Abstract
Problems related to power system operation and control are complex and time consuming because of the non-linearities involved in their formulation and solution. Fast solutions to these problems can be obtained only through parallel processing. Neural nets provide massive parallel processing facilities and may also be used efficiently to model systems with non-linearities. The capabilities of neural nets can, therefore, be well utilized in modelling and processing problems related to power systems. In order to reduce the burden on computers, algorithms involving optimization and complex equations can be converted to heuristics. These heuristics can then be represented in terms of rules and an expert system can be built, with the added advantage of obtaining solutions in a time intensive fashion. This paper studies the application of neural nets to problem solving in power system operation and control, and demonstrates how present methods for solving such problems can be converted to the neural net approach.
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