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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]

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]

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]