Method for optimizing transmission grid planning based on single-objective new energy access

Abstract

The invention discloses a method for optimizing the transmission grid planning based on single-objective new energy access, including the steps of: constructing a multi-objective transmission grid planning model containing new energy, and transforming the model into a single-objective function through a selected weight coefficient; according to the particle individuals of an EPSO optimization algorithm, constructing and repairing a corresponding transmission grid network topology structure, so that the transmission grid network topology structure is connected; using a probabilistic DC power flow method to obtain the power flow of each branch of the transmission grid network corresponding to the particle individuals, and determining and correcting the particle individuals that cannot satisfy the constraints of the transmission grid planning model; according to the single-objective function, using an adaptive strategy to select a PSO strategy with a higher success rate each time for iteration multiple times to obtain the optimal global particle individuals to obtain a planning solution. The method solves the uncertainty information modeling of the risk occurrence probability, realizes the transmission grid network topology planning under the condition of controlling an 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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