A Fast Protection Scheme for TCSC Compensated Transmission Line Using Wavelet-Alienation-Neural Technique

This paper proposes a security algorithm based on thewavelet-alienation-neural technique for detecting, classifying, and locating faults on Thyristor-Controlled Series compensator (TCSC) compensated lines. A fault index has been calculated using wavelet transform and alienation coefficients with post-fault current signals measured/ sampled for quarter cycle time at both near and far end buses for fault detection and classification. The location of the fault is predicted using an Artificial Neural Network (ANN) after the fault has been diagnosed. Approximate coefficients (quarter cycle time) of both voltage and current signals, from both buses, were provided as input to ANN. Various case studies, such as variations in TCSC position, fault location, sampling frequency, power flow path, incipient angle of fault, TCSC control strategy, fault resistance, and load switching conditions, have verified the robustness of the proposed safety system.

NÂNG CAO LỢI NHUẬN XÃ HỘI TRONG THỊ TRƯỜNG ĐIỆN CÓ THIẾT BỊ TCSC SỬ DỤNG GIẢI THUẬT COA

Thị trường điện ra đời đã mang lại nhiều lợi nhuận xã hội. Tuy nhiên, nó cũng làm cho hệ thống thường xuyên bị nghẽn mạch. Nghẽn mạch làm ảnh hưởng trực tiếp đến các hợp đồng giao dịch, làm giảm lợi nhuận xã hội. Vì vậy, để giảm nghẽn mạch, cực đại lợi nhuận xã hội, cần phải xây dựng mới các đường dây truyền tải. Điều này thường gặp nhiều khó khăn từ việc điều tiết chính sách của nhà nước và môi trường. Do đó, việc cân bằng lại công suất trong hệ thống bằng cách sử dung thiết bị Thyristor Controlled Series Compensator (TCSC) để nâng cao khả năng truyền tải và cực đại lợi nhuận xã hội là một trong những vấn đề quan trọng đối với ngƣời vận hành hệ thống điện. Để giài quyết vấn đề này, một số giải thuật tìm kiếm bầy đàn đã đƣợc đề xuất trong các nghiên cứu trước. Tuy nhiên, việc áp dụng giải thuật Cuckoo Optimazation Algorithm (COA) để giải quyết vấn đề này chưa được các nhóm nghiên cứu đề xuất trước đây. Vì vậy, trong bài báo này, giải thuật Cuckoo Optimazation Algorithm (COA) đã được đề xuất và áp dụng để giải bài toán tối ưu cực đại lợi nhuận xã hội thông qua xác định vị trí và dung lượng hợp lý của TCSC. Phương pháp đề nghị được kiểm tra trên trên hệ thống IEEE 14 nút và kết quả mô phỏng đƣợc so sánh với các giải thuật Genetic Algorithm (GA) Grey Wolf Optimization (GWO) đã cho thấy, COA cũng là một trong những phương pháp hữu ích để tối ưu lắp đặt TCSC để cực đại lợi nhuận xã hội.

Application of the First Replica Controller in Korean Power Systems

The purpose of this paper is to introduce, examine, and evaluate the industrial experiences and effectiveness of a Thyristor Controlled Series Compensator (TCSC) replica controller installed in Korea in 2019 through a review of its configuration, test platform, and practical application, and further to propose operational guidelines for replica controllers. Four representative practical cases were conducted: a Dynamic Performance Test (DPT) under a sufficiently large-scale power system prior to the Site Acceptance Test (SAT), pre-verification for on-site controller modification during operation stage, parameter tuning to mitigate the control interaction, and time domain simulation for Sub-Synchronous Torsional Interaction (SSTI). None of these four cases can be performed in a Factory Acceptance Test (FAT) or on-site. Therefore, TCSC control performance was accurately verified under the entire Korean power system based on a large-scale real-time simulator, which demonstrated its effectiveness as a powerful tool for operations including multiple power electronics devices. Our review herein of these four practical cases is expected to show the usefulness of replica controllers, to demonstrate their strength to deal with practical field events, and to contribute to the further expansion of the application area from a perspective of electric utility.

