电力系统自动化
電力繫統自動化
전력계통자동화
AUTOMATION OF ELECTRIC POWER SYSTEMS
2014年
20期
61-67
,共7页
张旭%梁军%贠志皓%王洪涛%牛睿%石国萍
張旭%樑軍%贠誌皓%王洪濤%牛睿%石國萍
장욱%량군%원지호%왕홍도%우예%석국평
风力发电%不确定分析%广义负荷建模%概率统计%Levenberg-Marquardt 神经网络
風力髮電%不確定分析%廣義負荷建模%概率統計%Levenberg-Marquardt 神經網絡
풍력발전%불학정분석%엄의부하건모%개솔통계%Levenberg-Marquardt 신경망락
wind power generation%uncertainty analysis%generalized load modeling%probability statistics%Levenberg-Marquardt neural network
考虑风电接入原负荷节点后带来的节点特性不确定性问题,提出了基于概率统计的广义负荷节点稳态特性学习与建模的新方法。为分析风电接入后功率流向的改变,将节点特性分为电源特性与负荷特性;针对节点特性的不确定性变化,基于历史实测数据对有功功率样本空间进行自适应分段细化,统计其概率分布;利用 Levenberg-Marquardt 神经网络法学习并提取各段节点特征,构建节点特性统一模型,并以风险分析为例说明新模型的应用。仿真结果表明,所提方法不但可精确建模,而且通过统计数据样本引入概率信息,可对不确定性问题按概率分场景分析,弥补了传统方法对随机特征描述能力不足的缺陷,是对传统建模方法在不确定场景应用上的扩展和延伸,从而可为风电接入后的仿真分析与调度控制提供辅助参考。
攷慮風電接入原負荷節點後帶來的節點特性不確定性問題,提齣瞭基于概率統計的廣義負荷節點穩態特性學習與建模的新方法。為分析風電接入後功率流嚮的改變,將節點特性分為電源特性與負荷特性;針對節點特性的不確定性變化,基于歷史實測數據對有功功率樣本空間進行自適應分段細化,統計其概率分佈;利用 Levenberg-Marquardt 神經網絡法學習併提取各段節點特徵,構建節點特性統一模型,併以風險分析為例說明新模型的應用。倣真結果錶明,所提方法不但可精確建模,而且通過統計數據樣本引入概率信息,可對不確定性問題按概率分場景分析,瀰補瞭傳統方法對隨機特徵描述能力不足的缺陷,是對傳統建模方法在不確定場景應用上的擴展和延伸,從而可為風電接入後的倣真分析與調度控製提供輔助參攷。
고필풍전접입원부하절점후대래적절점특성불학정성문제,제출료기우개솔통계적엄의부하절점은태특성학습여건모적신방법。위분석풍전접입후공솔류향적개변,장절점특성분위전원특성여부하특성;침대절점특성적불학정성변화,기우역사실측수거대유공공솔양본공간진행자괄응분단세화,통계기개솔분포;이용 Levenberg-Marquardt 신경망락법학습병제취각단절점특정,구건절점특성통일모형,병이풍험분석위례설명신모형적응용。방진결과표명,소제방법불단가정학건모,이차통과통계수거양본인입개솔신식,가대불학정성문제안개솔분장경분석,미보료전통방법대수궤특정묘술능력불족적결함,시대전통건모방법재불학정장경응용상적확전화연신,종이가위풍전접입후적방진분석여조도공제제공보조삼고。
By considering the bus characteristic uncertainty after wind power integration at the original load bus,a new method based on probability statistics is proposed to learn about and model steady-state characteristics of generalized load buses.To analyze the change of the power direction after wind power integration, the bus characteristics are divided into source characteristics and load characteristics.In view of the change in the uncertainty of bus characteristics,the sample space of active power is segmented adaptively according to the past measured data. The probability distribution is obtained by probability statistics.Levenberg-Marquardt neural network is used to abstract the bus characteristics prior to the development of the unified model.The application of the new model is described by taking the risk analysis as an example.Simulation results show that the method proposed can not only accurately build the model,but also analyze the uncertainty problem by making use of probability statistics according to the different scenarios.The new method has made up the inadequacy of the traditional method in random characteristic description,which is an extension and supplement to the traditional method in uncertain scenario application useful for simulation analysis and dispatch control following wind power integration.