Probability box theory-based uncertain power flow calculation for power system with wind power

Abstract

The uncertainty of wind speed may lead to the deviation and change of wind power output, which influences the stability of wind farm. Therefore, in this paper, a probability box (p-box) based uncertain power flow model for wind power is proposed, which initially introduces p-box to power flow calculation. A probabilistic interval power flow model with both probability and interval is established. Firstly, the drift interval of wind speed is obtained and its p-box model is established by analyzing the distribution of wind speed. Secondly, the wind power output p-box is derived from the wind speed p-box based on the relationship between wind power output and wind speed, then the p-box of wind power output is discretized and introduced into the power flow equation to obtain the power flow p-box model. Finally, Newton–Raphson method is used to solve the power flow p-box model. Experiments on data collected from a wind farm (running standard IEEE30-bus test system) in Inner Mongolia demonstrate that our method is more effective and accurate than the traditional Monte Carlo simulation (MCS) and classical interval power flow (IPF) method.

Research on Wind Power Short-Term Forecasting Method Based on Temporal Convolutional Neural Network and Variational Modal Decomposition

“…Wind energy, as a renewable energy source with abundant energy storage, is an important part of the worldwide efforts to promote clean energy development and a sustainable energy path [ 1 , 2 ]. In recent years, with the development of power generation technology, wind power has become an important source of electric energy in various countries.…”

“…However, the fluctuating, intermittent, and random nature of wind energy leads to severe difficulties in the grid-connected operation of a high percentage of wind power. These could cause the wasting of wind energy and even lead to significant safety hazards in the power system [ 1 , 2 , 3 ]. Therefore, it is of great significance to accurately predict the wind power and reduce the impact of randomness and intermittence of the wind farm on the power system in the process of wind power grid connection.…”