Short-term load forecast plays an important role in the day-to-day operation and scheduling of generating units. Season and temperature are the most important factors that affect the load change, but random factors su...Short-term load forecast plays an important role in the day-to-day operation and scheduling of generating units. Season and temperature are the most important factors that affect the load change, but random factors such as big sport events or popular TV shows can change demand consumption in particular hours, which will lead to sudden load changes. A weighted time-variant slide fuzzy time-series model (WTVS) for short-term load forecasting is proposed to improve forecasting accuracy. The WTVS model is divided into three parts, including the data preprocessing, the trend training and the load forecasting. In the data preprocessing phase, the impact of random factors will be weakened by smoothing the historical data. In the trend training and load forecasting phase, the seasonal factor and the weighted historical data are introduced into the Time-variant Slide Fuzzy Time-series Models (TVS) for short-term load forecasting. The WTVS model is tested on the load of the National Electric Power Company in Jordan. Results show that the proposed WTVS model achieves a significant improvement in load forecasting accuracy as compared to TVS models.展开更多
The research progress of a novel traffic solution,a submerged floating tunnel（SFT）,is reviewed in terms of a study approach and loading scenario.Among existing publications,the buoyancy-weight ratio（BWR） is usuall...The research progress of a novel traffic solution,a submerged floating tunnel（SFT）,is reviewed in terms of a study approach and loading scenario.Among existing publications,the buoyancy-weight ratio（BWR） is usually predefined.However,BWR is a critical structural parameter that tremendously affects the dynamic behaviour of not only the tunnel tube itself but also the cable system.In the context of a SFT prototype（SFTP） project in Qiandao Lake（Zhejiang Province,China）,the importance of BWR is illustrated by finite element analysis and subsequently,an optimized BWR is proposed within a reasonable range in the present study.In the numerical model,structural damping is identified to be of importance.Rayleigh damping and the corresponding Rayleigh coefficients are attained through a sensitivity study,which shows that the adopted damping ratios are fairly suitable for SFTP.Lastly,the human sense of security is considered by quantifying the comfort index,which helps further optimize BWR in the SFTP structural parameter design.展开更多
面向规模化屋顶光伏接入配电网急需进行有序控制的现状,提出了一种考虑源荷匹配特性的屋顶光伏并网的综合排序方法。首先,综合考虑负荷与光伏协调特性等需求,设计了兼顾光伏业主侧、电网侧和用电用户侧需求的综合评价指标体系;其次,提...面向规模化屋顶光伏接入配电网急需进行有序控制的现状,提出了一种考虑源荷匹配特性的屋顶光伏并网的综合排序方法。首先,综合考虑负荷与光伏协调特性等需求,设计了兼顾光伏业主侧、电网侧和用电用户侧需求的综合评价指标体系;其次,提出了一种基于改进层次分析法(improved analytic hierarchy process,IAHP)-改进反熵权法(improved anti-entropy method,IAM)-博弈组合赋权法-改进逼近理想解法(improved technique for order preference by similarity to ideal solution,improved TOPSIS)的评价方法,先根据改进的层次分析法进行主观赋权,同时考虑到指标间的相关性和波动性,采用所提改进反熵权法确定各指标的客观权重,再基于博弈论思想获取综合权重,以确保权重的合理性,然后,为提高各方案的整体区分度,采用所提改进逼近理想解法对屋顶光伏接入方案进行排序。最后,以IEEE 33节点系统为例,在MATLAB平台验证了所提指标体系和排序方法的有效性。展开更多
