Method for obtaining optimal planning of transmission grid under new energy access

Abstract

The invention discloses a method for obtaining optimal planning of the transmission grid under new energy access. The method comprises steps that a transmission network planning model containing the new energy is established; a corresponding transmission network grid structure is established according to individual particles of the EPSO particle swarm optimization algorithm for the transmission network planning model; the transmission grid network structure is repaired to ensure the transmission network grid structure connected; the probabilistic DC power flow method is utilized to obtain thepower flow of each branch of the transmission network grid corresponding to the individual particles, and the individual particles which do not meet constraints of the transmission network planning model are determined; a fitness function value is calculated, and the adaptive strategy is utilized to select the optimal PSO strategy for multiple iterations to obtain the globally optimal individual particles; the globally optimal individual particles are transformed to form an optimal configuration scheme for transmission network planning. The method is advantaged in that the generalization ability and robust performance of the calculation process are enhanced, and the high-precision high-guided optimal configuration scheme for planning of the transmission network grid structure under new energy access can effectively obtained.

Description

technical field [0001] The invention belongs to the technical field of power transmission network, and in particular relates to a method for obtaining the optimal planning of power 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 intermittency of new energy power generation, the transmission network under the access of new energy has more uncertainty, so the traditional deterministic transmission network planning model and optimization method are no longer applicable. [0003] Under the premise of satisfying the safe and reliable operation of the system, traditional power grid planning is based on a certain power supply planning scheme, aiming to meet a certain level of predicted load, and planning with the objective function of minimizing the construction cost and operating cost. ...

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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