The problem of minimising the technical energy losses in electric power distribution systems corresponds to the definition of the best network configuration, through the manipulation of sectionalising switches. Using a graph terminology, we have a combinatorial optimisation problem, whose solution asks for the definition of the minimum spanning tree for the network. With the purpose of treating the case of time-varying profiles of energy requirements, this paper presents the first results obtained with the application of learning classifier systems, an evolutionary computation approach to find network configurations close to the one associated with minimum energy losses. Its uttermost feature is the possibility of application to on-line network supervision, proposing new configurations that will reduce the level of energy losses when significant demand variations are detected.
Power distribution; loss minimisation; time-varying demand; learning classifier systems; evolutionary computation
