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Artificial Intelligence Applications in Power Systems, IEE Colloquium on

Date 20 Apr 1995

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Displaying Results 1 - 5 of 5
  • Developments of artificial intelligence techniques for voltage control

    Page(s): 2/1 - 2/6
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (296 KB)  

    The authors review the developments in artificial intelligence techniques for power system voltage control. They discuss: expert systems; artificial neural nets; hybrid systems of expert systems and neural nets; fuzzy control; and genetic algorithms. The advantages of these technologies as well some of the drawbacks are discussed View full abstract»

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  • Genetic algorithms in power system planning and operation

    Page(s): 5/1 - 5/3
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (228 KB)  

    Effective optimal power system planning and operation is limited by: (i) the high dimensionality of power systems; and (ii) the incomplete domain dependent knowledge of power system engineers. The first limitation is addressed by numerical optimisation procedures using gradient approximations to calculate the search directions in various nonlinear programming formulations or by linear programming solutions to imprecise models. The advantages of such methods are in their mathematical underpinnings, but disadvantages exist also in the sensitivity to problem formulation, algorithm selection and undue focus on local minima. Here, the author examines the use of genetic algorithms in addressing the above problems View full abstract»

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  • Advantages for power system operation using a neural network based adaptive single pole autoreclosure relay

    Page(s): 4/1 - 4/7
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (344 KB)  

    The use of adaptive single pole autoreclosure on EHV transmission lines can provide clear benefits to the utility, particularly when included in an autoreclosure scheme. These benefits are described, and the implications on system performance are discussed View full abstract»

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  • Expert systems and model based reasoning for protection performance analysis

    Page(s): 1/1 - 1/4
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (220 KB)  

    This paper discusses an expert system based decision support system (DSS) for protection system performance analysis. The DSS interprets data from the supervisory, control and data acquisition (SCADA) system, plus the data captured by fault recorders and modern relays with inbuilt fault recording capabilities. Within this DSS both knowledge based and model based reasoning are utilised. Given the role of protection engineers within a utility, this DSS aims to provide them with information extracted from the voluminous data available during power system disturbances View full abstract»

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  • Neural network and its ancillary techniques as applied to power systems

    Page(s): 3/1 - 3/6
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (348 KB)  

    The layered perceptron neural net is receiving the most attention as a viable candidate for application to power systems. The layered perceptron is taught by example. Before neural networks can gain the necessary recognition as useful problem solving tools in the power industry, certain fundamental issues need to be addressed. Some of them are associated with neural network technology, and others are problem dependent. The author discusses the following issues: learning versus memorisation; best net size determination, network saturation, feature extraction, neural net inversion, genetic based neural nets, and fuzzified neural nets View full abstract»

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