) technique. The proposed hybrid method produces a significant reduction of NDZ and is suitable for more accurate detection of islanding condition. The effect of NDZ for the proposed hybrid method has been derived analytically and the system performance has been assessed, under various power mismatch conditions for a DG-grid interface. The overall system performance has been found to be superior under the presence of constant power control strategy. The effect of frequency and voltage variations at the common coupling point during islanding have also been considered. Finally, the performance of the proposed method under the IEEE standard 1547 islanding test condition has been investigated for different load factors and load variations.

Performance Analysis of Grid-Connected Distributed Generation System Integrating a Hybrid Wind-PV Farm Using UPQC

This work presents a distributed generation system (DG) that combines system of a wind turbine (WT) and photovoltaic (PV) using a unified power quality conditioner (UPQC). Along with providing active power (AP) to the utility grid, Wind-PV-UPQC improves PQ indicators, for example, voltage drops/surges, harmonics of grid voltages, and PF. Since Wind-PV-UPQC depends on dual compensation scheme, the parallel converter works as a sinusoidal voltage source, while the series converter works as a sinusoidal current source. In this way, a smooth transition from grid operation to island operation and vice versa can be achieved without load voltage transitions. In addition, in order to overcome the problems through abrupt solar radiation or wind speed variations, a faster power balance is achieved between the wind turbines, the PV array, and the grid, as FFCL pursue the production of the current references of series converter. Consequently, the dynamic reactions of the converter currents and the voltage of dc bus are enhanced. A comprehensive analysis of flow of the AP through the converters is done to ensure a proper understanding of how Wind-PV-UPQC works. Finally, the simulation results are shown to estimate the dynamic and static performance of Wind-PV-UPQC in conjunction with the power distribution system.

Intelligent Transition Control between Grid-Connected and Standalone Modes of Three-Phase Grid-Integrated Distributed Generation Systems

This paper proposes an intelligent seamless transition controller for smooth transition between grid-connected (GC) and standalone modes of distributed generation (DG) units in the grid. The development of this seamless controller contributes to two main processes in the transition modes: the synchronization process and an islanding process. For the synchronization process, the stationary reference frame phase-locked loop (SRF-PLL) associated with the voltage source inverter (VSI) is modified using the frequency, voltage deviation, and phase angle information. Furthermore, the islanding process is classified as intentional and unintentional islanding scenarios for achieving efficient transition control. Here, the intentional islanding process is achieved with the information that is available in the system due to the planned disconnection. For the unintentional islanding process, a fuzzy inference system (FIS) is used to modify the conventional droop control using the information of change in active power, voltage, and frequency. To identify the action of the proposed approach during the transition process, numerical simulations are conducted with the hardware-in-loop (HIL) simulator by developing a 10kWp three-phase grid-connected DG system. The results identified the efficient control of the VSI for both islanding and grid connection processes. In the islanding conditions, the proposed controller provides advantage with less detection and disconnection time, and during synchronization, it instantly minimizes the phase-angle deviation to achieve efficient control.

Virtual State Damping for Resonance Suppression and Robustness Improvement in LCL-Type Distributed Generation Inverters

This article proposes a Virtual State Damping (VSD) plugin to output current controllers of distributed generation (DG) inverters. The VSD is designed to suppress the resonance usually present in LCL-type grid-connected DG systems, providing robustness to the control system against grid impedance uncertainties or variations. Typical active damping techniques apply an equivalence impedance model to design their structures. The proposed VSD has the advantage of not needing to take such analysis into account for its design, i.e., it is not dependent on the LCL filter's physical model. The VSD structure applies the model reference theory, and it does not require additional sensors for its implementation. The paper also presents the VSD design methodology and stability analysis. Real-time domain emulation (RTDE) results and 5kW lab-prototype experimental results demonstrate the effectiveness of the proposed technique.

Advanced Variable Switching Frequency Control for Improving Weighted Efficiency of Distributed Renewable Generation Systems

Energy conversion efficiency and output current harmonic distortion are two key performance measures of small-scale grid-connected distributed generation (DG) systems. As the interface between renewable energy generators and the utility grid, dc-ac converters (i.e. inverters) have been increasingly used in recent years. In this paper, a novel control algorithm termed “variable switching frequency control (VSFC)” is proposed to increase the weighted efficiency of the inverter for renewable energy generators through selection of optimal switching frequencies of pulse width modulation (PWM) in real time, based on estimation of output current harmonic distortion. Both simulation and experimental results indicate the proposed VSFC algorithm ensures that the inverter can operate with maximum efficiencies at different output levels while satisfying standard requirements for grid current harmonic distortion. Furthermore, implementation of this method to improve the inverter efficiency has no impact on inverter costs or control complexity.

