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This study presents a low-cost thyristor-controlled LC compensator scheme for the improvement of overall power quality in the distribution system. The parameters of the compensator have been designed and optimal triggering angles for thyristor switching have been obtained for reducing the unbalanced condition and harmonic injection at a high power factor. Compared to the traditional static VAr compensator schemes, the proposed technique can significantly reduce the harmonic injection into the system. The particle swarm optimization technique has been applied to compute the optimal triggering angles, and different aspects of the power quality factor have been assessed through rigorous simulations. Power quality assessment has been further validated through an experimental setup in the laboratory. Finally, a comparison of the proposed scheme with other similar schemes has been carried out to highlight its efficacy. [ABSTRACT FROM AUTHOR]

This article presents a new algorithm for fault detection in grid-tied microgrids with inverter-interfaced distributed generators (DGs). To support the Grid codes, the DGs require a low voltage ride through (LVRT) capability. The control strategy used in the DGs results in large changes in the fault characteristics of the microgrid. Hence, it is required to study the fault characteristics of the DGs in a microgrid under various operating conditions. The study presents fault detection for microgrids with PQ-controlled DGs having LVRT capability under different DG voltage and different fault conditions (high impedance and low impedance). The fault location has been identified using the phase change in the positive sequence current at specific DG voltages. The reliability of the proposed scheme has been validated under diverse fault conditions through extensive simulations in the Matlab/ Simulink environment, and the comparison with other fault detection techniques proves the efficacy of the proposed scheme for fault detection in microgrids. [ABSTRACT FROM AUTHOR]

This paper proposes a new algorithm for the detection and classification of faults in transmission lines in the presence of distributed generation. The proposed algorithm uses wavelet transform-based detail and approximation coefficients of voltage and current signals over one cycle after fault inception at one end of the transmission line. The line impedance calculated from the ratio of the voltage and current approximation coefficients is fed to the fuzzy inference system to classify faults. The proposed algorithm has been tested successfully in a real-time digital simulator for nonlinear high impedance faults in the presence of wind farm, considering the effects of CT saturation. All types of faults with the variation of pre-fault loading condition, line parameters, line length and source impedance can be correctly classified using the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper numerically investigates both the inline and staggered arrays of circular multiple swirling air jets that impinge perpendicularly onto a smooth flat surface. The simulations were conducted for various flow and geometric parameters, such as Reynolds number (Re = 11,600, 24,600, and 35,000), jet‐to‐surface distance (H/D = 1, 2, 3, and 4), jet‐to‐jet separation distance (Z/D = 1.5, 3.0, and 4.5) and swirl numbers (S = 0, 0.3, and 0.75), where D is the nozzle diameter. For S = 0.75, a strong recirculation develops due to the vortex breakdown, depends on Z/D, around the axis and near the wall. The extent of the recirculation is larger for the staggered array. Intense heat transfer is anticipated at strong swirl and close impingement cases with the expense of uniformity; whereas a relatively even heat transfer is observed for larger impingements. The increase in jet‐to‐jet separation enhances the overall cooling effect and the staggered configuration of nozzles gives better performance. It appears that both the crossflow and turbulence around the periphery of each jet predominantly govern the heat transfer characteristics. The enhancement of heat transfer occurs for increasing Re, and the overall Nusselt number (Nu) prediction is scaled by Ren, with n dependent on S. Finally a correlation is developed for the average Nusselt number to relate different control parameters. [ABSTRACT FROM AUTHOR]

This study aims to develop a new relaying scheme for the complete protection of transmission line based on only voltage data. Fault detection and classification is obtained from the fundamental component of the voltage signal collected from one end of the line. Magnitudes of positive sequence component of voltage signals from both ends of the line have been considered for fault location. As only magnitude of voltage signal is used, the requirement for data synchronization can be avoided, and the error caused by current transformers (CT) is eliminated. Moreover, positive sequence components exist for all types of faults, unlike negative sequence components. Hence, all types of faults can be located. Fuzzy decision approach has been proposed to avoid computationally expensive training of expert systems. The proposed scheme has been tested for different dynamic situations in MATLAB/Simulink software. The superiority of the scheme has been established by considering coupling capacitor voltage transformer (CCVT) transient error, weak infeed condition, change of transmission voltage level and line loading. [ABSTRACT FROM AUTHOR]

Transmission lines (TL) are exposed to diverse climatic conditions, which make them prone to faults in different phases simultaneously or after a short delay at the same or different locations. These complicated faults can cause failure or mal-operation of the conventional distance protection schemes. This research work presents a solution to identify and classify faults in long TLs under challenging situations. In this algorithm, the fundamental components of voltage and current signals from both ends of the TLs have been considered to evaluate the admittance-based fault index to discriminate the internal fault from the external ones and also to identify the faulty phase. The proposed algorithm has been tested under different dynamic conditions viz. swing condition, close-in fault, presence of series compensator, load angle and source strength variation, etc., to ascertain the robustness and reliability of the algorithm. The significant contribution of this algorithm is that it can accurately detect and classify the complex high impedance faults including evolving and cross-country faults in the transmission systems. [ABSTRACT FROM AUTHOR]

