Application of Artificial Intelligent Tools to The Transmission Expansion Problem

The purpose of transmission expansion problem (TEP) is to determine the timing and type of new transmission facilities. The TEP has been formulated as an optimization problem. The objective was to minimize the transmission investment costs that handle the increased load and the additional generation requirements in terms of line additions and power losses. Several constraints were considered including the power flow on the network lines, the right-of-way's validity and its maximum line addition. The TEP was then solved using artificial intelligence (AI) tools such as the genetic algorithm, Tabu search and artificial neural networks (ANNs) with linear and quadratic programming models. The effectiveness of the AI methods in dealing with small and large-scale systems was tested through the applications of a six-bus system, the IEEE-24 bus network and a Saudi Arabian network. The hybridization of GA, TS and ANN has several features. Its results confirm that it is superior in dealing with a large-scale problem in which the size of the search spaces increases exponentially with the dimension of the network