Inverter-Current-Feedback Resonance-Suppression Method for LCL-Type DG System to Reduce Resonance-Frequency Offset and Grid-Inductance Effect

For the LCL-type grid-connected distributed generation system, the grid-current-feedback active damping (GCFAD) methods have a conflict between the resonance-suppression ability and harmonic-currents amplification. For this, an inverter-current-feedback reso-nance-suppression (ICFRS) method without additional sensors is proposed to reduce resonance-frequency offset and grid-inductance effect due to its unattenuated damping characteristic under high-frequency bandwidth. By analyzing two types of equivalent impedance models of ICFRS and GCFAD with a high-pass filter (HPF), GCFAD can suppress the resonance peak well only with a large resonance-frequency offset and might result in a narrow control bandwidth. However, ICFRS can suppress the resonance peak well with smaller resonance-frequency offset and maintain a high power quality compared with GCFAD. Considering the influence of control delay and grid inductance, the positive/negative critical point of an equivalent virtual resistance of ICFRS derived in the interval of [1/6, 1/3) is obtained, and a robust ICFRS is further proposed to improve system stability by maintaining a positive resistance regardless of grid-inductance variation. The stable-state and dynamic properties of the overall system are analyzed in detail in this paper, and its proper control parameters are selected without a complicated trial. Finally, simulation and experimental results verify the validity of the proposed method.

Islanding detection using sparse S-transform in distributed generation systems

Anti-islanding protection is a mandatory requirement for grid-connected distributed generation system so as to avoid the adverse effect of islanding. In order to achieve the objective of negligible non-detection zone along with fast detection and to reduce the computational burden, sparse S-transform (SST) is proposed here. The SST matrix is computed by considering the selected frequency components containing substantial information about signal irregularities caused by islanding and ignores the irrelevant data. The modal voltage signal of the voltage at point of common coupling is processed through the SST. The energy, standard deviation and entropy values are obtained from the transformed signal for islanding detection. The proposed scheme is validated for islanding cases under closely matched power scenarios and simultaneous occurrence of islanding event with power quality disturbances. Similarly, scheme is tested for normally occurring non-islanding disturbances. The performance of the scheme is validated in IEEE-13 bus distribution system. From the simulation results, it is found that the proposed scheme performs satisfactorily under almost all practical network disturbances. The SST technique reduces the computational burden and memory requirement significantly; hence, it is more suitable for real-time implementation.

Variational Mode Decomposition and Decision Tree Based Detection and Classification of Power Quality Disturbances in Grid-Connected Distributed Generation System

This paper presents a variational mode decomposition (VMD) and decision tree based detection and classification method of single and mixed power quality (PQ) disturbances in grid-connected distributed generation system. Applicability of VMD technique is investigated for discrimination of stationary PQ disturbances (such as harmonics, interharmonics, and flicker), non-stationary events (e.g., transients) and noise. Studies indicate usefulness of VMD for accurate estimation of phasor quantities such as amplitude, phase angle, and frequency and other describing features. Features namely, mode central frequencies, relative mode energy ratios, zero crossings, and instantaneous amplitude (IA) are extracted for classification of single and mixed PQ disturbances using a decision tree algorithm. A set of synthetic test signals, disturbance signals obtained from real events as well as signals generated from real time digital simulator platform are used to test effectiveness of proposed method, under various system operating scenarios and noise levels. Proposed method is found to be capable of accurate detection, estimation, localization, and classification of all kinds of PQ disturbances in both noisy and noise-free cases.

Open-circuit Fault Diagnosis of Three-phase Inverter for Grid-connected Distributed Generation System

To solve the increase cost of acquisition of multivariate information and the impact of the rapidity of diagnosis system in processing multivariate data, we proposed a novel fault diagnosis method for three-phase inverter based on wavelet packet transform and the probabilistic neural network, which can further improve the accuracy of open-circuit fault diagnosis. The wavelet packet transform is used to extract the feature vector of the output voltage of three-phase inverter. The probabilistic neural network has strong tolerance and can be employed to classify the feature vector. The simulation results show that the method has better diagnosis accuracy, which can diagnose the open-circuit fault effectively.

