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Fast detection of islanding is very important for effective operation and control in distributed generation (DG) penetrated distribution networks. The islanding detection techniques such as passive, active, communication, and hybrid have their own merits and demerits. This paper proposed wavelet transform (WT) and wavelet packet transform (WPT) based techniques for detection of islanding and fault disturbances in a microgrid consisting of resources like wind turbine generator, fuel cell (FC), and microturbine. Voltage signal is extracted at the point of common coupling (PCC) and is passed through these detection techniques to obtain the time-frequency multi-resolution analysis. Further, to validate the graphical study, performance indices (PIs) like standard deviation and entropy are calculated for the disturbance detection using suitable selection of threshold. A comparative analysis using WT and WPT is presented in the form of graphical simulation as well as in terms of PIs to analyse their effectiveness and robustness under different operating conditions. It is observed that WPT shows better detection capability in comparison to WT even under 20-dB noisy scenarios. [ABSTRACT FROM AUTHOR]

Abstract This paper presents wavelet transform, independent component based detection of the power quality disturbances in a microgrid. Wavelet transform (WT) is well known for its better time-frequency multi-resolution analysis because of selection of adaptive window size depending inversely with the frequency. This makes it suitable for identification of both stationary and non-stationary characteristics of the power quality disturbances. But, it is analyzed in the study that the detection capability of wavelet is degraded when the input voltage signal contains noise and completely fails when the noise level is increased to 25 dB. Of course, a wavelet-denoising technique is tested to improve the ability of wavelet transform under noisy conditions, but observed to increase the detection time. Hence, independent component analysis (ICA) is proposed for detection based on its property of finding the significant components which are statistically independent and non-Gaussian. In addition, the statistical features are extracted to formulate the input dataset for support vector machine (SVM) to classify different power quality disturbances like sag, swell, interruptions, harmonics, transients, and flickering. A comparative analysis is presented and it is observed from the study that ICA-SVM hybrid combination provides better classification accuracy as comparison to WT-SVM under different operating scenarios. [ABSTRACT FROM AUTHOR]

This paper presents frequency regulation in a microgrid consisting of wind, photovoltaic (PV), fuel cell (FC) and diesel engine generator (DEG) along with the energy storage system such as flywheel energy storage (FES) and battery energy storage (BES). In this study, firefly and particle swarm (FF–PSO) based hybrid optimization technique is proposed to tune parameters the proportional–integral–derivative (PID) controller to minimize the frequency deviation in microgrid system under different operating conditions such as variation in wind speed, and load demand. Further, a comparative analysis for tuning of the PID controller is performed using particle swarm optimization (PSO), and firefly algorithms (FFA) to minimize the deviation in frequency. The power management as well as frequency control in microgrid is studied with the help of the performance indices; integral absolute errors (IAE), peak overshoots, settling times and standard deviation (SD). In addition, the effect of communication delay with higher non-linearity is tested to assess the performance of the controllers. Further, the frequency control is validated in real-time digital simulation environment using OPAL-RT. The qualitative, quantitative and real-time analysis reflects the improvements in frequency deviation in microgrid using the proposed hybrid FF–PSO optimized PID as comparison to the PSO/FF optimized PID controllers. • Frequency regulation in a microgrid. • Frequency regulation is studied in a microgrid. • FF–PSO based hybrid optimization technique is proposed. • Performance of the controllers is tested with incorporation of communication delay. • The power management in microgrid is studied. • Improvements in frequency in microgrid is better with FF–PSO than other controllers. [ABSTRACT FROM AUTHOR]

• A Cyber-resilience based frequency regulation study is proposed in this paper. • To make the test system more realistic, different uncertainties such as solar insolation, wind. • Speed pattern, and random load changes are considered. • An adaptive type-2 fuzzy logic control method is applied, whose performance is being Compared with type-1 fuzzy logic. • IT Achieves robust frequency regulation under load change, uncertainties and cyber-attacks. • The proposed model is also validated through real-time digital simulator opal-rt. Cyber-physical attacks and parameter uncertainties are becoming a compelling issue on load frequency control, directly affecting the resilience (i.e., reliability plus security) of the microgrid and multi-microgrid systems enabled by internet of things and the fifth generation communication system. A resilient system aims to endure and quickly restore a system's transients during extreme events. Therefore, it is critically important to have a resilient system to evade the total system failure or blackout in order to make them attack-resilient. With this objective, this paper presents a resilience-based frequency regulation scheme in a microgrid under different operating conditions, such as, step and random change in load and different wind speed patterns. Furthermore, a cyber-attack model is considered in the problem formulation to make the system robust against external attacks. To protect against the cyber-attack and parameter uncertainties in the system, different control schemes are employed, and their robustness characteristics are compared through various performance indices. Besides, the proposed control schemes are validated through a real-time software synchronisation environment, i.e., OPAL-RT. As noted, the proposed type-2 fuzzy proportional-integral-derivative based controller provides the most significant improvement in the dynamic performance for frequency regulation compared to that of the others under the cyber-attack and uncertainties. [ABSTRACT FROM AUTHOR]