A novel two stage multi-objective control strategy for optimal voltage unbalance compensation in low voltage microgrid systems consisting of inverter interfaced distributed generators (IIDGs) has been presented in this research. To ensure continuous and safe operation of the IIDGs during unbalanced voltage sags, the proposed control strategy supplies the optimal positive sequence voltage support and performs voltage unbalance compensation considering the current limitation of the inverters. The control strategy also ensures that the DGs deliver maximum allowable active power during voltage sag. The positive and negative sequence quantities of the IIDGs are controlled in such a way so that these objectives can be achieved simultaneously. The DGs are operated in coordination with each other to maintain the voltage profile as desired by the grid operator. Prioritisation of active power and unbalance compensation can be set depending upon the requirement of the customer. Under severe grid imbalance condition, the proposed technique can raise the positive sequence voltage to near nominal value from below 0.9 per unit maintaining all phase currents of DGs within safety limit.To solve the optimization problem and to generate the optimal references for the DG control unit, artificial cooperative search algorithm has been utilised. The two stage control strategy includes a local control for each DG, which coordinates with the central control to provide the optimal references for all the DGs. The multi-objective control strategy has been tested under different operating conditions and implemented in real time digital simulator to ensure the robustness and effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

• Detection and classification of faults including high impedance faults in microgrid. • Fault detection and classification from current signals at the substation. • Faulty feeder and sub-feeder identification within half cycle of post fault current signal. • Wavelet based power spectral density of current signals utilized to detect and classify fault and also identify faulty feeder. • Performance of the proposed algorithm verified under dynamic and challenging situations. The recent progress in the area of microgrid protection has led to the application of data-driven and signal processing techniques for fault detection in microgrids. The deployment of inverter interfaced distributed generators makes the traditional protection schemes ineffective. In this paper a wavelet based power spectral density (PSD) has been utilized to detect fault, identify faulty phases and locate fault in the microgrid. Wavelet based PSD decouples the frequency information from the time information and it is the optimal technique to reveal the change of distribution of harmonics in non-stationary faulty signals as for fault analysis it can consider the faulty frequency band instead of one particular harmonic. The proposed technique can detect fault and identify faulty phases by analyzing current signals from the substation only. The normalized value of PSD of three phase current signals has been considered for fault detection and probabilistic distribution of PSD has been considered for faulty phase identification. The normalized value of PSD of the current signals collected from both ends of the main feeders and one end of the non-DG sub-feeder have been used to locate the faulty feeder and sub-feeder. Appropriate threshold values have been considered to detect fault and to locate the faulty feeder. To locate faults, the technique does not require synchronized signals and thus provides a promising and economical solution for inverter interfaced microgrid. It does not require huge amount of data set for training and testing as it is essentially a threshold based technique and also does not require collection of data at high sampling rate. The proposed scheme has been extensively tested for high impedance fault (HIF), unbalanced loading, load switching, variation of DG parameters, measurement uncertainty and presence of noise in the signal with signal to noise ratio up to 10 dB. This technique provides accurate results for fault resistance from 0 Ω to 300 Ω and up to 10% measurement error. The performance of the proposed technique has been verified for feeder length variation up to 20%. Half cycle of current signal only after fault is required and three levels of wavelet decomposition has been considered. The simulation results and comparative assessment demonstrate the efficacy of the proposed scheme. [ABSTRACT FROM AUTHOR]

This study presents a scheme for improvement of power quality in electrical distribution systems using a static VAr compensator (SVC). The switching of the SVC has been controlled with an objective to improve the overall power quality at the distribution level. The reduction of the degree of unbalance and improvement of power factor along with minimisation of harmonics injected into the system due to the operation of SVC are identified as the objectives of the SVC switching scheme. The proposed scheme can minimise a wider range of harmonics injected into the system without any external filter. The optimised switching angles have been calculated using the particle swarm optimisation technique. An artificial neural network has been designed to predict the optimum triggering angles and the performance of the scheme for fast changing loads has been evaluated in the laboratory using a data acquisition system. Practical evaluation of power quality has been carried out at each stage of simulation and experimentation to highlight the effectiveness of the proposed scheme. The results obtained from the proposed scheme have been compared with other recent works to prove the efficacy of the system. [ABSTRACT FROM AUTHOR]

