Breaker Status Research Articles

60kV, 10Amp DC power supply multiple input control and monitoring provision for the operation of various high power RF generation systems

A 60 kV, 10 A DC power supply is used for testing of high power RF and microwave tubes e.g. Klystron, Gyrotron. Two 500 kW, 3.7 GHz klystrons, and one 82.6 GHz Gyrotron are located in SST1 Hall where as 200 kW; 28 GHz Gyrotron is located in Aditya Hall. The same power supply is required to operate, control and monitor various systems at different locations with easy change over from one system to other as per experimental requirements.An off line, control change over system, is designed to accomplish the above requirements, with control panels installed at desired different locations. The input (0 to 11 kV) A.C. voltage to power supply is given from a motorized voltage variation system (VVS). The control panels provide indication of A.C. input voltage to power supply from 11 kV potential transformers of VVS. In addition, the control panel is provided with 11 kV circuit breaker status indication and control i.e. Emergency OFF switch. The control panels are designed and developed indigenously which are successfully installed and are in continuous use for the safe and easy operation of different high power rf systems from the same DC power supply.The paper presents the design of the controls, monitoring and indications. Safety aspects of the system are also highlighted.

The Frequency Closed-Loop Control Strategy of Islanded Power Systems

A novel power system frequency control strategy is designed in this paper, which is mainly used to improve the stability of the islanding power system. Detecting the change of circuit breaker status, it is feasible to identify the serious accidents, for instance, a generator outage or disconnection from main grids, and so on. The balanceable power before disturbance and the capacity of the removed power can be used to calculate the power deficiency. Then, appropriate load can be shed adaptively. In the subsequent regulating process, adapting to the various stages of frequency variation, the concepts of rough-adjusting step and fine-adjusting step are proposed to obtain a balance between shedding loads quickly and refining the load shed in every step. The concept of proportional-integral-differential (PID) is introduced to design a closed-loop control strategy to trace frequency variation, with which a balance between restraining the sharp drop of frequency effectively and releasing the reserved system capacity thoroughly can be obtained. Moreover, the frequency recovery curve can be optimized and the dead zone of control during the frequency rising stage can be avoided. Compared with the conventional under-frequency loading shedding (UFLS) schemes, the effectiveness of the control strategy presented has been verified by EMTDC simulation tests.

A Topology Error Identification Method Directly Based on Collinearity Tests

A method for topology error identification based on collinearity tests involving Lagrange multipliers and the columns of the corresponding covariance matrix is presented. It relies on a geometric interpretation of the multipliers associated with the equality constraints that model circuit breaker status in generalized state estimation. The method is conceptually simple, and its implementation requires little computational effort, therefore being suitable for real-time applications. Results of several simulated cases conducted at the substation level on a real-life test system based on a subnetwork of the Brazilian Northern power system are used to illustrate the performance of the proposed technique.

A Genetic Algorithm-Based Procedure to Optimize System Topology Against Parallel Flows

Parallel (or loop) flows consist in the undesired circulation of power flows through certain interconnection corridors. Remedial actions available to transmission system operators or system planners include installation and operation of phase-shifting transformers and of dc transmission systems. Moreover, the invaluable experience of transmission system operators has shown that the network can be operated so as to reduce parallel flows also by properly selecting the topology of the system. In the present paper, a genetic algorithm-based procedure is designed for the topological optimization of the network against parallel flows. The control variables considered are the status of substation breakers and the location (and angle) of phase-shifting transformers. The problem is formulated as a multiobjective optimization. The main objective is that of reducing the power transfer distribution factor of an assigned transaction with reference to a set of lines; N and N-1 security levels are accounted for by means of subsidiary objective functions. The procedure is tested on a small CIGRE sample system and on a 4500-bus network representative of the European electric system (UCTE).

Fault section estimation in power systems using a novel decision support system

This paper presents a novel decision support system (DSS) using circuit breaker information for online fault section estimation in power systems. The new representation of knowledge and approach to resolving fault diagnosis problems are included in the proposed system. The DSS automatically creates rules for knowledge representation and develops an efficient diagnosis procedure. After the fault section is estimated, the logical reasoning approach uses the relay information to further validate the candidate fault section and circuit breaker status. Test results verify that the DSS can obtain rapid and accurate diagnosis results with flexibility and portability for fault diagnosis of diverse power systems. Those results further demonstrate the feasibility of applying the proposed DSS to actual power system fault section estimation.

Fault Section Estimation in Power Systems Using a Novel Decision Support System

This paper presents a novel decision support system (DSS) using circuit breaker information for online fault section estimation in power systems. The new representation of knowledge and approach to resolving fault diagnosis problems are included in the proposed system. The DSS automatically creates rules for knowledge representation and develops an efficient diagnosis procedure. After the fault section is estimated, the logical reasoning approach uses the relay information to further validate the candidate fault section and circuit breaker status. Test results verify that the DSS can obtain rapid and accurate diagnosis results with flexibility and portability for fault diagnosis of diverse power systems. Those results further demonstrate the feasibility of applying the proposed DSS to actual power system fault section estimation.

