电力系统自动化
電力繫統自動化
전력계통자동화
AUTOMATION OF ELECTRIC POWER SYSTEMS
2012年
14期
119-124
,共6页
王成福%梁军%张利%冯江霞%韩学山
王成福%樑軍%張利%馮江霞%韓學山
왕성복%량군%장리%풍강하%한학산
风电场%双馈感应发电机%风功率分布%无功电压控制%无功补偿容量%粒子群优化
風電場%雙饋感應髮電機%風功率分佈%無功電壓控製%無功補償容量%粒子群優化
풍전장%쌍궤감응발전궤%풍공솔분포%무공전압공제%무공보상용량%입자군우화
wind farm%double fed induction generator%wind power distribution%reactive power voltage control%reactive powercompensation%particle swarm optimization
双馈型风电机组的无功调节范围随其有功功率输出变化而存在波动性,极端条件下,又有其不可调节性,由此必然降低其对自身电压水平支撑的持续性。为此,在依据功率估算数据对风电场输出功率分布特性进行统计分析的基础上,提出考虑风功率分布特性的风电场无功补偿容量优化决策方法。该方法在充分计及双馈感应发电机无功调节能力与风功率分布特性的前提下,以无功补偿的投资成本与运行成本最小化为目标,构建无功补偿容量优化计算模型。该研究可使双馈型风电场的无功补偿决策更具针对性,并以最小代价实现该类风电场连续、无缝的无功电压调节。应用改进粒子群优化算法对所构建算例系统进行求解,分析结果表明了该研究的有效性。
雙饋型風電機組的無功調節範圍隨其有功功率輸齣變化而存在波動性,極耑條件下,又有其不可調節性,由此必然降低其對自身電壓水平支撐的持續性。為此,在依據功率估算數據對風電場輸齣功率分佈特性進行統計分析的基礎上,提齣攷慮風功率分佈特性的風電場無功補償容量優化決策方法。該方法在充分計及雙饋感應髮電機無功調節能力與風功率分佈特性的前提下,以無功補償的投資成本與運行成本最小化為目標,構建無功補償容量優化計算模型。該研究可使雙饋型風電場的無功補償決策更具針對性,併以最小代價實現該類風電場連續、無縫的無功電壓調節。應用改進粒子群優化算法對所構建算例繫統進行求解,分析結果錶明瞭該研究的有效性。
쌍궤형풍전궤조적무공조절범위수기유공공솔수출변화이존재파동성,겁단조건하,우유기불가조절성,유차필연강저기대자신전압수평지탱적지속성。위차,재의거공솔고산수거대풍전장수출공솔분포특성진행통계분석적기출상,제출고필풍공솔분포특성적풍전장무공보상용량우화결책방법。해방법재충분계급쌍궤감응발전궤무공조절능력여풍공솔분포특성적전제하,이무공보상적투자성본여운행성본최소화위목표,구건무공보상용량우화계산모형。해연구가사쌍궤형풍전장적무공보상결책경구침대성,병이최소대개실현해류풍전장련속、무봉적무공전압조절。응용개진입자군우화산법대소구건산례계통진행구해,분석결과표명료해연구적유효성。
The reactive power range of a doubly fed induction generator (DFIG) wind turbine fluctuates with its active power output, and it may become uncontrollable under some extreme conditions. As such, DFIG wind turbines ability for sustainable voltage support will be affected adversely. An optimization method for determining the reactive power compensation capacity is proposed, on the basis of statistical analysis of wind power distribution characteristic by using estimated power data. Considering the wind power distribution characteristic and the wind turbine reactive power capacity, an optimization model is built to minimize both the total cost of operation and reactive power compensation. The method can be used for decision-making in the reactive power compensation of wind farm, and realize continuous and seamless reactive voltage regulation for wind farms at minimum cost. An improved particle swarm optimization (PSO) is developed to solve the optimization problem. The model is proved to be effective.