电力系统自动化
電力繫統自動化
전력계통자동화
AUTOMATION OF ELECTRIC POWER SYSTEMS
2015年
4期
135-140,151
,共7页
陆晶晶%肖湘宁%张剑%罗超
陸晶晶%肖湘寧%張劍%囉超
륙정정%초상저%장검%라초
弱阻尼次同步振荡%次同步振荡动态稳定器%次同步调制%实时数字-物理闭环仿真%有效阻尼区域
弱阻尼次同步振盪%次同步振盪動態穩定器%次同步調製%實時數字-物理閉環倣真%有效阻尼區域
약조니차동보진탕%차동보진탕동태은정기%차동보조제%실시수자-물리폐배방진%유효조니구역
subsynchronous oscillation with weak damping%subsynchronus oscillation-dynamic stabilizer (SSO-DS)%subsynchronous modulation%real-time digital and physical closed-loop simulation%effective damping area
针对呼盟系统呼伦贝尔电厂存在的弱阻尼次同步振荡问题,实际工程采用次同步振荡动态稳定器(SSO-DS)进行抑制。文中提出了一种适用于 SSO-DS 的瞬时无功功率次同步调制策略,基于复转矩系数法推导出该控制策略下 SSO-DS 提供的阻尼,给出了影响其阻尼大小的相关因素;搭建了实时数字—物理闭环仿真平台,并基于弱阻尼次同步振荡问题,提出了确定其有效阻尼区域的方法,对控制器参数进行优化。闭环仿真及现场实验均验证了 SSO-DS 控制策略的有效性以及闭环仿真实验参数优化的准确性。
針對呼盟繫統呼倫貝爾電廠存在的弱阻尼次同步振盪問題,實際工程採用次同步振盪動態穩定器(SSO-DS)進行抑製。文中提齣瞭一種適用于 SSO-DS 的瞬時無功功率次同步調製策略,基于複轉矩繫數法推導齣該控製策略下 SSO-DS 提供的阻尼,給齣瞭影響其阻尼大小的相關因素;搭建瞭實時數字—物理閉環倣真平檯,併基于弱阻尼次同步振盪問題,提齣瞭確定其有效阻尼區域的方法,對控製器參數進行優化。閉環倣真及現場實驗均驗證瞭 SSO-DS 控製策略的有效性以及閉環倣真實驗參數優化的準確性。
침대호맹계통호륜패이전엄존재적약조니차동보진탕문제,실제공정채용차동보진탕동태은정기(SSO-DS)진행억제。문중제출료일충괄용우 SSO-DS 적순시무공공솔차동보조제책략,기우복전구계수법추도출해공제책략하 SSO-DS 제공적조니,급출료영향기조니대소적상관인소;탑건료실시수자—물리폐배방진평태,병기우약조니차동보진탕문제,제출료학정기유효조니구역적방법,대공제기삼수진행우화。폐배방진급현장실험균험증료 SSO-DS 공제책략적유효성이급폐배방진실험삼수우화적준학성。
In view of the subsynchronous oscillation with weak damping occurring in Hulunbeier power plant in the Hulunbeier League power system,the subsynchronous oscillation-dynamic stabilizer(SSO-DS)is recommended to suppress the oscillation in this actual project.This paper proposes the subsynchronous modulation of instantaneous reactive power control strategy for SSO-DS.The damping provided by SSO-DS using the proposed control strategy is derived on the basis of the complex torque coefficient method.Relevant factors that influence the size of the damping are presented.And the real-time digital and physical closed-loop simulation platform is developed.In order to suppress the subsynchronous oscillation with weak damping,a method of finding the effective damping area is proposed to optimize the controller parameters.The effectiveness of the control strategy and the accuracy of parameter optimization are both verified by closed-loop simulation and field experiment.