Internal power allocation strategy of multi-type energy storage power stations based on improved NSGA- II

In order to improve the rationality of power distribution of multi-type new energy storage system, an internal power distribution strategy of multi-type energy storage power station based on improved non-dominated fast sorting genetic algorithm is proposed. Firstly, the mathematical models of the operating cost of energy storage system, the health state loss of energy storage units and the consistency of the state of charge of energy storage system are established. Finally, under the constraints of system power balance and SOC upper and lower limits, aiming at the problems of artificial selection of target weight of traditional optimization algorithm and local convergence of conventional NSGA- II algorithm, the normal distribution crossover operator is introduced into NSGA- II algorithm, and the global search ability of the algorithm is enhanced by NDX operator to optimize the best power grid planning scheme. The analysis of an example shows that this strategy can effectively reduce the charge and discharge times of battery cells, reduce the capacity loss of battery cells, and ensure the SOC consistency of energy storage system.