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

A technology of probabilistic power flow calculation and Latin hypercube, which is applied to AC network circuits, electrical components, circuit devices, etc., can solve problems such as difficulty in obtaining output variables, long time consumption, and large error in high-order moments of output variables, so as to achieve parallel probability Power flow calculation, the effect of reducing the number of samples

Inactive Publication Date: 2015-07-29
SOUTHEAST UNIV
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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

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

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[0025] Such as figure 1 with figure 2 As shown, the two-way iterative parallel probability power flow calculation method combined with Latin hypercube sampling of the present invention includes the following steps:

[0026] 1) According to the cumulative distribution function of the new energy generation power variables, the Latin hypercube sampling method is used to sample the new energy generation power variables to establish a sample matrix of the new energy generation power variables.

[0027] Assuming random variable X 1 ,X 2 ,...X K For K new energy generation power variables, for random variables X k (k=1,2,...,K), its cumulative distribution function is F k (x).

[0028] (1) Sampling

[0029] First, the random variable X k Cumulative distribution function F k The value interval [0, 1] of (x) is divided into N equal parts to generate N sub-intervals (s=1,2,...,N), and then in each subinterval (s=1, 2,...,N) choose the midpoint or randomly pick a point Finally, according to t...

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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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Application Information

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IPC IPC(8): H02J3/00
CPCH02J3/00H02J2203/20
Inventor 喻洁仇式鹍梁峻恺梅军
Owner SOUTHEAST UNIV
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