多态场景下考虑出行链重构的电动汽车多目标协同优化调度

电动汽车用户日内的充电计划具有规律性,但在突发事件影响下,电动汽车用户的充电行为则具有突发性和主观性。突发事件由用户影响到电动汽车的充放电过程,最终波及电力系统的稳定运行。首先,考虑实际出行中距离变化时用户的充电意愿,提出充电意愿模型,模拟用户的充电意愿区间;然后,基于电动汽车出行时空特性,将影响调度计划的突发事件分为4类,模拟4种事件对既定调度计划的影响,并综合考虑气温和电价等因素,对电动汽车进行充放电调度;最后,提出多态场景下储能站协同电动汽车的能量管理策略,对常态及两种极端条件下的电动汽车进行充放电调度。采用区域电网进行仿真,分析出行链重构在行为场景、事件类型、调度策略、集群规模、用户参与度和风电规模的条件中对电动汽车充放电调度的影响,验证了所提模型的合理性和有效性。

Low Dynamic Range Solutions to the High Dynamic Range Imaging Problem

While capturing a real world scene using a common digital camera, due to limitations of the sensor dynamic range, we will not be able to capture the entire dynamic range of the some. This problem is evident while capturing a picture of a some which has both brightly and poorly illuminated regions. High Dynamic Range （HDR） imaging aims to recover the entire dynamic range of the scene by compositing multi-exposure images. Tone reproduction is required for displaying HDR images as the corresponding Low Dynamic Range（LDR） images on common displays. This paper discusses novel approaches to reconstruct LDR images directly from multi-exposure images. It is assumed that there is no knowledge of camera response function and other camera settings. At last, it is explained how this task can be achieved effectively for static and dynamic scenes.