Bidirectional iteration parallel probability load flow calculation method combining Latin hypercube sampling

Abstract

The invention discloses a bidirectional iteration parallel probability load flow calculation method combining Latin hypercube sampling. The method includes: using a Latin hypercube sampling method to sample new energy power generating power variables according to the accumulation distribution function of the new energy power generating power variables, and building the sample matrix of the new energy power generating power variables; aiming at the partitionable feature of a power grid, using a branch cutting and node tearing method to concentrate the power grid into meshes, and building a bidirectional iteration parallel load flow calculation model; using the sample matrix of the new energy power generating power variables as the input variable of the bidirectional iteration parallel load flow calculation model to perform probability load flow calculation so as to obtain the discrete result of output variables, and using kernel density estimation to fit the discrete result of the output variables to obtain the probability density function of the output variables. The method has the advantages that the Latin hypercube sampling is combined with the bidirectional iteration parallel load flow algorithm based on the concentrated meshes, sampling number is reduced, and parallel probability load flow calculation is achieved.

Description

Technical field [0001] The invention belongs to the field of power system analysis, and specifically relates to a two-way iterative parallel probability power flow calculation method combined with Latin hypercube sampling. Background technique [0002] New energy power generation, such as wind power and photovoltaic power generation, has gradually attracted attention due to the increasing maturity of its power generation technology and huge environmental effects. However, due to its own randomness, if a large number of power grids are connected to the power grid, the uncertainty of the power grid will be aggravated and the power grid will suffer Safe operation brings risks. The traditional deterministic power flow calculation method can only reflect the steady-state operating conditions of the power system under certain certain working conditions, and cannot be used for the analysis of scenarios that take into account uncertain factors. The probabilistic power flow calculation me...

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Problems solved by technology

The point estimation method is an approximate solution method. Although the speed is fast and the expectation and variance precision of the output variable is high, the high-order moment error of the output variable is large and it is difficult to obtain the probability distribution of the output variable; analytical methods include Fast Fourier Transformation method, semi-invariant method, and first-order second-order moment method, although the calculation speed is fast, but the accuracy is not as high as the simulation method. The representative of the simulation method is the Monte Carlo simulation method. The traditional Monte Carlo simulation method uses random sampling technology to extract input Variable samples, after multiple deterministic power flow calculations, the probability distribution of output variables is obtained, which has high accuracy but takes a long time

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