储能应用于风电功率波动平抑时,存在有效平抑波动功率与减小储能电池负担难以协调的问题,导致风电功率波动平抑效果不佳或储能电池负担增大。针对以上问题,提出了一种改进的自适应滑动平均滤波算法,在满足1min和10min双时间尺度的风电...储能应用于风电功率波动平抑时,存在有效平抑波动功率与减小储能电池负担难以协调的问题,导致风电功率波动平抑效果不佳或储能电池负担增大。针对以上问题,提出了一种改进的自适应滑动平均滤波算法,在满足1min和10min双时间尺度的风电并网功率波动率标准下,对风电功率进行自适应分解,不仅获得了满足风电并网标准的并网功率参考值,还减小了需要储能电池平抑的波动功率,然后采用双磷酸铁锂电池来平抑波动功率,同时考虑荷电状态(state of charge,SOC)反馈,通过检测储能电池SOC的值,判断其是否达到充电上限或放电下限,以此防止过充过放电对储能电池运行寿命的影响,运用雨流计数法寿命评估模型对储能电池运行寿命进行评估。算例表明,所提算法能够根据风电功率波动率的大小在线实时调节滑动窗口的大小,实现风电功率的分解,从而有效地平抑了风电功率波动,并且降低了储能电池的负担,延长了其使用寿命。展开更多
A novel multiresolution pyramidal edge detector, based on adaptive weighted fuzzy mean(AWFM)filtering and fuzzy linking model, is presented in this paper. The algorithm first constructs a pyramidal structure by repeti...A novel multiresolution pyramidal edge detector, based on adaptive weighted fuzzy mean(AWFM)filtering and fuzzy linking model, is presented in this paper. The algorithm first constructs a pyramidal structure by repetitive AWFM filtering and subsampling of original image. Then it utilizes multiple heuristic linking criteria between the edge nodes of two adjacent levels and considers the linkage as a fuzzy model, which is trained offline. Through this fuzzy linking model, the boundaries detected at coarse resolution are propagated and refined to the bottom level from the coarse-to fine edge detection. The validation experiment results demonstrate that the proposed approach has superior performance compared with standard fixed resolution detector andprevious multiresolution approach, especially in impulse noise environment.展开更多
文摘储能应用于风电功率波动平抑时,存在有效平抑波动功率与减小储能电池负担难以协调的问题,导致风电功率波动平抑效果不佳或储能电池负担增大。针对以上问题,提出了一种改进的自适应滑动平均滤波算法,在满足1min和10min双时间尺度的风电并网功率波动率标准下,对风电功率进行自适应分解,不仅获得了满足风电并网标准的并网功率参考值,还减小了需要储能电池平抑的波动功率,然后采用双磷酸铁锂电池来平抑波动功率,同时考虑荷电状态(state of charge,SOC)反馈,通过检测储能电池SOC的值,判断其是否达到充电上限或放电下限,以此防止过充过放电对储能电池运行寿命的影响,运用雨流计数法寿命评估模型对储能电池运行寿命进行评估。算例表明,所提算法能够根据风电功率波动率的大小在线实时调节滑动窗口的大小,实现风电功率的分解,从而有效地平抑了风电功率波动,并且降低了储能电池的负担,延长了其使用寿命。
文摘A novel multiresolution pyramidal edge detector, based on adaptive weighted fuzzy mean(AWFM)filtering and fuzzy linking model, is presented in this paper. The algorithm first constructs a pyramidal structure by repetitive AWFM filtering and subsampling of original image. Then it utilizes multiple heuristic linking criteria between the edge nodes of two adjacent levels and considers the linkage as a fuzzy model, which is trained offline. Through this fuzzy linking model, the boundaries detected at coarse resolution are propagated and refined to the bottom level from the coarse-to fine edge detection. The validation experiment results demonstrate that the proposed approach has superior performance compared with standard fixed resolution detector andprevious multiresolution approach, especially in impulse noise environment.
