G.S. Hope

An artificial neural network based adaptive power system stabilizer

An artificial neural network (ANN)-based power system stabilizer (PSS) and its application to power systems are presented. The ANN-based PSS combines the advantages of self-optimizing pole shifting adaptive control strategy and the quick response of ANN to introduce a new generation PSS. A popular type of ANN, the multilayer perceptron with error backpropagation training method, is used in this PSS. The ANN was trained by the training data group generated by the adaptive power system stabilizer (APSS). During the training, the ANN was required to memorize and simulate the control strategy of APSS until the differences were within the specified criteria. Results show that the proposed ANN-based PSS can provide good damping of the power system over a wide operating range and significantly improve the dynamic performance of the system. >

Improved operation of differential protection of power transformers for internal faults

The possibility of nonoperation of second-harmonic restraint differential protection in the case of internal faults of power transformers was studied. The smaller the setting for harmonic restraint, the longer will likely be the time delay in the operation of the relay. To study this aspect, various internal faults and inrush conditions were tested on a physical model of a three-phase transformer in the laboratory. The data were analyzed by different protection algorithms. Based on the results of these studies, modified schemes for improved operation for internal faults are presented. >

An adaptive power system stabilizer based on the self-optimizing pole shifting control strategy

An adaptive power system stabilizer (APSS) employing a new self-optimizing pole shifting control strategy and its application to a power system are described in this paper. Based on an identified model of the system, the control is computed by an algorithm which shifts the closed-loop poles of the system to some optimal locations inside the unit circle in the z-domain to minimize a given performance criterion. With the self-optimization property, outside intervention in the controller design procedure is minimized, thus simplifying the tuning procedure during commissioning. Also, a new method of calculating the variable forgetting factor in real-time parameter identification is discussed. Studies show that the proposed APSS can provide good damping of the power system over a wide operating range and significantly improve the dynamic performance of the system. >

Expert systems in electric power systems-a bibliographical survey

This paper presents a bibliographical survey of research, development and application of expert systems in electric power systems based on over 80 articles published since 1982.

An expert system for voltage and reactive power control of a power system

A methodology called the sensitivity tree, which can be easily used to form an expert system for real-time control, is proposed. Based on this methodology, an expert system for the control of voltage and reactive power of a power system is developed. The main objective of this expert system is to help the operator detect buses experiencing abnormal conditions, select the most effective control measures, and calculate the control actions required to overcome the voltage violation. The control measures used to alleviate the voltage problem are capacitor compensation, transformer tap changes, and generator terminal voltage changes. By keeping the bus voltage in the entire system within limits, system security is increased. The expert system is written in the PROLOG language. Simulation studies with this expert system applied to a 30-bus power system show satisfactory results. >

Theory and method for selection of power system stabilizer location

An approach for the selection of best PSS (power system stabilizer) locations in multimachine power systems is proposed. Study shows that the right-eigenvector measures the activity of state variables and the left-eigenvector measures the control effect of control signals. Based on the right and left eigenvector, the concept of sensitivity of PSS effect (SPE) is presented and used to identify the best PSS locations. The method is used to identify the best PSS location is a 13-machine system to increase the damping of an interarea mode. The time-domain simulation results confirm that the prediction of the best PSS location by the SPE method is correct and accurate. >

A load frequency control algorithm based on a generalized approach

A generalized approach to load frequency control that combines discontinuous control and dual-mode control and uses variable-structure-systems concepts is developed. Using this approach, a novel load-frequency control algorithm is proposed. Studies on a multi-area power system, including generation rate constraint and governor dead-band, demonstrate the effectiveness of the control scheme. >

Application of an inverse input/output mapped ANN as a power system stabilizer

An artificial neural network (ANN), trained as an inverse of the controlled plant, to function as a power system stabilizer (PSS) is presented in this paper. In order to make the proposed ANN PSS work properly, it was trained over the full working range of the generating unit with a large variety of disturbances. Data used to train the ANN PSS consisted of the control input and the synchronous machine response with an adaptive PSS (APSS) controlling the generator. During training, the ANN was required to memorize the reverse input/output mapping of the synchronous machine. After the training, the output of the synchronous machine was applied as the input of the ANN PSS and the output of the ANN PSS was used as the control signal. Simulation results show that the proposed ANN PSS can provide good damping of the power system over a wide operating range and significantly improve the system performance. >

Damping of multi-modal oscillations in power systems using a dual-rate adaptive stabilizer

The ability of a dual-rate adaptive stabilizer to damp multimode oscillations in a power system is investigated. The controller adjusts its parameters to track the dominant frequency of oscillation and damps different modes one by one according to their dominance. The results show that adaptive and conventional stabilizers working on different units within a system can operate cooperatively and mutually support each other. >

A self-tuning controller for the control of multi-machine power systems

An adaptive synchronous machine controller that minimizes a cost function incorporating system input, output, and set-point variations, and its application to a multimachine power system are described. The control is based on a criterion of automatically shifting the closed loop poles of the system towards the origin in the z-domain without violating the control constraints. It possesses the property of robustness and ease of reference signal tracking. The ability of the proposed controller to damp multimode oscillations is investigated. Studies show that the proposed controller cooperates with the conventional power-system stabilizers on the system in damping the oscillations. >