Network Planning Using Iterative Improvement Methods and Heuristic Techniques

Abstract

The problem of minimum-cost expansion of power transmission network is formulated as a genetic algorithm with the cost of new lines and security constraints and Kirchhoff’s Law at each bus bar included. A genetic algorithm (GA) is a search or optimization algorithm based on the mechanics of natural selection and genetics. An applied example is presented. The results from a set of tests carried out on the prototype show that the application of GA techniques is feasible in transmission network planning. An empirical analysis of the effects of the parameters of the algorithm is also presented in the context of this novel application. Existing mathematical programming, heuristic techniques, artificial intelligence (AI) and iterative improvement methods are also reviewed briefly.