Probabilistic load flow calculation of AC/DC hybrid system based on cumulant method

TL;DR

This paper introduces a probabilistic load flow method based on cumulant calculations for AC/DC hybrid power systems with renewable sources, enhancing speed and accuracy in uncertainty analysis.

Contribution

It proposes a novel cumulant-based probabilistic load flow method tailored for AC/DC hybrid systems with renewable energy, improving computational efficiency and convergence.

Findings

Accurately models uncertainty of renewable energy sources.

Reduces computational complexity compared to traditional methods.

Demonstrates effectiveness on IEEE test systems.

Abstract

The operating conditions of the power system have become more complex and changeable. This paper proposes a probabilistic load flow based on the cumulant method (PLF-CM) for the voltage sourced converter high voltage direct current (VSC-HVDC) hybrid system containing photovoltaic grid-connected systems. Firstly, the corresponding control mode is set for the converter, including droop control and master-slave control. The unified iterative method is used to calculate the conventional AC/DC flow. Secondly, on the basis of the probability model of load and photovoltaic output, based on the aforementioned flow results, use correlation coefficient matrix of this paper will change the relevant sample into independent sample, the cumulants of the load and photovoltaic output are obtained; then, the probability density function (PDF) and cumulative distribution function (CDF) of state variables are obtained by using Gram-Charlie series expansion method. Finally, the mean value and standard deviation of node voltage and line power are calculated on the modified IEEE 34-bus and IEEE 57-bus transmission systems. The algorithm can reflect the inherent uncertainty of new energy sources, and replace the complex convolution operation, greatly improving the calculation speed and the convergence.