Dynamic Equivalent Modeling for Wind Farms With DFIGs Using the Artificial Bee Colony With K-Means Algorithm

Xiaohui Wang,Zhemeng Zhang,Hao Yu,Yong Lin,Xianfu Gong

doi:10.1109/access.2020.3024212

Abstract

With the increasing penetration of wind power, it is recognized that wind power will have a greater and greater impact on the planning and operation of the original power system. And the detailed modeling of wind farm with doubly-fed induction wind generator (DFIG) will require large storage and computation resources, which poses technical challenges for equivalent modeling of wind farm. In this paper, a multi-machine dynamic equivalent modeling method for wind farms with DFIGs is proposed. First, the artificial bee colony with k-means (ABC-KM) algorithm is proposed to improve the effectiveness of wind farm clustering. Second, the operating data composed of wind speed, pitch angle, rotor angular velocity, rotor current, real-time active and reactive power are selected as clustering indicators. A wind farm with DFIGs is divided into several groups and DFIGs in the same group are clustered as one DFIG through equivalent parameter aggregation. The proposed wind farm modeling method consisting of clustering method and clustering indicators is verified by comparing the simulation results of equivalent and detailed models at steady-state and dynamic-state cases.

Highlights

With the rapid development of wind power technology, the scale of grid-connected wind farms is gradually increasing
In order to meet the practical engineering requirement, a multi-machine dynamic equivalence method for wind farm with doubly-fed induction wind generator (DFIG) is proposed in this paper
The artificial bee colony with k-means (ABC-KM) algorithm is proposed to improve the effectiveness of clustering

Summary

INTRODUCTION

With the rapid development of wind power technology, the scale of grid-connected wind farms is gradually increasing. The existing methods on the modeling of wind farms with doubly-fed induction wind generator (DFIG) are divided into two categories of single-machine and multi-machine equivalent methods. X. Wang et al.: Dynamic Equivalent Modeling for Wind Farms With DFIGs Using the Artificial Bee Colony With K-Means Algorithm characteristics of DFIGs based on the voltage and flux equation analyses. A multi-machine representation dynamic equivalent method based on the fuzzy C-means was proposed considering the active power characteristics of DFIGs in [17]. We propose a multi-machine dynamic equivalent modeling method for wind farms with DFIGs. The paper is organized as follows. The power grid voltage orientation is used for the GSC control in which the grid voltage is collinear with the d-axis

ABC-KM CLUSTERING ALGORITHM

ERROR ANALYSIS OF EQUIVALENT MODEL

CASE STUDY

Findings

CONCLUSION