含大规模储热的光热电站—风电联合系统多日自调度方法

含储热的光热电站具有良好的可调度性,其可调度能力与实时光照功率和储热装置内存储的能量有关。当光热电站与风电组成联合系统发电时,光热电站可以削减风电的不确定性,但由于风、光功率情况在不同调度日间具有波动性,因此联合系统需要的光热电站的可调度能力和光热电站的实际可调度能力每天均不相同。文中建立了基于场景方法的光热电站与风电联合系统的多日随机调度模型。该模型充分考虑多日风、光功率预测的不确定性,进行联合系统日前自调度。最后,通过算例分析,讨论了不同预测时间尺度、储能参数取值对自调度结果的影响。     

Integrated assessment on multi-temporal and multi-sensor combinations for reducing cloud obscuration of MODIS snow cover products of the Pacific Northwest USA

MODIS (Moderate Resolution Imaging Spectroradiometer) snow cover products, of daily, freely available, worldwide spatial extent at medium spatial resolution, have been widely applied in regional snow cover and modeling studies, although high cloud obscuration remains a concern in some applications. In this study, various approaches including daily combination, adjacent temporal deduction, fixed-day combination, flexible multi-day combination, and multi-sensor combination are assessed to remove cloud obscuration while still maintain the temporal and spatial resolutions. The performance of the resultant snow cover maps are quantitatively evaluated against in situ observations at 244 SNOTEL stations over the Pacific Northwest USA during the period of 2006-2008 hydrological years. Results indicate that daily Terra and Aqua MODIS combination and adjacent temporal deduction can reduce cloud obscuration and classification errors although an annual mean of 37% cloud coverage remains. Classification errors in snow-covered months are actually small and tend to underestimate the snow cover. Primary errors of MODIS daily, fixed and flexible multi-day combination products occur during transient months. Flexible multi-day combination is an efficient approach to maintain the balance between temporal resolution and realistic estimation of snow cover extent since it uses two thresholds to control the combination processes. Multi-sensor combinations (daily or multi-day), taking advantage of MODIS high spatial resolution and AMSR-E cloud penetration ability, provide cloud-free products but bring larger image underestimation errors as compared with their MODIS counterparts.     

面向弃风消纳的电储能-热电分级协调优化方法

中国北方地区存在高比例的热电联产机组,受冬季采暖负荷制约,调节能力有限,引发冬季弃风问题,增加电储能和储热设备是提高热电联产机组调节能力的重要手段。研究在电力辅助服务市场环境下的热电联产机组与电储能、储热设备的协调优化运行方法,分别建立以电储能设备和热电联产机组调峰效益最大和蓄热效益最大为目标,考虑弃风最大化消纳、系统供热需求以及热电联产机组、电储能和储热设备运行约束的分级协调优化模型。系统仿真测试表明：所提方法能够协调优化电储能和储热装置的运行,充分利用储热设备的多日调节能力,提高系统在电力市场中的运行收益,有效减少弃风。研究结果对解决当前电力市场环境下北方地区的冬季弃风问题具有一定价值。     

基于快速动态时间弯曲和最小覆盖球的多日负荷曲线聚类方法

现有负荷曲线聚类的研究主要基于单日负荷曲线或多日同时刻的负荷分布开展,忽略了负荷在多日间的波动特性和负荷曲线的时间滞后特性,导致聚类结果的准确度和鲁棒性不足。综合考虑负荷的波动特性和时间滞后特性,提出一种快速动态时间弯曲和最小覆盖球相结合的多日负荷曲线聚类方法。在考虑负荷时间滞后特性的基础上,利用快速动态时间弯曲和多维尺度缩放对负荷曲线进行降维;为每个降维负荷迭代寻找最小覆盖球,并计算不同覆盖球的球间相似度;利用谱聚类算法得到相似度矩阵。算例结果表明,所提方法在准确度和鲁棒性上较传统方法有一定优势。     

面向弃风消纳的电储能-热电分级协调优化方法

中国北方地区存在高比例的热电联产机组,受冬季采暖负荷制约,调节能力有限,引发冬季弃风问题,增加电储能和储热设备是提高热电联产机组调节能力的重要手段。研究在电力辅助服务市场环境下的热电联产机组与电储能、储热设备的协调优化运行方法,分别建立以电储能设备和热电联产机组调峰效益最大和蓄热效益最大为目标,考虑弃风最大化消纳、系统供热需求以及热电联产机组、电储能和储热设备运行约束的分级协调优化模型。系统仿真测试表明：所提方法能够协调优化电储能和储热装置的运行,充分利用储热设备的多日调节能力,提高系统在电力市场中的运行收益,有效减少弃风。研究结果对解决当前电力市场环境下北方地区的冬季弃风问题具有一定价值。