Abductive reasoning network based diagnosis system for fault section estimation in power systems

This paper presents an abductive reasoning network (ARN) for real-time fault section estimation in power systems. The proposed ARN handles complicated and knowledge-embedded relationships between the circuit breaker status (input) and the corresponding candidate fault section (output) using a hierarchical network with several layers of function nodes of simple low-order polynomials. The relay status is then further used to validate the final fault section. Test results confirm that the proposed diagnosis system can obtain rapid and accurate diagnosis results with flexibility and portability for diverse power system fault diagnosis. In addition, the proposed method performs better than the artificial neural networks (ANN) classification method both in developing the diagnosis system and in estimating the practical fault section. Moreover, this study demonstrates the feasibility of applying the proposed method to real power system fault diagnosis.

Abductive Reasoning Network-Based Diagnosis System for Fault Section Estimation in Power Systems

This study presents an abductive reasoning network (ARN) for real-time fault section estimation in power systems. The proposed ARN handles complicated and knowledge-embedded relationships between the circuit breaker status (input) and the corresponding candidate fault section (output) using a hierarchical network with several layers of function nodes of simple low-order polynomials. The relay status is then further used to validate the final fault section. Test results confirm that the proposed diagnosis system can obtain rapid and accurate diagnosis results with flexibility and portability for diverse power system fault diagnosis. In addition, the proposed method performs better than the artificial neural networks (ANN) classification method both in developing the diagnosis system and in estimating the practical fault section. Moreover, this study demonstrates the feasibility of applying the proposed method to real power system fault diagnosis.

AI automates substation control

The control of a substation is a very complex task due to the great number of related problems and, therefore, the decision variables that can influence the substation performance. Under such circumstances, the use of learning control systems can be very useful. The difficulties associated with the application of artificial intelligence techniques include: selection of the magnitudes to be controlled; definition and implementation of the soft techniques; and elaboration of a programming tool to execute the control. The interest of the present work is to expose the obtained results and to present them for discussion. The objective is to show that it is possible to control the status of circuit breakers (CB) in a substation making use of a knowledge base that relates some of the operation magnitudes, mixing status variables with time variables and fuzzy sets. Even when all the magnitudes to be controlled cannot be included in the analysis (mostly due to the great number of measurements and status variables of the substation and, therefore, to the rules that would be required by the controller), it is possible to control the desired status while supervising some important magnitudes as the voltage, power factor, and harmonic distortion, as well as the present status.

Modelling and Analysis of a Unit Protection Scheme

This paper presents the modelling and analysis of unit protection of feeders. The protection system module is linked to the primary power system module in such a way that it acts as a feedback loop. The primary power system module provides the three-phase voltages and/or currents at the transducer locations. The protection system module then processes this data, and outputs a circuit breaker status, which can then be feedback to the primary power system module. The paper also describes the operating principles of the protection unit. Finally, practical applications of the model under fault conditions are examined.

Fuzzy logic approach in power system fault section identification

Great emphasis has been put on applying expert systems for transmission system fault diagnosis. However, very few papers deal with the unavoidable uncertainties that occur during operation involving the fault location and other available information. The paper proposes a method using fuzzy sets to cope with such uncertainties. A fuzzy expert system is developed, which requires much less memory to store an active database than that used by conventional rule-based expert systems. The fuzzy expert system identifies two basic network section sets, S/sub healthy/ for the healthy subnetwork and S/sub island/ for the fault islands, using the postfault status of circuit breakers and relays. It then conducts inference to determine the most likely fault sections and the associated fault sequences. Two case studies are provided to demonstrate salient features of the proposed approach, and to compare results both with a conventional rule-based expert system and a refined genetic algorithm. The proposed fuzzy expert system can be operated either in a stand-alone manner, or as part of the overall architecture of a diagnosis system for parallel decision making.

Identifying the unknown circuit breaker statuses in power networks

This paper describes an approach by which the circuit breaker status errors can be detected and identified in the presence of analog measurement errors. This is accomplished by using the least absolute value (LAV) state estimation method and applying the previously suggested two stage estimation approach by A. Monticelli (see ibid., vol.8, no.3, p.1143-9, 1993). The ability of the LAV estimators to reject inconsistent measurements, is exploited in order to differentiate between circuit breaker status and analog measurement errors. The first stage of estimation uses a bus level network model as in conventional LAV estimators. Results of stage 1 are used to draw a set of suspect buses whose substation configurations may be erroneous. In the second stage, the identified buses are modeled in detail using the bus sections and the circuit breaker models while keeping the bus level network models for the rest of the system. The LAV estimation is repealed for the expanded system model and any remaining significant normalized residuals are flagged as bad analog measurements, while the correct topology is determined based on the estimated flows through the modeled circuit breakers in the substations. The proposed approach is implemented and tested. Simulation results for cases involving circuit breaker status and/or analog measurement errors are provided.

