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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]

• 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]

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]