风电场无功电压模糊多目标决策方法
Reactive Power and Voltage Fuzzy Multi-Objective Decision Making Method of Wind Farm
作者: 吕思琦 , 刘文颖 , 张雨薇 , 朱丹丹 :华北电力大学电气与电子工程学院,北京 ; 梁 琛 :国网甘肃省电力公司电力科学研究院,甘肃 兰州 ;
关键词: 模糊多目标决策; 无功电压优化; 双馈风电机组; SVC; 风电场; Fuzzy Multi-Objective Decision Making; Reactive Power and Voltage Optimization; DFIG; SVC; Wind Farm
摘要:Abstract: To solve stability and economy coordinated problem caused by wind farm integration, the targets of stability and economy are put forward, in which economy target considers active power loss, and stability target includes reactive power reserve capacity and voltage deviation of wind farm. Based on this, an optimization control model of reactive power and voltage fuzzy multi-objective decision making method of wind farm is established, in which the reactive power of SVC and DFIG are taken as control objectives, and the fuzzy multi-objective decision making method is used to convert the optimization of reactive power and voltage into a multi-objective and multi-constrained nonlinear programming problem. The particle swarm algorithm (PSO) is adopted to solve the built model. The simulation example results show that the proposed method can achieve the dual targets of economy and stability of wind farms, and can improve the voltage stability of wind farms, and reasonably re-duce the power loss of wind farms.
文章引用: 吕思琦 , 刘文颖 , 张雨薇 , 朱丹丹 , 梁 琛 (2016) 风电场无功电压模糊多目标决策方法。 智能电网, 6, 221-230. doi: 10.12677/SG.2016.64025
参考文献
[1] 中共中央国务院. 关于进一步深化电力体制改革的若干意见[R] (中发[2015]9号), 2015-03-15.
[2] 迟永宁, 刘燕华, 王伟胜, 等. 风电接入对电力系统的影响[J]. 电网技术, 2007, 31(3): 76-81
[3] 中华人民共和国国家质量监督检验检疫总局, 中国国家标准化管理委员会. 风电场接入电力系统技术规定: GB/T 19963-2011 [S]. 北京: 中国标准出版社, 2011.
[4]
Tapia, A. and Tapia, G. (2004) Reactive Power Control of Wind Farms for Voltage Control Application. Re-newable Energy, 29, 377-392.
http://dx.doi.org/10.1016/S0960-1481(03)00224-6
[5]
Chen, Z. and Spooner, E. (2001) Grid Power Quality with Variable Speed Wind Turbines. IEEE Transactions on Energy Conversion, 16, 148-154.
http://dx.doi.org/10.1109/60.921466
[6] 陈宁, 朱凌志, 王伟. 改善接入地区电压稳定性的风电场无功控制策略[J]. 中国电机工程学报, 2009, 29(10): 102-108.
[7] 杨桦, 梁海峰, 李庚银. 含双馈感应电机的风电场电压协调控制策略[J]. 电网技术, 2011, 35(2): 121-126.
[8] 王成福, 梁军, 张利, 等. 基于静止同步补偿器的风电场无功电压控制策略[J]. 中国电机工程学报, 2010, 30(20): 23-28
[9] 栗然, 唐凡, 刘英培, 等. 双馈风电场新型无功补偿与电压控制方案[J]. 中国电机工程学报, 2012, 32(19): 16-23.
[10] 杨硕, 王伟胜, 刘纯, 等. 双馈风电场无功电压协调控制策略[J]. 电力系统自动化, 2013, 37(12): 1-6.
[11] 陈慧粉, 乔颖, 鲁宗相, 闵勇. 风电场群的无功电压协调控制策略[J]. 电力系统自动化, 2010, 34(18): 78-83.
[12] 赵亮, 吕剑虹. 基于改进遗传算法的风电场多目标无功优化[J]. 电力自动化设备, 2010, 30(10): 84-88.
[13] 孙伟伟, 付蓉, 陈永华. 计及无功裕度的双馈风电场无功电压协调控制[J]. 电力自动化设备, 2014, 34(10): 81-85.
[14] 卢锦玲, 何振民, 何同祥, 魏方园, 徐超. 计及暂态电压安全性的风电场无功电压协调控制[J]. 电网技术, 2015, 39(10): 2780-2786.
[15] 盛四清, 陈安, 杨少波. 双馈式风电场多阶段无功电压控制策略[J]. 现代电力, 2015, 32(5): 89-94.
[16] Garson, G.D. (1991) Interpreting Neural-Network Connection Weights. Artificial Intelligence Expert, 6, 46-51.
[17] Hecht-Nielsen, R. (1987) Kolmogorov’s Mapping Neural Network Existence Theorem. Proceedings of the International Conference on Neural Networks, 3, 11-13.
[18] 刘述奎, 李奇, 陈维荣, 林川, 郑永康. 改进粒子群优化算法在电力系统多目标无功优化中应用[J]. 电力自动化设备, 2009, 29(11): 31-36.
[19]
Mirchandani, G. and Cao, W. (1989) On Hidden Nodes for Neural Nets. IEEE Transactions on Circuits and Systems, 36, 661-664.
http://dx.doi.org/10.1109/31.31313