Multiobjective genetic algorithm for demand side management of smart grid

Demand side management is one of the most effective methods to control the usage of energy so as to achieve reliability and sustainability in the smart grid. Conventional methods for generating the management scheme are generally based on one objective, which represents only the requirements of energy suppliers or only the energy consumers. In this paper, a multiobjective genetic algorithm (GA) is proposed for extending the optimization problems by considering the objectives from the two conflicting groups and some compromise solutions are provided. The performance of the multiobjective GA is compared with its single objective version by three different cases. The results show that the solutions obtained by the multiobjective GA are more reasonable and better solutions for a single objective can even be found.