This study presents a novel technique for automated power quality (PQ) disturbance detection and classification in power distribution system using cross-correlation-based approach in conjunction with fuzzy logic. The proposed method requires minimum number of features when compared with conventional approaches for identification of disturbances. Total 17 types of PQ disturbances including eight basic and nine combinations which are very close to real situations are considered for the classification. The scheme is immune to real life uncorrelated noises due to incorporation of cross spectrum analysis in the feature extraction stage. Experimentation under real operating conditions is carried out in the laboratory using data acquisition system in order to test the proposed technique. The proposed scheme is also applied in IEEE 33-bus distribution system and validated by a real-time simulator. The developed classifier achieved 100% accuracy and could comfortably outperform several contemporary methods for PQ disturbance classification. [ABSTRACT FROM AUTHOR]

This study presents a novel technique for automated power quality (PQ) disturbance detection and classification in power distribution system using cross‐correlation‐based approach in conjunction with fuzzy logic. The proposed method requires minimum number of features when compared with conventional approaches for identification of disturbances. Total 17 types of PQ disturbances including eight basic and nine combinations which are very close to real situations are considered for the classification. The scheme is immune to real life uncorrelated noises due to incorporation of cross spectrum analysis in the feature extraction stage. Experimentation under real operating conditions is carried out in the laboratory using data acquisition system in order to test the proposed technique. The proposed scheme is also applied in IEEE 33‐bus distribution system and validated by a real‐time simulator. The developed classifier achieved 100% accuracy and could comfortably outperform several contemporary methods for PQ disturbance classification. [ABSTRACT FROM AUTHOR]

• An efficient multi-objective algorithm has been proposed for optimized operation of DGs to reduce voltage unbalance at different buses. • The voltage unbalance limits for different buses can be customized according to the distinctive requirement of the consumers. • The negative sequence voltage has been reduced as much as possible. • The positive sequence voltage has been increased by incorporating LVRT capability in the DG control. • The DG output current is also optimised since the power interfacing converter consists of semiconductor devices which cannot withstand excessive currents. • Several case studies have been conducted and the performance of the proposed method has been tested in real time digital simulator. Voltage unbalance control plays an important role in maintaining the power quality standard in microgrid. This paper presents a multi-objective control strategy to realize optimal voltage unbalance compensation in a multibus microgrid, satisfying customized power quality requirement of the consumers at different buses. The distributed generators (DGs) in the microgrid share the compensation effort cooperatively to satisfy the power quality standard at different buses. Multi-objective Artificial Cooperative Search Algorithm (MOACS) has been proposed to solve the multi-objective pareto optimization problem. The algorithm assigns compensation reference to all the DGs so that the DGs can accordingly compensate the negative sequence voltage at different buses and thereby mitigate voltage unbalance. The effectiveness of the proposed scheme has been established through the results obtained from simulation and real time digital simulator. [ABSTRACT FROM AUTHOR]

A method for detecting and classifying transmission line faults using cross-correlation and k-Nearest Neighbor (k-NN) has been presented in this article. A unique analogy between the cross-correlogram obtained from the sound phase and a faulty phase in an electric power system, defined here as the fault correlogram, and a normal electrocardiogram (ECG) of human heart has been validated in the proposed work. The proposed method uses synthetic fault data within half cycle of pre-fault and half cycle of post-fault to detect and classify the different faults under varying fault parameters. EMTP/ATP software has been used as the platform to carry out simulation of the power system network followed by signal processing in MATLAB. [ABSTRACT FROM AUTHOR]

This paper presents an optimal cascaded three degree of freedom proportional integral (3DOF PI) controller and compares its performance with conventional proportional integral (PI) controller for load frequency control of two area deregulated power system. The 3DOF PI controller enhances the degree of freedom and gives better dynamic response. Genetic algorithm (GA) is used to get the optimal gains of the proposed controllers. In the considered two area thermal-gas-fuel cell system, the thermal system consists of a reheat turbine with appropriate generation rate constraint non linearity. Battery storage and unified power flow controller (UPFC) are also assumed to be present. The performance of the proposed controllers is evaluated under different operating conditions that take place in deregulated power market. To tackle any contract violation this article emphasizes on the ancillary services provided by electric vehicles (EVs) and distributed generations. A robustness analysis is also presented by varying parameters from their nominal values. [ABSTRACT FROM AUTHOR]

• High impedance fault detection in multi-feeder radial distribution system. • Detection and classification of faults and faulty line identification in presence of wind farm. • Power spectral density of current signals used to detect fault. • Wavelet covariance matrix used to calculate power spectral density. The recent progress in the area of signal processing has led to the development of intelligent schemes for fault classification and faulty phase selection in distribution system. The conventional algorithms find limitations to detect high impedance fault (HIF) and HIF remains a great concern for utilities as it can cause serious danger and accident if not detected properly. This study presents an algorithm for the detection and classification of HIF in a multi-feeder radial distribution system based on the calculation of power spectral density of faulty current signals. Discrete wavelet transform has been used to decouple the time information from the frequency information to detect and classify HIF effectively. The proposed technique has been extensively assessed under various dynamic situations including the presence of distributed generation and nonlinear load. This technique does not involve any training or learning process nor it involves any concern about data synchronization. The fault detection time is improved as it requires only half cycle of post fault current signal to detect and classify faults successfully. It is noteworthy to mention that the proposed technique considers only one end terminal current data. The comparative assessment reveals that this method can overcome the limitations of other existing techniques. [ABSTRACT FROM AUTHOR]

