在深化电力市场改革以及促进需求侧消纳清洁能源的背景下,售电商需综合考虑火电年度合同电量以及清洁能源消纳年度合同电量,在合理安排年度合同电量分解的基础上,根据月度用电量预测偏差优化月度市场交易策略,构建了售电商月度购电滚动修正优化策略框架.基于月度市场电价波动风险分析,提出了年度合同电量分解到月度合同电量的进度系数.考虑了清洁能源出力波动的季节性修正因子,从而建立了满足偏差考核的售电商月度最优购电策略模型.算例分析了电价波动以及清洁能源消纳年度合同电量对售电商月度市场竞价策略的影响,对售电商承担新能源消纳权责、降低竞价风险、满足偏差考核具有现实意义.

The ubiquitous power internet of things (UPIoT) can make full use of advanced communication technologies to realize the wide interconnection of power generation, transmission, distribution and use in the power system, thus providing technical support for the massive access of distributed generations (DGs). Under the background of the UPIoT, the idea of the P2P technology was applied to establish the decentralized scheduling architecture of distributed generations, so that the optimal scheduling could be completed through information interaction based on communication among distributed generations. The distributed sub-gradient algorithm was applied to solve the established P2P optimal scheduling model, and the doubly stochastic matrix was introduced to construct the connection matrix between nodes in the UPIoT. Finally, the feasibility and effectiveness of the optimization model and its solution method were verified through simulation examples, and the interrupts and errors that may be encountered in the communication process were also discussed.

学习投入理论建立了学习投入、学习行为、学习效果之间的关联,为预测学习效果提供了良好的理论架构.文章根据认知与情感投入因素、网络学习行为、学习效果的具体分类,建立了基于学习投入理论的网络学习行为模型,并以“网络教学平台设计与开发”课程为例进行了实证研究,梳理了模型中各要素之间的关系,并通过优化模型的影响因素及其关联,最终构建了基于学习投入理论的网络学习行为修正模型.文章认为,认知投入因素中的认知能力与策略、元认知和情感投入因素中的唤醒、兴趣均显著影响社会性学习行为,在线讨论行为则显著影响满意度和课程持续使用意向.

学习分析可以帮助教师更加全面地了解学生，挖掘深层问题，同时可视化的反馈也可以使学生自我诊断并及时修正。本文从西蒙斯过程模型入手，解读了四个关键环节：数据类型、分析过程、追踪预测、个性化或适应。笔者使用模型框架对国外三所高校实际案例的具体环节进行概述性分析，对比了学习分析在应用过程中的差异及其可能产生的原因，并提出相关建议。