Distribution network reinforcement planning in uncertain environment using stochastic multi-attribute utility analysis

Abstract

This paper considers a stochastic multiple criteria decision-making problem in power distribution system reinforcement planning. The problem with exhaustive set of alternatives, with different types of trade-offs among stochastic criteria, has been solved using the novel analytical methodology. The proposed methodology is based on discrete convolution of criteria probability distribution functions and OWA operators, modelling different types of criteria aggregation. After the new, aggregated probability distributions have been built for every alternative, they are ranked by the overall expected utility. The methodology allows the usage of compensatory aggregation, which is more suitable for conflicting criteria or the human aggregation behaviour. Finally, an example of decision on the network reinforcement of IEEE 34 bus test feeder illustrates the efficiency of this method.