含风力发电的电动汽车充电站区间优化调度

针对风机出力的间歇性与波动性和电动汽车充电负荷的随机性使含风力发电的电动汽车充电站内的源、荷在一定范围内变化的问题,需要采用不确定性分析方法对其进行优化调度。不同于其他调度模型,文中以多场景方法模拟出的区间值代替点值作为风机出力和基础负荷的预测结果,并根据区间运算规则建立了含风力发电的电动汽车充电站区间优化调度模型。其次,由于辅助模型直接优化求解得出的调度方案和目标函数不一定是最优区间,因此提出了一种转换目标函数的方法,能够迅速求解得出模型中决策变量最优区间解和相应的目标函数最优区间值。最后通过算例仿真表明区间调度结果囊括了点值调度的所有可能运行工况,并且与鲁棒优化结果相比,区间优化结果的保守性有所降低,区间调度结果波动性更小,削峰填谷效果更好,证明了区间调度在处理不确定性调度问题时的优越性和有效性。

Mapping and Assessing Typhoon-induced Forest Disturbance in Changbai Mountain National Nature Reserve Using Time Series Landsat Imagery

Monitoring forest disturbances is important for understanding changes in ecosystems. The 1986 Typhoon Vera was a serious disturbance that severely impacted the forest ecosystems of Changbai Mountain National Nature Reserve. Although the typhoon disturbance occurred more than two decades ago, the effects of the typhoon still remain within the study area. Few studies have focused on mapping and assessing disturbances across broad spatial and temporal scales. For this study, we first generated a map of forest composition prior to the typhoon disturbance, which served as a baseline data for the extraction of disturbed area. Then, the Disturbance Index(DI) method was tested for mapping the extent and magnitude of disturbance in the study area by applying a Tasseled Cap transformation to the Landsat imagery. The Landsatbased DI method estimated that an area of 13,764.78 ha of forest was disturbed by the typhoon. Based on visual assessments, these results correspond closely with the reference map derived from ground surveys. These results also revealed the influence of local topographic features on the distribution of windthrow areas. Windthrow areas were more pronounced inareas with elevations ranging from 1,000 to 2,000 m, slopes of less than 10 degrees, and southwestern to northwestern aspects. In addition, the relatively long(25 years) post-typhoon recovery period assessed by this study provided a more comprehensive analysis of the dynamics of forest recovery processes over time. Windthrow areas did not recover immediately after the typhoon, likely due to forest management practices enacted at the time. So far, forest recovery has proceeded more rapidly at elevations below 1,400 m, particularly on western slopes within the study area. Finally, a time series of DI values within the study period suggests a secondary disturbance may have occurred between 2000 and 2001.

Comparison of the spatio-temporal dynamics of vegetation between the Changbai Mountains of eastern Eurasia and the Appalachian Mountains of eastern North America

The Changbai Mountains and the Appalachian Mountains have similar spatial contexts.The elevation,latitude,and moisture gradients of both mountain ranges offer regional insight for investigating the vegetation dynamics in eastern Eurasia and eastern North America.We determined and compared the spatial patterns and temporal trends in the normalized difference vegetation index(NDVI)in the Changbai Mountains and the Appalachian Mountains using time series data from the Global Inventory Modeling and Mapping Studies 3^(rd) generation dataset from 1982 to 2013.The spatial pattern of NDVI in the Changbai Mountains exhibited fragmentation,whereas NDVI in the Appalachian Mountains decreased from south to north.The vegetation dynamics in the Changbai Mountains had an insignificant trend at the regional scale,whereas the dynamics in the Appalachian Mountains had a significant increasing trend.NDVI increased in 55% of the area of the Changbai Mountains and in 95% of the area of the Appalachian Mountains.The peak NDVI occurred one month later in the Changbai Mountains than in the Appalachian Mountains.The results revealed a significant increase in NDVI in autumn in both mountain ranges.The climatic trend in the Changbai Mountains included warming and decreased precipitation,and whereas that in the Appalachian Mountains included significant warming and increased precipitation.Positive and negative correlations existed between NDVI and temperature and precipitation,respectively,in both mountain ranges.Particularly,the spring temperature and NDVI exhibited a significant positive correlation in both mountain ranges.The results of this study suggest that human actives caused the differences in the spatial patterns of NDVI and that various characteristics of climate change and intensity of human actives dominated the differences in the NDVI trends between the Changbai Mountains and the Appalachian Mountains.Additionally,the vegetation dynamics of both mountain ranges were not identical to those in previous broader-scale studies.

The driving factors and their interactions of fire occurrence in Greater Khingan Mountains, China

Fire is an important disturbance in terms of forest management.A comprehensive understanding of the relationships between the spatial distribution of fire occurrence and its driving factors are critical for effective forest fire management.To reveal biogeoclimatic and anthropogenic influences,this study introduced a geographical detector model to quantitatively examine the effects of multiple individual factors and their combinations on spatial patterns of fire occurrence in the Greater Khingan Mountains between 1980 and 2009.The geographical detector computes the explanatory power(q value)to measure the connection between driving factors and spatial distributions of fire occurrence.Kernel density estimation revealed the spatial variability of fire occurrence which was impacted by bandwidth.30 km might be the optimal bandwidth in this study.The biogeoclimatic and anthropogenic effects were explored using topography,climate,vegetation,and human activity factors as proxies.Our results indicated that solar radiation had the most influence on the spatial pattern of fire occurrence in the study area.Meanwhile,Normalized Difference Vegetation Index,temperature,wind speed,and vegetation type were determined as the major driving factors.For various groups of driving factors,climate variables were the dominant factors for the density of fire occurrence,while vegetation exerted a strong influence.The interactions between the driving factors had a more significant impact than a single factor.Individually,the factors in the topography and human activity groups exhibited weaker influences.However,their effects were enhanced when combined with climate and vegetation factors.This study improves our understanding of various driving factors and their combined influences on fire occurrences of the study area in a spatial context.The findings of this study verify that the geographical detector is applicable in revealing the driving factors of fire occurrence.

元素地球化学揭示的长江中下游下蜀黄土物源及其环境意义

中晚更新世以来长江中下游地区粉尘堆积广泛发育,这些广义上可称之为"下蜀土"的区域粉尘堆积,典型代表有"九江下蜀土"、"安徽下蜀土"、"南京下蜀土"。其形成的年代及其粉尘堆积属性已基本明了,但是其物质来源却存在较大争议。详细分析了这些粉尘的元素地球化学特征,并与黄土高原黄土和红土进行了对比,结果表明:1)长江中下游的下蜀黄土均非来自北方的黄土高原,且九江、安徽、南京三地物源相互之间也存在显著差异,均为近源堆积,北方粉尘的作用过去被严重高估了;2)冰期背景下,长江中下游地区气候普遍恶化,区内大面积沙化和厚层粉尘堆积是现代亚热带湿润季风区对冰期气候环境响应的结果,是特殊地形条件和气候背景下冬季风近地面气流侵蚀—搬运裸露的河(湖)漫滩而形成的区域风沙—粉尘堆积体系,长江流域这种区域堆积体系及其地环境与地生态效应在以往的研究中没有得到应有的重视和认识。