Fault Classification and Fault Zone Identification in a Thyristor Controlled Series Compensator Based Transmission Line by using Decision Tree

A new method has been introduced for classification of fault and to identify zone of fault in Thyristor Controlled Series Capacitor based line by utilizing Decision Tree method. PSACD/EMTDC software is used in this paper for the simulation of TCSC. Voltage and current samples after fault are used in this method as input against predicted output vectors for zone identification of fault. Decision Tree based classification algorithm also used to classify all ten types of faults in the TCSC based line. This method is being tested on simulated data and the results indicate that this method can classify different types of faults and also identify zone of fault more accurately than any neural network systems in a TCSC based line.

Public assistance intensification of wind-integrated restructured endowment system using thyristor-controlled series compensator peerless location and gauging using the hybrid Genetic Algorithm-Gravitational Search Algorithm

In a deregulated electricity market, it may at times become challenging to swift all the essential power which are obligatory to move along the transmission line due to congestion. This paper primly waltz up the finest allotment of thyristor-controlled series compensator in deregulated capacity setup with wind generator by considering the maximization of social welfare cost as objective function. In this work, hybrid market model has been considered and the hybrid algorithm is used as a tool, in which Gravitational Search Algorithm is used for attaining optimal location of thyristor-controlled series compensator as major issue, though Genetic Algorithm-based top-notch outflow of power minimizes operating cost after incorporating thyristor-controlled series compensator and Wind Generator as sub-optimization problem. The coherence of this prospective has been tested and analyzed on modified IEEE 14-bus system and modified IEEE 118-bus system at different loading conditions. The influences on the locational marginal pricing and system voltage have been also investigated in this work and the obtained results are compared with other globally accepted techniques reported in the literary texts.

Solar Power and Wind Power Management System using Power Line Communication using PSO

This enterprise proposes Particle swarm upgrade based TCSC Compensator in solar primarily based breeze mixture station for Reactive electricity the board and brief adequacy exam. It also hopes to choose the placing parameters of TCSC (Thyristor controlled series Compensator) controller using Particle Swarm Optimization (PSO). The self sufficient cream structure has been reproduced under distinct stacking situations for which a alternate paintings display has been considered. affects due to variable weight, Wind manipulate data and solar fueled insolation have been focused and the distinct direct of the shape has been concentrated inside the midst of normal and accuse situation. era effects related to Reactive strength repayment and voltage sufficiency have been improvised with PSO. [19],[20],[21]

Transmission Congestion Management and Techno Economical Analysis using Placement of TCSC

Congestion management is a major problem in deregulated power system. Congestion leads to increase in transmission line loading, increases losses and reducing transmission efficiency. It also leads to increase in congestion cost and thus affects technical as well as economical parameters. Research work is carried out under single line critical contingency condition. Critical contingency is found out by overall performance index (OPI). Optimal Power Flow (OPF) is carried out and objective is to maximize social welfare. Thyristor controlled series compensator is used to improve power flow, thus it reduces congestion and improves techno-economical parameters. Optimal location of Thyristor controlled series compensator (TCSC) is found out by LMP difference method.

Bi-Objective Optimization Model for Optimal Placement of Thyristor-Controlled Series Compensator Devices

Exposure to extreme weather conditions increases power systems’ vulnerability in front of high impact, low probability contingency occurrence. In the post-restructuring years, due to the increasing demand for energy, competition between electricity market players and increasing penetration of renewable resources, the provision of effective resiliency-based approaches has received more attention. In this paper, as the major contribution to current literature, a novel approach is proposed for resiliency improvement in a way that enables power system planners to manage several resilience metrics efficiently in a bi-objective optimization planning model simultaneously. For demonstration purposes, the proposed method is applied for optimal placement of the thyristor controlled series compensator (TCSC). Improvement of all considered resilience metrics regardless of their amount in a multi-criteria decision-making framework is novel in comparison to the other previous TCSC placement approaches. Without loss of generality, the developed resiliency improvement approach is applicable in any power system planning and operation problem. The simulation results on IEEE 30-bus and 118-bus test systems confirm the practicality and effectiveness of the developed approach. Simulation results show that by considering resilience metrics, the performance index, importance of curtailed consumers, congestion management cost, number of curtailed consumers, and amount of load loss are improved by 0.63%, 43.52%, 65.19%, 85.93%, and 85.94%, respectively.