An Efficient Calculation Method of Probabilistic Power Flow with High Dimensional Related Uncertainty Sources Based on Improved Nataf Transform

Abstract

The invention discloses an improved Nataf transform-based probabilistic load flow efficient calculation method containing a high-dimensional correlation uncertainty source. The method mainly comprisesthe steps of 1) determining a random input variable X and a Pearson correlation coefficient matrix CX of a load flow calculation model; 2) determining an n-dimensional standard normal distribution variable Z and a Pearson correlation coefficient matrix CZ corresponding to the random input variable X; 3) generating an n-dimensional independent random variable G obeying standard normal distribution; and 4) calculating to obtain a variable Z of a standard normal domain with correlation; and 5) converting the variables which have correlation and obey standard Gaussian distribution into original domain variables with correlation; 6) establishing a deterministic probabilistic power flow model; 7) calculating the numerical range of each dimension of the generated sample Xinput, and generating aconfiguration point; and 8) completing PPF calculation to obtain output W'output of PPF calculation. According to the method, a large-scale power grid containing high-dimensional linear correlation random variables can be analyzed, and probabilistic load flow calculation and analysis are carried out at a high-precision and high-speed calculation speed.

Description

technical field [0001] The invention relates to the field of grid-connected new energy sources, in particular to an efficient calculation method for probabilistic power flow with high-dimensional related uncertain sources based on improved Nataf transformation. Background technique [0002] In recent years, mankind's pursuit of a clean environment and lifestyle has promoted the rapid development and widespread utilization of renewable energy. According to the 2018 annual report of REN 21, throughout 2017, renewable energy generation accounted for 26.5% of the total global electricity production, of which hydropower and wind power accounted for 16.4% and 5.6%, and the remaining 4.5% included biomass, Photovoltaic, marine power generation, etc. However, due to the obvious randomness of primary energy sources such as wind speed, solar radiation, and tidal flow velocity, a large number of probabilistic sources of uncertainty will be introduced into modern power systems. This l...

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Problems solved by technology

[0005] The first thing to be clear is that a power system with high-dimensional random variables must be a very large-scale network, and its deterministic power flow calculation itself is very time-consuming

After applying its deterministic model to PPF calculation, since PPF needs to generate a large number of samples, each set of samples needs to be transmitted through the deterministic model, so the PPF calculation for large power grids is also extremely time-consuming

However, when analyzing the operation of large power grids, the PPF analysis based on the original deterministic model of the network can hardly meet the required computational efficiency, cannot accurately analyze the network's operating status, and cannot detect potential threats to the network in time

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