Multi-objective design and control of hybrid systems minimizing costs and unmet load

This paper presents, for the first time, the application of the strength Pareto evolutionary algorithm to the multi-objective design of isolated hybrid systems, minimising both the total cost throughout the useful life of the installation and the unmet load. For this task, a multi-objective evolutionary algorithm (MOEA) and a genetic algorithm (GA) have been used in order to find the best combinations of components for the hybrid system and control strategy. Also, a novel control strategy has been developed and it will be expounded in this article. As an example of application, a PV–wind–diesel system has been designed, obtaining a set of possible solutions (Pareto set) from which the designer can choose those which he/she prefers considering the costs and unmet load of each. The results obtained demonstrate the practical utility of the design method used.