Optimal configuration method for power transmission network planning under new energy access

Abstract

The invention discloses an optimal configuration method for power transmission network planning under new energy access. The method comprises the following steps of: establishing a power transmissionnetwork planning model containing new energy, establishing a corresponding power transmission network frame structure for the power transmission network planning model according to population individuals of an NSGA-III optimization algorithm, repairing the grid structure of the power transmission network to ensure that the grid structure of the power transmission network is communicated, acquiringthe power flow of each branch of the power transmission network frame corresponding to the population individuals by adopting a probabilistic direct current power flow method, judging and correctingthe population individuals which do not meet the constraint conditions of the power transmission network planning model, and acquiring the final population individuals through multiple iterations, andconverting the final population individuals into an optimal configuration scheme. The method plans the power transmission network frame structure under new energy access, and by adopting the NSGA-IIIoptimization algorithm, the calculation complexity of the algorithm is reduced, the sampling space is expanded, and meanwhile, the diversity among population individuals is well maintained.

Description

technical field [0001] The invention belongs to the technical field of transmission network, and in particular relates to an optimal configuration method of transmission network planning under the access of new energy. Background technique [0002] With the energy crisis and global climate change issues, new energy (wind power, etc.) power generation has become increasingly popular. Due to the randomness and intermittent nature of new energy power generation, the transmission network under the access of new energy has more uncertainties, so the traditional deterministic transmission network planning model and optimization methods are no longer applicable. [0003] Under the premise of satisfying the safe and reliable operation of the system, the traditional power grid planning is based on the determined power supply planning scheme, with the purpose of meeting a certain level of predicted load, and the planning is carried out with the objective function of minimizing the con...

AI Technical Summary

Problems solved by technology

The GA algorithm is computationally complex, unstable, and prone to local convergence; the PSO algorithm contains different PSO variants with complementary capabilities, and has strong randomness; NSGA-II is for two solutions with the same non-dominated sorting, in a smaller crowded area The solution is better, and the secondary population generated by the basic operation of the genetic algorithm is repeatedly selected from the parent population until the conditions are met. The NSGA-II algorithm is more complicated, and the convergence of the results needs to be improved.

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