智能电网背景下,具备分布式光伏出力和自动需求响应要素的智能楼宇联合运行可以促进光伏发电的就地消纳,提高其用电经济性。因此,构建了以配有储能系统的智能楼宇集群运营商(smart building cluster operator,SBCO)为中心的能量交易框架...智能电网背景下,具备分布式光伏出力和自动需求响应要素的智能楼宇联合运行可以促进光伏发电的就地消纳,提高其用电经济性。因此,构建了以配有储能系统的智能楼宇集群运营商(smart building cluster operator,SBCO)为中心的能量交易框架,并提出一种考虑分时电价差异性和基于主从博弈的能量共享方法。首先,考虑到不同负荷类型楼宇用户存在分时电价差异性,且智能楼宇的实时需求响应会促进集群内部的能量共享,建立了SBCO的日前储能调度模型。其次,计及SBCO和楼宇用户具有不同逐利特性及用户的信息私密性和对用电舒适度要求,提出了一种基于主从博弈的实时需求响应模型以实现两方利益制约平衡和联合优化。最后,通过实际算例证实了所提方法可以较好地提升SBCO和智能楼宇的经济效益,且在促进分布式光伏就地消纳和优化智能楼宇集群净负荷特性方面具有优势。展开更多
Data stream management system (DSMS) provides convenient solutions to the problem of processing continuous queries on data streams.Previous approaches for scheduling these queries and their operators assume that each ...Data stream management system (DSMS) provides convenient solutions to the problem of processing continuous queries on data streams.Previous approaches for scheduling these queries and their operators assume that each operator runs in separate thread or all operators combine in one query plan and run in a single thread.Both approaches suffer from severe drawbacks concerning the thread overhead and the stalls due to expensive operators.To overcome these drawbacks,a novel approach called clustered operators scheduling (COS) is proposed that adaptively clusters operators of the query plan into a number of groups based on their selectivity and computing cost using S-mean clustering.Experimental evaluation is provided to demonstrate the potential benefits of COS scheduling over the other scheduling strategies.COS can provide adaptive,flexible,reliable,scalable and robust design for continuous query processor.展开更多
文摘智能电网背景下,具备分布式光伏出力和自动需求响应要素的智能楼宇联合运行可以促进光伏发电的就地消纳,提高其用电经济性。因此,构建了以配有储能系统的智能楼宇集群运营商(smart building cluster operator,SBCO)为中心的能量交易框架,并提出一种考虑分时电价差异性和基于主从博弈的能量共享方法。首先,考虑到不同负荷类型楼宇用户存在分时电价差异性,且智能楼宇的实时需求响应会促进集群内部的能量共享,建立了SBCO的日前储能调度模型。其次,计及SBCO和楼宇用户具有不同逐利特性及用户的信息私密性和对用电舒适度要求,提出了一种基于主从博弈的实时需求响应模型以实现两方利益制约平衡和联合优化。最后,通过实际算例证实了所提方法可以较好地提升SBCO和智能楼宇的经济效益,且在促进分布式光伏就地消纳和优化智能楼宇集群净负荷特性方面具有优势。
基金Project(50275150) supported by the National Natural Science Foundation of ChinaProject(20040533035) supported by the National Research Foundation for the Doctoral Program of Higher Education of China
文摘Data stream management system (DSMS) provides convenient solutions to the problem of processing continuous queries on data streams.Previous approaches for scheduling these queries and their operators assume that each operator runs in separate thread or all operators combine in one query plan and run in a single thread.Both approaches suffer from severe drawbacks concerning the thread overhead and the stalls due to expensive operators.To overcome these drawbacks,a novel approach called clustered operators scheduling (COS) is proposed that adaptively clusters operators of the query plan into a number of groups based on their selectivity and computing cost using S-mean clustering.Experimental evaluation is provided to demonstrate the potential benefits of COS scheduling over the other scheduling strategies.COS can provide adaptive,flexible,reliable,scalable and robust design for continuous query processor.
