Intelligent Data Analysis in Electric Power Engineering Applications

  • V. P. AndrovitsaneasEmail author
  • K. Boulas
  • G. D. DouniasEmail author
Part of the Intelligent Systems Reference Library book series (ISRL, volume 149)


This chapter presents various intelligent approaches for modelling, generalization and knowledge extraction from data, which are applied in different electric power engineering domains of the real world. Specifically, the chapter presents: (1) the application of ANNs, inductive ML, genetic programming and wavelet NNs, in the problem of ground resistance estimation, an important problem for the design of grounding systems in constructions, (2) the application of ANNs, genetic programming and nature inspired techniques such as gravitational search algorithm in the problem of estimating the value of critical flashover voltage of insulators, a well-known difficult topic of electric power systems, (3) the application of specific intelligent techniques (ANNs, fuzzy logic, etc.) in load forecasting problems and in optimization tasks in transmission lines. The presentation refers to previously conducted research related to the application domains and briefly analyzes each domain of application, the data corresponding to the problem under consideration, while are also included a brief presentation of each intelligent technique and presentation and discussion of the results obtained. Intelligent approaches are proved to be handy tools for the specific applications as they succeed to generalize the operation and behavior of specific parts of electric power systems, they manage to induce new, useful knowledge (mathematical relations, rules and rule based systems, etc.) and thus they effectively assist the proper design and operation of complex real world electric power systems.


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Authors and Affiliations

  1. 1.High Voltage Laboratory, School of Electrical and Computer EngineeringNational Technical University of AthensAthensGreece
  2. 2.Management & Decision Engineering Lab, Department of Financial and Management EngineeringUniversity of the AegeanChiosGreece

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