Distributed Optimization Method for Operation Power of Large-scale Offshore Wind Farm Based on Two-step Processing

被引：0

作者：

Yang J. ^{[1
]}

Huang C. ^{[1
]}

Song D. ^{[1
]}

Dong M. ^{[1
]}

Chen S. ^{[2
]}

Hu Y. ^{[3
]}

Fang F. ^{[3
]}

机构：

[1] School of Automation, Central South University, Changsha

[2] Mingyang Smart Energy Co., Ltd., Zhongshan

[3] School of Control and Computer Engineering, North China Electric Power University, Beijing

来源：

Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2023年 / 47卷 / 07期

基金：

中国国家自然科学基金;

关键词：

distributed optimization; network clustering; offshore wind farm; wake effect;

D O I：

10.7500/AEPS20220419003

中图分类号：

学科分类号：

摘要：

As offshore wind farms gradually become larger, the wake effect has intensified the impact of wind farm power generation efficiency. Existing wake control methods for wind farms have large computational load and limited optimization effect. In this regard, according to the update and clustering of wind farm networks, a two-step power optimization method is proposed. Based on the improved network definition considering the wake effect of offshore wind farms, the optimization is divided into two stages to deal with the impact of optimization actions on the network and power of wind farms. The spectral clustering method is applied to achieve network clustering. Combined with improved equilibrium optimizer to achieve efficient solution, a two-step optimization strategy is implemented by the combination of cluster update and optimization iterations. The results of case simulation show that, compared with centralized optimization, the proposed method has significant optimization effect and significantly shortens solving time. Compared with direct optimization, larger power gain is obtained at the cost of increasing the limited solving time in complex wake correlation scenarios. Finally, the wind farms of different scales and the number of clusters are explored, and the proposed method has good application prospects for large-scale offshore wind farm. © 2023 Automation of Electric Power Systems Press. All rights reserved.

引用

页码：94 / 104

页数：10

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