Tutorial On Evolutionary Techniques And Fuzzy Logic In Power Systems
ISBN: 978-1-4244-6112-7
Year Published: 2000
Pages: 55
This tutorial presents an application of Evolutionary Computation to the problem of dynamic security assessment. This also overviews applications of fuzzy logic in power systems.
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Presents an application of Evolutionary Computation to the problem of dynamic security assessment. EC can be developed to enhance the accuracy of partially trained multilayer perceptron neural networks in specific operating regions. The technique is based on query learning algorithms and evolutionary-based boundary marking algorithm to evenly spread points on a power system security boundary. These points are then presented to an oracle (i.e, simulator) for validation. This also overviews the applications of fuzzy logic in power systems. Emphasis is placed on understanding the types of uncertainties in power system problems that are well-represented by fuzzy methods. The fuzzy inference engine is the foundation of most fuzzy expert systems and control systems. From a linguistic description of cause and effect of a process, a fuzzy inference engine can be designed to emulate the process.
