Probabilistic power flow data acquisition method based on renewable energy uncertainty

Abstract

The invention discloses a probabilistic power flow data acquisition method based on renewable energy uncertainty. The method comprises steps of S1 inputting a data file of electric parameters of a power grid and configuring random parameters of the power grid; S2, carrying out AC power flow calculation and probabilistic power flow calculation, and outputting MCS sampling scale, bus independent variable parameters and line independent variable parameters; S3, configuring a network equipment interval, including a bus voltage amplitude interval, a line load rate interval, and a transformer load rate interval; S4, utilizing the kernel density estimation to obtain the evaluation result of the utilization ratio of the electrical equipment; The invention can fully consider a plurality of uncertain factors of a power network, establishes a calculation program for estimating a power network power flow based on a probabilistic power flow method of Monte Carlo simulation, applies the program to apractical transmission system, analyzes a power network capacity level and a load rate, etc., and better guides the planning and evaluation of the power network.

Description

technical field [0001] The invention relates to a computer technology-based probabilistic power flow acquisition data acquisition method under the uncertainty of renewable energy sources. Background technique [0002] As a convenient and fast secondary energy, electric energy plays an extremely important role in social development and human life, and electric energy is mainly converted from primary energy such as coal and oil. With the continuous development of the economy, the demand for energy is also gradually increasing. Due to its non-renewable characteristics, the traditional fossil fuels dominated by coal are facing the plight of gradual depletion, and the continuous use of fossil fuels has caused serious pollution to the environment. The shortage of traditional non-renewable energy sources and serious environmental pollution have become serious obstacles to the development of electric power. Therefore, finding clean and efficient renewable energy to replace traditio...

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Problems solved by technology

[0025] Convolution calculation is relatively complicated. If the model of the system is large and the number of input variables is large, the convolution calculation will be quite time-consuming. Therefore, in order to reduce the time of traditional convolution calculation, some scholars have proposed a series of transformation methods. It is used to improve traditional convolution calculations, such as Laplace transform, Fourier transform and fast Fourier transform. Although these transformation methods have been used to improve traditional convolution calculations, the calculation speed has been improved to a certain extent. , but the computational efficiency is still not high

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