發(fā)布時間：2018-11-04 19:45

【摘要】：風電場出力具有隨機性,將其接入配電網(wǎng)會引起無功補償設備的動作頻繁。為此,提出一種先對風電場有功輸出曲線進行分段,再對各個時段進行整體動態(tài)無功優(yōu)化的方法。針對直接對24h風力發(fā)電曲線采用整體動態(tài)無功優(yōu)化會引起維數(shù)災導致算法難以收斂的問題,采用基于譜系聚類思想的風電場出力曲線的分段法。針對傳統(tǒng)粒子群算法收斂到全局尋優(yōu)能力較差且易陷入局部最優(yōu)解的確定,采用云模型對粒子群算法的權值進行動態(tài)調(diào)整。最后,將上述算法運用于改進的IEEE 33節(jié)點系統(tǒng),仿真結(jié)果表明提出的動態(tài)優(yōu)化方法大大縮小了優(yōu)化的時間,并減少了控制設備的動作次數(shù),從而延長了設備的壽命。
[Abstract]:Wind farm output is random, and connecting it to distribution network will cause frequent action of reactive power compensation equipment. For this reason, a method is proposed to segment the active power output curve of wind farm first, and then to optimize the overall dynamic reactive power of each period. Aiming at the problem that the global dynamic reactive power optimization for 24 h wind power generation curve will lead to the difficulty of convergence of dimensionality disaster algorithm, a piecewise method of wind farm output curve based on pedigree clustering is adopted. The traditional particle swarm optimization (PSO) algorithm has poor convergence to global optimization and is easy to fall into local optimal solution. A cloud model is used to dynamically adjust the weight of PSO. Finally, the proposed algorithm is applied to the improved IEEE 33-bus system. The simulation results show that the proposed dynamic optimization method can greatly reduce the optimization time and reduce the number of actions of the control equipment, thus prolonging the life of the equipment.
【作者單位】： 國網(wǎng)江蘇省電力公司經(jīng)濟技術研究院;
【分類號】：TM614;TM714.3

【參考文獻】

相關期刊論文 前4條

1 蔡昌春;丁曉群;王寬;沈茂亞;吳禎;;動態(tài)無功優(yōu)化的簡化方法及實現(xiàn)[J];電力系統(tǒng)自動化;2008年05期

2 趙晶晶;符楊;李東東;;考慮雙饋電機風電場無功調(diào)節(jié)能力的配電網(wǎng)無功優(yōu)化[J];電力系統(tǒng)自動化;2011年11期

3 何佳;吳耀武;婁素華;熊信艮;;基于微粒群優(yōu)化算法的電力系統(tǒng)動態(tài)無功優(yōu)化[J];電網(wǎng)技術;2007年02期

4 劉方;顏偉;徐國禹;CHUNG C Y;WONG K P;;求解動態(tài)無功優(yōu)化問題的混合免疫遺傳算法[J];中國電力;2006年08期

【共引文獻】

相關期刊論文 前10條

1 何芳;丁金Z，

本文編號：2310957