Stochastic Modeling of a DFIG Wind Turbine in Matpower

Abstract

One of the main trends in the electric power industry is the use of green energy – renewable energy sources (RES), especially wind power generation. The penetration of large wind turbine (WT) power capacity leads to changes in the topology and characteristics of electric power systems (EPS), which can cause an increase the likelihood of emergency processes and a decrease in the steady-state and transient EPS stability. The issue arises in ensuring the EPS stability with RES units, especially in the case of large disturbances. The main way to solve this issue is mathematical modeling. However, almost all the main currently used software programs are based on deterministic methods for calculating EPS processes, which are not able to consider all possible state uncertainties. To reliably determine all possible states of the system in which it can be, it is necessary to determine in a non-deterministic form how the values in the nodes and branches will be distributed. The peculiarity of this paper is associated with the use of a set of approaches to increase the accuracy of the results obtained: the approximation method in combination with two goodness-of-fit criteria for wind; the SIBD method, which generates the required probability density without loss of density values; and the controlled discretization of input variables. This paper assumes the formation of a WT stochastic model to study the impact of RES on stability in a non-deterministic form using the example of IEEE standard bus systems in the Matpower program.

Keywords

• Wind turbine
• wind speed time series
• probability density function
• cumulative distribution function
• power system stability
• numerical simulation