Previous Virtual Network (VN) embedding researches mostly focus on developing heuristic algorithms to enhance the efficiency of a physical resource. However, in the equal-scale condition, where the scale of a VN is si...Previous Virtual Network (VN) embedding researches mostly focus on developing heuristic algorithms to enhance the efficiency of a physical resource. However, in the equal-scale condition, where the scale of a VN is similar to that of a substrate network, the number of successfully mapped VNs decreases sharply since bottlenecks form easily in the substrate network and disturb the embedding process. In this paper, reversed and bidirectional irrigation methods are proposed for the equal-scale and all-scale conditions. The two proposed methods can be combined with most of the existing heuristic algorithms and map a relatively large number of VNs by reducing the potential substrate bottlenecks. The simulation results show that the reversed irrigation method almost doubles the successfully mapped Revenue than the traditional one in the equal-scale condition. Meanwhile, the bidirectional irrigation method achieves the synthetically best performance in almost all scale conditions.展开更多
基于荷电状态(state of charge,SOC)控制储能系统参与一次调频时,由于储能系统出力约束条件较为单一,因而限制了储能系统的性能。针对此问题提出一种基于储能系统多重约束的一次调频策略。首先,把通过双层模糊控制方法确定储能系统多时...基于荷电状态(state of charge,SOC)控制储能系统参与一次调频时,由于储能系统出力约束条件较为单一,因而限制了储能系统的性能。针对此问题提出一种基于储能系统多重约束的一次调频策略。首先,把通过双层模糊控制方法确定储能系统多时间尺度调频死区作为第1重约束条件,避免火电机组与储能电池频繁动作。其次,将SOC作为第2重约束条件,约束因子作为第3重约束条件,基于logistic曲线构建惯性与下垂综合控制模型,约束储能系统出力。最后,通过高精度SOC构建快速均衡函数,缩短SOC均衡时间。通过搭建仿真模型分别在阶跃负荷扰动和连续负荷扰动的工况下验证所提控制策略有效性。展开更多
基金supported by the National Basic Research Program of China under Grants No.2012CB315801,No.2011CB302901the National Science and Technology Major Projects under Grant No.2010ZX03004-002-02
文摘Previous Virtual Network (VN) embedding researches mostly focus on developing heuristic algorithms to enhance the efficiency of a physical resource. However, in the equal-scale condition, where the scale of a VN is similar to that of a substrate network, the number of successfully mapped VNs decreases sharply since bottlenecks form easily in the substrate network and disturb the embedding process. In this paper, reversed and bidirectional irrigation methods are proposed for the equal-scale and all-scale conditions. The two proposed methods can be combined with most of the existing heuristic algorithms and map a relatively large number of VNs by reducing the potential substrate bottlenecks. The simulation results show that the reversed irrigation method almost doubles the successfully mapped Revenue than the traditional one in the equal-scale condition. Meanwhile, the bidirectional irrigation method achieves the synthetically best performance in almost all scale conditions.
文摘基于荷电状态(state of charge,SOC)控制储能系统参与一次调频时,由于储能系统出力约束条件较为单一,因而限制了储能系统的性能。针对此问题提出一种基于储能系统多重约束的一次调频策略。首先,把通过双层模糊控制方法确定储能系统多时间尺度调频死区作为第1重约束条件,避免火电机组与储能电池频繁动作。其次,将SOC作为第2重约束条件,约束因子作为第3重约束条件,基于logistic曲线构建惯性与下垂综合控制模型,约束储能系统出力。最后,通过高精度SOC构建快速均衡函数,缩短SOC均衡时间。通过搭建仿真模型分别在阶跃负荷扰动和连续负荷扰动的工况下验证所提控制策略有效性。
基金sponsored by the National Key Research and Development Program of China (Grant No.2018YFC0807801)the Yueqi Eminent Scholar Program (Grant No.2019JCA01)of China University of Mining and Technology (Beijing).
