According to the demand of sustainable development and low-carbon electricity, it is important to develop clean resources and optimize scheduling generation mix. Firstly, a novel method for probabilistic production si...According to the demand of sustainable development and low-carbon electricity, it is important to develop clean resources and optimize scheduling generation mix. Firstly, a novel method for probabilistic production simulation for wind power integrated power systems is proposed based on universal generating function(UGF), which completes the production simulation with the chronological wind power and load demand. Secondly,multiple-period multiple-state wind power model and multiple-state thermal unit power model are adopted, and both thermal power and wind power are coordinately scheduled by the comprehensive cost including economic cost and environmental cost. Furthermore, the accommodation and curtailment of wind power is synergistically considered according to the available regulation capability of conventional generators in operation. Finally, the proposed method is verified and compared with conventional convolution method in the improved IEEE-RTS 79 system.展开更多
叶面积指数(Leaf Area Index,LAI)是生物地球化学循环中重要的植被结构参数。针对目前基于我国GF-1 WFV卫星影像的夏玉米多生育期LAI反演研究较少的问题,基于不同隐含层构建BP神经网络模型(BP1模型和BP2模型),对比分析BP1模型、BP2模型...叶面积指数(Leaf Area Index,LAI)是生物地球化学循环中重要的植被结构参数。针对目前基于我国GF-1 WFV卫星影像的夏玉米多生育期LAI反演研究较少的问题,基于不同隐含层构建BP神经网络模型(BP1模型和BP2模型),对比分析BP1模型、BP2模型和6种统计模型(NDVI、RVI、DVI、EVI、SAVI、ARVI)反演之间的精度差异,并根据实测数据绘制BP1模型和BP2模型的夏玉米多生育期LAI动态变化图。结果表明:LAI与6种常用的统计模型均有良好相关性,其中NDVI指数方程式回归模型拟合度最优;BP神经网络模型整体R 2略小于统计模型,而RMSE则小于统计模型,取得了与实测值差异更小的结果,统计模型与BP神经网络模型各有优劣之处;BP2模型在R 2和RMSE均优于BP1模型,能获得更为精确的反演值,BP2整体预测精度更高;基于BP神经网络模拟夏玉米生育期反演,LAI值呈现缓慢升高—快速增长—逐渐减小的S型变化过程,基本符合作物生长规律。该研究结合不同隐含层建立的BP神经网络模型,为GF-1卫星在作物叶面积指数多生育期反演的应用推广提供了方法支撑。展开更多
The repair kit problem seeks an optimal stock of parts for a repair kit for purposes of remote repairs. This problem has often been studied when restocking is possible between each order, or when the number of orders ...The repair kit problem seeks an optimal stock of parts for a repair kit for purposes of remote repairs. This problem has often been studied when restocking is possible between each order, or when the number of orders is known between each restocking. This research evaluates a model for the repair kit stocking problem for which there is multiple-period demand with a known time interval between each restocking, but an unknown number of on-site repair visits is required during the restocking period. Most previous work focuses on minimum cost subject to some minimum service level;in the case where the value of technician time and customer service is relatively large, the space constraint of the kit and volume of parts comes into play. This work contributes to the literature by testing the robustness of a heuristic originally proposed by [1] in a field study. We conduct numerical experiments to evaluate the heuristic over a wide range of parameterizations. Our results indicate that the heuristic performs close to optimum, and its performance improves as the problem size grows.展开更多
基金supported by National High Technology Research and Development Program of China (863 Program) (No. 2012AA050208)the Program of the National Natural Science Foundation of China (No. 51177043)
文摘According to the demand of sustainable development and low-carbon electricity, it is important to develop clean resources and optimize scheduling generation mix. Firstly, a novel method for probabilistic production simulation for wind power integrated power systems is proposed based on universal generating function(UGF), which completes the production simulation with the chronological wind power and load demand. Secondly,multiple-period multiple-state wind power model and multiple-state thermal unit power model are adopted, and both thermal power and wind power are coordinately scheduled by the comprehensive cost including economic cost and environmental cost. Furthermore, the accommodation and curtailment of wind power is synergistically considered according to the available regulation capability of conventional generators in operation. Finally, the proposed method is verified and compared with conventional convolution method in the improved IEEE-RTS 79 system.
文摘The repair kit problem seeks an optimal stock of parts for a repair kit for purposes of remote repairs. This problem has often been studied when restocking is possible between each order, or when the number of orders is known between each restocking. This research evaluates a model for the repair kit stocking problem for which there is multiple-period demand with a known time interval between each restocking, but an unknown number of on-site repair visits is required during the restocking period. Most previous work focuses on minimum cost subject to some minimum service level;in the case where the value of technician time and customer service is relatively large, the space constraint of the kit and volume of parts comes into play. This work contributes to the literature by testing the robustness of a heuristic originally proposed by [1] in a field study. We conduct numerical experiments to evaluate the heuristic over a wide range of parameterizations. Our results indicate that the heuristic performs close to optimum, and its performance improves as the problem size grows.