A unified index for power quality evaluation in distributed generation systems

Excessive penetration of distributed generation units with their electronic power interfaces into distribution systems has introduced different power quality problems into these systems. To date, there is no agreed upon approach to quantify the overall power quality performance of a system in the presence of distributed generation units. In this paper, a unified index for power quality assessment in different distributed generation systems is proposed using the analytic hierarchy process. The unified index is determined in terms of six power quality performance parameters, namely voltage total harmonic distortion, current total harmonic distortion, frequency deviation, voltage sags score, voltage flicker, and power factor at different interface buses of three grid-connected distributed generation systems: distributed wind, wind/photovoltaic, and hybrid wind/photovoltaic/fuel cell energy systems. Simulations are carried out in the Matlab-Simulink environment. The results show that the proposed index can facilitate overall power quality evaluation of different systems under different operating conditions. It makes the assessment simple and effective as one number only is used for each comparison. Furthermore, based on the values of the index in the different systems, it was found that the hybrid energy system shows better power quality performance compared to the other systems.

Optimisation of controller parameters for grid‐tied photovoltaic system at faulty network using artificial neural network‐based cuckoo search algorithm

This study exhibits the optimum design procedure to tune controller parameters for grid-connected distributed generation system based on cuckoo search algorithm (CSA). To investigate the effectiveness of proposed algorithm, a grid-tied photovoltaic (PV) system consisting of two power electronic converters controlled by five proportional integral (PI) controllers is chosen. Setting proper values for all the PI controllers is a complicated task, notably when the system is non-linear. In this study, response surface methodology (RSM) is used to develop the mathematical design of the PV system which is required to apply the optimisation algorithm. To minimise the design efforts of RSM, an alternate approach based on artificial neural network is introduced to develop the mathematical model of the PV system which is another salient feature of this research. Moreover, two modifications in the CSA are proposed to extract optimum parameters for the controllers which are found suitable in power system applications. Both the transient and dynamic performances of the system with the optimum values obtained through CSA are studied for different types of grid fault conditions using PSCAD/EMTDC. The design values are compared with values obtained through genetic algorithm and bacterial foraging optimisation. Experimental validation is also given for the proposed method.

Impact of phase-locked loop on stability of active damped LCL-filter-based grid-connected inverters with capacitor voltage feedback

Active damped LCL-filter-based inverters have been widely used for grid-connected distributed generation (DG) systems. In weak grids, however, the phase-locked loop (PLL) dynamics may detrimentally affect the stability of grid-connected inverters due to interaction between the PLL and the controller. In order to solve the problem, the impact of PLL dynamics on small-signal stability is investigated for the active damped LCL-filtered grid-connected inverters with capacitor voltage feedback. The system closed-loop transfer function is established based on the Norton equivalent model by taking the PLL dynamics into account. Using an established model, the system stability boundary is identified from the viewpoint of PLL bandwidth and current regulator gain. The accuracy of the ranges of stability for the PLL bandwidth and current regulator gain is verified by both simulation and experimental results.

Perspectives in Solid Oxide Fuel Cell-Based Microcombined Heat and Power Systems

Abstract Fuel cell technology has undergone extensive research and development in the past 20 years. Even though it has not yet made a commercial breakthrough, it is still seen as a promising enabling technology for emissions reduction. The high electrical efficiency (Powell et al., 2012, “Demonstration of a Highly Efficient Solid Oxide Fuel Cell Power System Using Adiabatic Steam Reforming and Anode Gas Recirculation,” J. Power Sources, 205, pp. 377–384; Föger and Payne, 2014, “Ceramic Fuel Cells BlueGen—Market Introduction Experience,” 11th European SOFC & SOE Forum 2014, Lucerne, Switzerland, Paper No. A0503; and Payne et al., 2009, “Generating Electricity at 60% Electrical Efficiency From 1-2 kWe SOFC Products,” ECS Trans., 25(2), pp. 231–240) of an solid oxide fuel cell (SOFC)-based fuel cell system and the ability to operate on renewable fuels make it an ideal platform for transition from fossil-fuel dependency to a sustainable world relying on renewable energy, by reducing emissions during the transition period where fossil fuels including natural gas remain a major source of energy. Key technical hurdles to commercialization are cost, life, and reliability. Despite significant advances in all areas of the technology cost and durability targets (Papageorgopoulos, 2012, “Fuel Cells, 2012 Annual Merit Review and Peer Evaluation Meeting,” U.S. Department of Energy, Washington, DC, accessed May 14, 2012, http://www.hydrogen.energy.gov/pdfs/review12/fc_plenary_papageorgopoulos_2012_o.pdf) have not been met. The major contribution to cost comes from tailor-made balance of plant (BoP) components as SOFC-based systems cannot be optimized functionally with off-the shelf commercial items, and cost targets for BoP and stack cannot be met without volume manufacturing (Föger, 2008, “Materials Basics for Fuel Cells,” Materials for Fuel Cells, M. Gasik ed., Woodhead Publishing, Cambridge, UK, pp. 6–63). Reliability issues range from stack degradation and mechanical failure and BoP component failure to grid-interface issues in a grid-connected distributed generation system. Resolving some of these issues are a key to the commercial viability of SOFC-based microcombined heat and power (CHP) systems. This paper highlights some of the technical and practical challenges facing developers of SOFC-based products.

