Multi-objective optimal scheduling for DC microgrid systems

In order to improve the economy of DC microgrid operation and battery service life, a multi-objective joint optimization model for DC microgrid is established, which integrally considers factors such as power generation cost, power purchase cost, power sales revenue, power balance constraints, charging and discharging time constraints, and so on. In addition, the corresponding model solving algorithm based on particle swarm algorithm is given. The validity of the proposed model and algorithm is verified. Finally, the superiority of the particle swarm optimization algorithm is demonstrated through experiments, and its daily operating cost is 11% lower than that of the genetic algorithm.