Kubernetes容器云是当前流行的云计算技术,其默认的弹性伸缩方法HPA(Horizontal Pod Autoscaler)能对云原生应用进行横向扩缩容。但该方法存在以下问题:基于单一负载指标,使其难以适用于多样化云原生应用;基于当前负载进行弹性伸缩,使...Kubernetes容器云是当前流行的云计算技术,其默认的弹性伸缩方法HPA(Horizontal Pod Autoscaler)能对云原生应用进行横向扩缩容。但该方法存在以下问题:基于单一负载指标,使其难以适用于多样化云原生应用;基于当前负载进行弹性伸缩,使扩缩容过程具有明显的滞后性;基于滑动时间窗口算法进行弹性缩容,使缩容过程缓慢易造成系统资源浪费。针对上述问题,文中提出一种改进的弹性伸缩方法。设计一种动态加权融合算法将多种负载指标融合为综合负载因子,全面反映云原生应用的综合负载。提出CEEMDAN(Complete Ensemble Empirical Mode Decomposition with Adaptive Noise)-ARIMA(Autoregressive Integrated Moving Average Model)预测模型,基于该模型的预测负载值实现预先弹性伸缩以应对突发流量。提出快速缩容与滑动时间窗口相结合的方法,在确保应用服务质量的基础上减少系统资源浪费。实验结果表明,相较于HPA机制,改进的弹性伸缩方法在应对首次突发流量时的平均响应时间缩短了336.55%,流量结束后系统资源占用减少了50%,再次遇到突发流量时能迅速扩容,平均响应时间缩短66.83%。展开更多
文摘Short-term load forecast plays an important role in the day-to-day operation and scheduling of generating units. Season and temperature are the most important factors that affect the load change, but random factors such as big sport events or popular TV shows can change demand consumption in particular hours, which will lead to sudden load changes. A weighted time-variant slide fuzzy time-series model (WTVS) for short-term load forecasting is proposed to improve forecasting accuracy. The WTVS model is divided into three parts, including the data preprocessing, the trend training and the load forecasting. In the data preprocessing phase, the impact of random factors will be weakened by smoothing the historical data. In the trend training and load forecasting phase, the seasonal factor and the weighted historical data are introduced into the Time-variant Slide Fuzzy Time-series Models (TVS) for short-term load forecasting. The WTVS model is tested on the load of the National Electric Power Company in Jordan. Results show that the proposed WTVS model achieves a significant improvement in load forecasting accuracy as compared to TVS models.
文摘The research progress of a novel traffic solution,a submerged floating tunnel（SFT）,is reviewed in terms of a study approach and loading scenario.Among existing publications,the buoyancy-weight ratio（BWR） is usually predefined.However,BWR is a critical structural parameter that tremendously affects the dynamic behaviour of not only the tunnel tube itself but also the cable system.In the context of a SFT prototype（SFTP） project in Qiandao Lake（Zhejiang Province,China）,the importance of BWR is illustrated by finite element analysis and subsequently,an optimized BWR is proposed within a reasonable range in the present study.In the numerical model,structural damping is identified to be of importance.Rayleigh damping and the corresponding Rayleigh coefficients are attained through a sensitivity study,which shows that the adopted damping ratios are fairly suitable for SFTP.Lastly,the human sense of security is considered by quantifying the comfort index,which helps further optimize BWR in the SFTP structural parameter design.
文摘面向规模化屋顶光伏接入配电网急需进行有序控制的现状,提出了一种考虑源荷匹配特性的屋顶光伏并网的综合排序方法。首先,综合考虑负荷与光伏协调特性等需求,设计了兼顾光伏业主侧、电网侧和用电用户侧需求的综合评价指标体系;其次,提出了一种基于改进层次分析法(improved analytic hierarchy process,IAHP)-改进反熵权法(improved anti-entropy method,IAM)-博弈组合赋权法-改进逼近理想解法(improved technique for order preference by similarity to ideal solution,improved TOPSIS)的评价方法,先根据改进的层次分析法进行主观赋权,同时考虑到指标间的相关性和波动性,采用所提改进反熵权法确定各指标的客观权重,再基于博弈论思想获取综合权重,以确保权重的合理性,然后,为提高各方案的整体区分度,采用所提改进逼近理想解法对屋顶光伏接入方案进行排序。最后,以IEEE 33节点系统为例,在MATLAB平台验证了所提指标体系和排序方法的有效性。
文摘Kubernetes容器云是当前流行的云计算技术,其默认的弹性伸缩方法HPA(Horizontal Pod Autoscaler)能对云原生应用进行横向扩缩容。但该方法存在以下问题:基于单一负载指标,使其难以适用于多样化云原生应用;基于当前负载进行弹性伸缩,使扩缩容过程具有明显的滞后性;基于滑动时间窗口算法进行弹性缩容,使缩容过程缓慢易造成系统资源浪费。针对上述问题,文中提出一种改进的弹性伸缩方法。设计一种动态加权融合算法将多种负载指标融合为综合负载因子,全面反映云原生应用的综合负载。提出CEEMDAN(Complete Ensemble Empirical Mode Decomposition with Adaptive Noise)-ARIMA(Autoregressive Integrated Moving Average Model)预测模型,基于该模型的预测负载值实现预先弹性伸缩以应对突发流量。提出快速缩容与滑动时间窗口相结合的方法,在确保应用服务质量的基础上减少系统资源浪费。实验结果表明,相较于HPA机制,改进的弹性伸缩方法在应对首次突发流量时的平均响应时间缩短了336.55%,流量结束后系统资源占用减少了50%,再次遇到突发流量时能迅速扩容,平均响应时间缩短66.83%。
