A method for obtaining optimal planning of transmission network under new energy access

Abstract

The invention discloses a method for obtaining the optimal planning of the transmission network under the access of new energy, which includes the steps of establishing a transmission network planning model containing new energy; and establishing a corresponding particle individual of the transmission network planning model according to the EPSO particle swarm optimization algorithm. The grid structure of the transmission grid; repair the grid structure of the transmission grid to ensure the connectivity of the grid structure of the transmission grid; use the probabilistic direct current flow method to obtain the power flow of each branch of the grid grid corresponding to the particle individual, and judge that the correction does not meet the requirements of the transmission network. Particle individuals under the constraints of the network planning model; solve the fitness function value, use the adaptive strategy to select the optimal PSO strategy for multiple iterations to obtain the globally optimal particle individual; transform the globally optimal particle individual to form the optimal transmission network planning Optimal configuration scheme. The invention enhances the generalization ability and robust performance of the calculation process, and can effectively obtain a high-precision, high-directive optimal configuration scheme for planning the grid structure of the transmission network under the access of new energy.

Description

technical field [0001] The invention belongs to the technical field of transmission network, and in particular relates to a method for obtaining optimal planning of transmission network 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more uncertainties, so the traditional deterministic transmission network planning model and optimization methods are no longer applicable.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 cons...

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 sort, 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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