Along with the wide-ranging addition of wind power into power systems,multiple uncertainties are produced due to continuous changes of wind power,which in turn will affect the dispatching and operational process of th...Along with the wide-ranging addition of wind power into power systems,multiple uncertainties are produced due to continuous changes of wind power,which in turn will affect the dispatching and operational process of the power grid.In this process,excessive pursuit of the lowest risk of wind energy may bring an apparent influence on the economic effect of the multi-energy complementary power generation system because a continuous imbalance between demand and supply may lead to wind curtailment.To solve these issues,a new model that couples the multi-dimensional uncertainty model with the day-ahead complementary operation model is developed for a wind-hydrothermal system.A multi-dimensional uncertainty model(MU)is used to deal with wind uncertainty because it can quantitatively describe the complex features of error distribution of hourly dayahead wind power forecasting.The multi-dimensional interval scenes attained by the MU model can reflect hour-to-hour uncertain interaction in the day-ahead complementary operation for the wind-hydro-thermal system.This new model can make up for the shortcomings of the day-ahead operation model by reducing wind power risk and optimizing the operational costs.A two-layer nested approach with the hierarchical structure is applied to handle the wind-hydro-thermal system’s complex equality and inequality constraints.The new model and algorithm’s effectiveness can be evaluated by applying them to the Shaanxi Electric Power Company in China.Results demonstrated that:compared with the conventional operation strategies,the proposed model can save the operational cost of the units by 7.92%and the hybrid system by 0.995%,respectively.This study can offer references for the impact of renewable energy on the power grid within the context of the day-ahead electricity market.展开更多
随着大量新能源的接入,使得多端柔性直流系统(modular multilevel converter based multi-terminal direct current, MMC-MTDC)故障特征愈加复杂,快速准确的故障识别与测距是亟需解决的关键难题之一。为此,提出了一种风-光-储-蓄互补发...随着大量新能源的接入,使得多端柔性直流系统(modular multilevel converter based multi-terminal direct current, MMC-MTDC)故障特征愈加复杂,快速准确的故障识别与测距是亟需解决的关键难题之一。为此,提出了一种风-光-储-蓄互补发电站经柔性直流输电外送系统故障识别与测距方法。首先,搭建风-光-储-蓄互补发电站经柔直外送系统,在此基础上,提出了一种Teager能量算子能量熵的新方法,利用测量点正负极Teager能量算子能量熵的比值构建故障选极及区段识别判据。接着,针对已识别的故障线路,提出变分模态分解(variational mode decomposition, VMD)与Teager能量算子(teager energy operator, TEO)相结合的故障测距方法。最后,利用PSCAD/EMTDC进行仿真,结果表明所提识别方法可以准确判断故障所在线路,所提测距方法能在故障发生2 ms时间窗内实现故障测距,误差率不超过2.55%,并具有较高的耐过渡电阻能力。展开更多
基于自组织抗体网络(so Ab Net)的变压器故障诊断方法中没有网络压缩机制,并且网络的初始抗体是随机选取的,网络性能不稳定。针对这一问题,提出了基于互补免疫算法的变压器故障诊断方法,结合变压器故障诊断的特点详细设计了免疫算子以弥...基于自组织抗体网络(so Ab Net)的变压器故障诊断方法中没有网络压缩机制,并且网络的初始抗体是随机选取的,网络性能不稳定。针对这一问题,提出了基于互补免疫算法的变压器故障诊断方法,结合变压器故障诊断的特点详细设计了免疫算子以弥补so Ab Net的不足。免疫算子中接种疫苗利用K-means最佳聚类算法为so Ab Net提供初始抗体,并通过免疫选择压缩网络规模,其参数由粒子群算法进行优化。变压器故障诊断实验结果表明,所提出的互补免疫算法能够充分利用系统的先验知识,并有效地提取故障样本的数据特征,与单一智能方法相比具有更高的诊断准确率。展开更多
基金supported by the Research on comprehensive energy system of park based on big data analysis technology(2019ZDLGY18-03)National Natural Science Foundation of China(No.51879213)China Postdoctoral Science Foundation(2020M673453).
文摘Along with the wide-ranging addition of wind power into power systems,multiple uncertainties are produced due to continuous changes of wind power,which in turn will affect the dispatching and operational process of the power grid.In this process,excessive pursuit of the lowest risk of wind energy may bring an apparent influence on the economic effect of the multi-energy complementary power generation system because a continuous imbalance between demand and supply may lead to wind curtailment.To solve these issues,a new model that couples the multi-dimensional uncertainty model with the day-ahead complementary operation model is developed for a wind-hydrothermal system.A multi-dimensional uncertainty model(MU)is used to deal with wind uncertainty because it can quantitatively describe the complex features of error distribution of hourly dayahead wind power forecasting.The multi-dimensional interval scenes attained by the MU model can reflect hour-to-hour uncertain interaction in the day-ahead complementary operation for the wind-hydro-thermal system.This new model can make up for the shortcomings of the day-ahead operation model by reducing wind power risk and optimizing the operational costs.A two-layer nested approach with the hierarchical structure is applied to handle the wind-hydro-thermal system’s complex equality and inequality constraints.The new model and algorithm’s effectiveness can be evaluated by applying them to the Shaanxi Electric Power Company in China.Results demonstrated that:compared with the conventional operation strategies,the proposed model can save the operational cost of the units by 7.92%and the hybrid system by 0.995%,respectively.This study can offer references for the impact of renewable energy on the power grid within the context of the day-ahead electricity market.
文摘随着大量新能源的接入,使得多端柔性直流系统(modular multilevel converter based multi-terminal direct current, MMC-MTDC)故障特征愈加复杂,快速准确的故障识别与测距是亟需解决的关键难题之一。为此,提出了一种风-光-储-蓄互补发电站经柔性直流输电外送系统故障识别与测距方法。首先,搭建风-光-储-蓄互补发电站经柔直外送系统,在此基础上,提出了一种Teager能量算子能量熵的新方法,利用测量点正负极Teager能量算子能量熵的比值构建故障选极及区段识别判据。接着,针对已识别的故障线路,提出变分模态分解(variational mode decomposition, VMD)与Teager能量算子(teager energy operator, TEO)相结合的故障测距方法。最后,利用PSCAD/EMTDC进行仿真,结果表明所提识别方法可以准确判断故障所在线路,所提测距方法能在故障发生2 ms时间窗内实现故障测距,误差率不超过2.55%,并具有较高的耐过渡电阻能力。
文摘基于自组织抗体网络(so Ab Net)的变压器故障诊断方法中没有网络压缩机制,并且网络的初始抗体是随机选取的,网络性能不稳定。针对这一问题,提出了基于互补免疫算法的变压器故障诊断方法,结合变压器故障诊断的特点详细设计了免疫算子以弥补so Ab Net的不足。免疫算子中接种疫苗利用K-means最佳聚类算法为so Ab Net提供初始抗体,并通过免疫选择压缩网络规模,其参数由粒子群算法进行优化。变压器故障诊断实验结果表明,所提出的互补免疫算法能够充分利用系统的先验知识,并有效地提取故障样本的数据特征,与单一智能方法相比具有更高的诊断准确率。