摘要:

The basic idea of model-based diagnosis is to exploit knowledge about the structure and behaviour of the physical system to be diagnosed in order to identify diagnoses from discrepancies between observed and predicted behaviour. In this paper, we describe the application of model-based diagnosis to the problem of fault localisation in power transmission networks. We also show that the resulting system, DPNet, has an extended competence w.r.t. rule-based approaches (treatment of unknown and multiple faults) while requiring less development effort because of the use of component libraries in the model-based approach.

DOI:10.1049/ise.1993.0002

出版商:IEE    

年代:1993

数据来源: IET

摘要:

We have implemented a real-time expert system as part of a supervisory control and data acquisition system for the Public Utilities Board of Singapore, controlling its 22 kV distribution network. It works as an operator support tool by diagnosing network disturbances and device malfunctions, and by presenting a switching sequence which can be executed immediately to restore supply. In this paper we describe how the expert system is integrated into a large supervisory control and data acquisition system for power distribution networks. The necessary techniques to cover on-line processing of real-time data, intelligent alarm processing and network reconfiguration/restoration are discussed. The expert system is based on a hierarchic multi-level problem-solving architecture, integrating model-based, heuristic and algorithmic techniques acting on an object-oriented data structure. Techniques such as the automatic creation and update of the knowledge base, event filtering, on-line event processing, and structural and temporal focusing have been implemented to enable the system to perform its task on-line and in real time.

DOI:10.1049/ise.1993.0003

出版商:IEE    

年代:1993

数据来源: IET

摘要:

In this paper we describe a learning classifier system (LCS) which employs genetic algorithms (GA) for adaptive on-line diagnosis of power transmission network faults. The system monitors switchgear indications produced by a transmission network, reporting fault diagnoses on any patterns indicative of faulted components. The system evaluates the accuracy of diagnoses via a fault simulator developed by National Grid Co. and adapts to reflect the current network topology by use of genetic algorithms.

DOI:10.1049/ise.1993.0004

出版商:IEE    

年代:1993

数据来源: IET

摘要:

Power transmission network design is a promising application area for artificial intelligence techniques. Recently, several attempts have been made to integrate conventional numerical algorithms with more ambitious decision support systems. In this paper, we present SELF, a knowledge-based system supporting a specific task in power transmission network design known as ‘load-flow analysis’. SELF is the result of long-term co-operation in this field between CISE and the Electric Research Centre of ENEL (the Italian Electricity Board). It integrates a heuristic search approach to the design task with conventional numerical algorithms within the framework of a ‘propose-critique-modify’ design methodology. The aim of the sytem is to help the designer interpret numerical results and take design decisions. SELF has been tested on networks of significant size (up to 420 nodes and 600 connections) and is currently used by ENEL researchers.

DOI:10.1049/ise.1993.0005

出版商:IEE    

年代:1993

数据来源: IET

摘要:

A comparative performance of rule-based and fuzzy logic-based power system stabilisers is described in this paper. The stabilising signal in these stabilisers is computed using two parameters depending on the speed/acceleration state of the generator in the phase plane. The required measurement is the speed deviation. The comparison of different stabilisers is demonstrated by a practical implementation using a digital signal processor mounted on a PC-AT. Results of experimental tests on a physical model of a simple power system are presented.

DOI:10.1049/ise.1993.0006

出版商:IEE    

年代:1993

数据来源: IET