Study on Three-phase Stability Simulation Model of Distributed Generation System for Multi Energy Utilization

Abstract There are many different kinds of energy in future multi-energy system, such as electric, gas, heat and hydrogen. Distributed generation system integrated as microgrid is one of the most important use form of multi-energy system for customer-side. Considering typical grid-connected distributed generation system and three phase unbalanced feature of low-voltage micro-grid, three-phase stability simulation technique is a very important analysis tool for system-level energy optimization management, design of control strategy, structure stability and so on. A unified interface model of grid-connected system for synchronous generator and inverter is discussed in this paper. The unified model is given in three conventional dq coordinates and described by Norton model which is the parallel connection of injection current source and constant admittance matrix. Based on the characteristics of the unified interface model and detailed dynamics of distributed sources, an alternative implicit trapezoidal integration algorithm is developed for the stability simulation of distributed generation system. The significance of the proposed modeling method is validated by test example simulation results.

Robust two degrees‐of‐freedom single‐current control strategy for LCL‐type grid‐connected DG system under grid‐frequency fluctuation and grid‐impedance variation

For LCL-type grid-connected distributed generation (DG) system, the grid-frequency fluctuation and grid-impedance variation affect the active/reactive power control accuracy and resonance peak suppression, respectively, which would reduce the system robustness. In this study, a robust two degrees-of-freedom single-current control strategy is proposed, which mainly includes the synchronous reference frame quasi-proportional–integral (SRFQPI) control and robust grid-current-feedback active-damping (RGCFAD) control. The proposed SRFQPI control can compensate the local-load reactive power, and regulate the instantaneous grid current without steady-state error regardless of the fundamental frequency fluctuation. Simultaneously, the proposed RGCFAD control effectively damps the LCL-resonance peak regardless of the grid-impedance variation, and further improves both transient and steady-state performances. The stability margin and dynamic response of the overall system are analysed in detail, and the proper parameters are selected without complicated trial. Finally, simulation and experimental results verify the proposed control and design strategies.

분산전원 시스템의 주파수 변동을 통한 단독운전 방지기법 분석

Unintentional islanding results in safety hazards, power quality degradation, and many other issues. Thus, islanding detection of grid-connected distributed generation system is a key function for standards compliance. Many anti-islanding schemes are currently being studied; however, existing anti-islanding schemes used in inverters have power quality degradation and non-detection zone issues. Therefore, this paper analyzes existing anti-islanding schemes by using frequency drift in accordance with both islanding detection performance and power quality. This paper also proposes a new anti-islanding scheme by using frequency drift. Both simulation and experimental results show that the proposed scheme has negligible power quality degradation and no non-detection zones compared with other existing schemes.

Radial Basis Neural Network Based Islanding Detection in Distributed Generation

This article presents a Radial Basis Neural Network (RBNN) based islanding detection technique. Islanding detection and prevention is a mandatory requirement for grid-connected distributed generation (DG) systems. Several methods based on passive and active detection scheme have been proposed. While passive schemes have a large non detection zone (NDZ), concern has been raised on active method due to its degrading power quality effect. The main emphasis of the proposed scheme is to reduce the NDZ to as close as possible and to keep the output power quality unchanged. The proposed algorithm is compared with the widely used rate of change of frequency relays (ROCOF) and found working effectively in the situations where ROCOF fails. This approach utilizes rate of change of frequency at the target distributed generation location and fed to the radial basis neural network for intelligent islanding detection. Hence a better reliability is provided. This approach utilizes the artificial neural network (ANN) as a machine learning technology for processing and analyzing the large data sets provided from network simulations using MATLAB software. To validate the feasibility of this approach, the method has been validated through several conditions and different loading, switching operation, and network conditions. Simulation studies showed that the RBNN-based algorithm detects islanding situation accurate than other islanding detection algorithms. Moreover, for those regions which are in need of a better visualization, the proposed approach would serve as an efficient aid such that the mains power disconnection can be better distinguished