• Protective relaying scheme for long transmission line. • Fault detection using positive sequence admittance of two-ends of the line. • Segregation of internal and external fault. • Localization of internal fault using positive sequence fault components. In this paper, a novel integrated approach of protective relaying methodology has been adopted for detecting faults and its location estimation in long transmission line. First, the detection algorithm has been formulated using positive sequence admittance. Subsequently, fault location algorithm has been developed using positive sequence voltage and current phasors. The proposed algorithms have been implemented on a 50 Hz, 400 kV single-circuit transmission line in MATLAB environment. A wide range of diversified and challenging cases have been simulated to test the reliability of this scheme. The results confirm the preciseness of the algorithm, as it can produce accurate results under stressed conditions, viz. high impedance fault (HIF), current transformer (CT) saturation/ capacitive voltage transformer (CVT) transient, close-in faults, swing condition, source strength variation, etc. Moreover, this scheme has also been successfully tested in series-compensated and double-circuit transmission line, which brings out the superiority of this scheme. The comparative analysis with recent protective relaying techniques institutes the potentiality and robustness of the scheme. [ABSTRACT FROM AUTHOR]

• Internal fault detection from phase angles of negative sequence currents. • Phasor diagram of internal fault detection. • Fault location method. 1–26 Double-circuit transmission lines are used in modern power systems to enhance the transmission capability and to improve system reliability and safety. However, the protection of double-circuit lines is a challenging task as the presence of flexible ac transmission system (FACTS) in modern power grid impairs the performance of the conventional distance protection schemes. Moreover, the high impedance faults cannot be detected by relays as they become under-reach. This paper proposes a negative sequence current based scheme for locating faults and identifying faulty circuit/ line in double circuit transmission line compensated by UPFC at one end. In the proposed scheme the current signals are collected from both ends of the line to be protected. Then the negative sequence components of the currents are calculated. The discrimination between internal and external fault is achieved from the phase angles of the negative sequence currents and the fault location is determined from the ratio of the negative sequence currents. Prior knowledge about the type of fault is not required for fault location estimation. Extensive fault simulation studies including high impedance faults have been performed. The scheme is immune to the fault inception angle and fault resistance. [ABSTRACT FROM AUTHOR]

• Protective relaying scheme of UPFC compensated transmission line. • Fault detection using complex power of two end of the line. • Segregation of internal and external fault. • Localization of internal fault using sequence component of voltage and current signal. This study presents an integrated approach for discrimination of internal and external fault, and to obtain pin-point location of the fault in a transmission line connected to unified power flow controller (UPFC). To detect internal fault, this method uses positive sequence component of voltage and current at the local and remote end bus. Fault location estimation technique requires both positive and negative sequence voltage and current components measured from both ends of the line. The performance of the proposed technique has been evaluated by simulating a 400 kV double circuit UPFC compensated transmission line. This technique can detect internal fault under stressed conditions, viz. high impedance fault (HIF), change in source strength, change in load angle, and power swing. Precise fault location has been achieved under wide variation of system and fault parameters. The comparative assessment has been provided to prove the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]

Modulation Index (MI) variant sinusoidal-pulse-width-modulation (SPWM) is desirable for converter applications in maintaining output voltage under variable input and load environments. Enabling a high-speed switching and resolution, field-programmable gate-arrays (FPGAs) have been dominating in digital control of power electronics. This paper proposes an FPGA-based high-frequency high-resolution digital variable-modulation-indexed sinusoidal-pulse-width-modulation (DVMI-SPWM) generator architecture which can support the requirements of modern high-frequency switching and the MI adjustment ability in voltage-source-inverter (VSI) applications. A mathematically formulated optimized finite-state-machine (FSM) architecture is introduced, which adopts MI of SPWM by adjusting the duty-cycle values of SPWM pulses based on the measured feedback signal. The design employs a minor segment of medium-sized FPGA and, thereby, provides a good trade-off for multi-functional and larger schemes. The post-design simulation and experimental results validate that compared to the earlier-reported architectures, the proposed DVMI-SPWM architecture is the most appropriate one for variable MI applications with improved performance such as lower power consumption, lower harmonic distortion, and higher resolution. [ABSTRACT FROM AUTHOR]