An optimization method for transmission network planning under new energy access based on single objective

Abstract

The invention discloses an optimization method for transmission network planning based on single-objective new energy access, comprising the steps of: building a multi-objective transmission network planning model containing new energy, and converting it into a single-objective function by selecting weight coefficients; According to the particle individual of the EPSO optimization algorithm, the corresponding transmission network topology structure is built and repaired, so that the transmission network network topology is connected; the power flow of each branch of the transmission network network corresponding to the particle individual is obtained by using the probabilistic DC power flow method, and the correction cannot be judged. Particle individuals that meet the constraints of the transmission network planning model; according to the single objective function, use an adaptive strategy to select a PSO strategy with a higher success rate for multiple iterations to obtain the optimal global particle individual, and obtain a planning scheme. The invention solves the uncertainty information modeling of the probability of risk occurrence, realizes the topology structure planning of the transmission network network under the condition of controlling the overload risk, and enhances the optimal performance of the algorithm.

Description

technical field [0001] The invention belongs to the technical field of transmission network, and in particular relates to an optimization method for transmission network planning based on single-objective new energy access. Background technique [0002] In terms of forecasting, planning, and evaluation of the power system, the grid connection of large-scale new energy has brought great challenges. With the increase of new energy grid-connected installed capacity, its random fluctuation characteristics, anti-peaking characteristics and other characteristics put forward higher requirements for the overall operation stability, safety and overall economy of the power system. Among them, the main challenge to the planning of the transmission network is the impact on the power flow distribution of the transmission network. The output of new energy sources such as wind power and photovoltaics has random fluctuations, which will indirectly lead to changes in the size and direction ...

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.

The existing transmission network planning method with new energy access cannot avoid the uncertainty of the probability of risk occurrence, and cannot plan the transmission network under the condition of controlling the risk of overload, and the optimization performance is poor

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