Fiber optic sensing applications in the electric power industry

Fiber optic telecommunications is a well-established discipline which finds applications in all industrial areas for signaling and control. However, fiber optics for intrinsic sensing of fluid levels, gas presence, temperature, pressure, or rotation, is rapidly being applied to the medical, petrochemical, and marine professions. Not to be overlooked are several new fiber optic sensing techniques which are now capable of accurately measuring electric current, voltage levels, and even breaker status. By monitoring such parameters, the power industry can take full advantage of the benefits of fiber optics, especially in high electromagnetic field environments. This paper surveys those techniques and experiences with fiber optic sensing applicable to today's power industry.

Examples of simulation using Pinogram

Fiber optic telecommunications is a well-established discipline which finds applications in all industrial areas for signaling and control. However, fiber optics for intrinsic sensing of fluid levels, gas presence, temperature, pressure, or rotation, is rapidly being applied to the medical, petrochemical, and marine professions. Not to be overlooked are several new fiber optic sensing techniques which are now capable of accurately measuring electric current, voltage levels, and even breaker status. By monitoring such parameters, the power industry can take full advantage of the benefits of fiber optics, especially in high electromagnetic field environments. This paper surveys those techniques and experiences with fiber optic sensing applicable to today's power industry.

Interactive modelling of transferable load facilities in distribution system operation

In power distribution systems it is extremely important to achieve rapid restoration of customer supply and speedy return to normal operating conditions following a system equipment failure or other system abnormality. This paper presents interactive modelling techniques that have been developed to detect and analyse the available transferable load restoration operations following a system abnormality. These techniques recognize the operating configuration of the system existing at the time of fault by inputting the source points and the operating status of the system breakers and switches. The increased and more meaningful information on distribution system operation that can be gained from these techniques is illustrated by the analysis of a 20 kV system based on a real Hellenic distribution system.

A Hybrid Expert System for Faulted Section Identification, Fault Type Classification and Selection of Fault Location Algorithms

This paper presents an expert system developed in turbo prolog to identify faulted sections and interpret protective apparatus operation in large interconnected power systems. The expert system presented here is capable of identifying bus faults, line fault sections, and fault sections in the common area of a specific bus and line. Also, the expert system identifies relays or breakers malfunctions. The expert system is then expanded to include real-time measurements of current and voltage phasors to classify the type of fault that the faulted section has experienced. Furthermore, when the faulted section is a transmission line, the expert system selects an appropriate fault location algorithm to compute the fault location in miles. This paper shows that the combination of numeric and data base algorithm is essential to many developments in expert system application in power systems. Evaluating the expert systems reported so far for fault diagnosis reveals that all of these schemes utilize only the data received from breaker and relay status. Consider the recent trend in digital protection, real-time phasor measurements would be available. To combine real-time phasor measurements with relay and breaker status, a hybrid expert system is required. A hybrid expert system combines numeric algorithms with data base algorithms in one scheme. This paper recognizes this feature in the expert system developed here. The expert system reported in this paper includes four stages. The first stage determines the faulted section of the power system and reports correct and incorrect breaker and relay operation.

Consideration for Implementing Multiterminal DC Systems

The established principles of multiterminal dc transmission are applied to the planning needs of practical projects. Without further detailed review of operating techniques, possibilities and contraints that are intended to be useful in the assessment of potential projects are discussed. Reference is made to the plans for certain schemes and the status of dc circuit breakers is reviewed.

On-Line Observability Determination for Power System Monitoring

Prerequisites for on-line state estimation in electric power systems include the determination of the electrical connectivity of the system (i.e. its configuration), based on the status of circuit breakers and isolators, and the determination of the ‘measurement’ connectivity of the system (i.e. its observability) based on the type and availability of measurement devices.The observability problem is to a large extent unexplored and appears from recent literature to be inadequately defined.The present paper concentrates on the definition of the terminology regarding ‘observability’ of the network, and presents an ‘algorithm’ which is currently implemented in an on-line security assessment installation.

Static state estimation in electric power systems

A static state estimator is a collection of digital computer programs which convert telemetered data into a reliable estimate of the transmission network structure and state by accounting for 1) small random metering-communication errors; 2) uncertainties in system parameter values; 3) bad data due to transients and meter-communication failures; and 4) errors in the network structure due to faulty switch-circuit breaker status information. The overall state estimation process consists of four steps: 1) hypothesize mathematical structure; 2) estimate state vector; 3) detect bad data and/or structure errors; and identify bad data and/or structure errors. The problem is characterized by high dimensionality and the need for real-time solutions using limited computer time and storage. Various methods of solution are discussed and compared.