An optimal configuration method for transmission network planning under the access of new energy

Abstract

The invention discloses an optimal configuration method for transmission network planning under new energy access, comprising the steps of: establishing a transmission network planning model containing new energy; establishing a corresponding population individual of the transmission network planning model according to the NSGA‑III optimization algorithm The grid structure of the transmission network; repair the grid structure of the transmission network to ensure the connectivity of the grid structure of the transmission network; use the probabilistic DC power flow method to obtain the power flow of each branch of the transmission network grid corresponding to the population individual, and judge that the correction does not meet the requirements of the transmission network. The population individuals under the constraints of the network planning model are obtained through multiple iterations to obtain the final population individuals; the final population individuals are transformed into an optimal configuration scheme. The invention plans the grid structure of the transmission network under the access of new energy sources; the adopted NSGA-III optimization algorithm reduces the computational complexity of the algorithm, expands the sampling space, and at the same time better maintains the diversity among population individuals .

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more uncertainties, so the traditional deterministic transmission network planning model and optimization methods are no longer applicable.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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