A genetic based fuzzy approach to optimisation of electrical distribution networks

Electrical distribution networks are built as interconnected meshed networks, while in the operation they are arranged into radial, tree structures. The network configuration problem is to find a radial operating structure that optimises the network performance while satisfying operating constraints. In fact, this problem call be viewed as the problem of determining an 'optimal' tree of the given graph. The problem is usually formulated as a constrained multi-objective combinatorial problem that belongs to the class of very large non-linear mixed-integer problems. In this paper a fuzzy co-ordination technique is used to identify overall degree of satisfaction, while GA is employed to maximise it. The major difficulty in the application of GA to this problem is that crossovers normally generate infeasible solutions, as random combination of parts of different trees of the same graph do not create a new three of that graph. The constraints are enforced by adjusting the new string to the 'nearest' three which is, in terms of GA, adequate with performing 'mutation' at each crossover. The results obtained by the proposed algorithm are compared with the previously developed 'greedy' algorithms on a slightly changed real distribution system, showing that GA has a potential to address some other planning and operation problems in electrical distribution systems.