中国电力工业CO2减排战略分析

对电力工业主要的碳减排方式的减排成本、减排潜力及对化石能源消耗量的影响进行分析对比,并在此基础上对中国电力工业的碳减排战略进行了分析预测.研究结果表明:各种减排方式综合应用是我国电力工业碳减排的必然趋势,其中节能、核电以及水电、风电和太阳能发电等可再生能源发电在2050年的CO2减排潜力均可达到10亿吨以上,且可以节约大量化石能源,是应优先发展的重要减排技术.     

基于安全效能成本的资产全寿命周期管理研究

传统的管理模式使资产管理各环节分属不同部门管理,这不利于资产全寿命周期成本管理工作的开展。分析了基于安全、效能、成本(SEC)的资产全寿命周期管理的定义、具体指标与计算模型,并用一个具体事例来说明SEC管理模式的实现方式,最后讨论了SEC资产全寿命周期管理的管控措施。     

风电场对电力系统运行成本和市场价格的影响

将基于安全域的电力系统有功定价模型用于拟并网的风电场装机容量和风电场位置的论证中。采用按小时的平均日发电曲线表示风电场的运行约束,并通过比例因子来反映负荷随时间的变化。由于模型中计及了线路热稳定约束和暂态稳定约束,使风电场装机容量和风电场位置对市场价格、发电成本和安全成本影响的分析结果更符合实际。新英格兰10机39节点系统的示例表明,所得的影响分析结果可辅助电网规划人员就风电上网问题做出科学的评估。     

市场环境下电力系统机组检修规划模型

构建了基于市场竞争机制的机组检修规划模型。首先,发电商根据其效益分析确定其机组在各检修窗口的竞价费用,独立系统运行员（ISO）据此计算各机组在相应时段的满意度水平,两者均用以表征其在各时段检修及运行的意愿程度。基于此,建立了考虑检修竞价费用、满意度水平及系统切负荷水平的检修规划模型及基于满意度的费用结算机制。算例仿真结果表明,该模型可确保系统的可靠性及发电商的经济效益,并体现了公平、公正的市场原则。     

受端电网静态/动态无功补偿综合优化

提出了一种可同时考虑静态与动态无功补偿的无功补偿优化模型.在对负荷裕度的概率分析的基础上用最小二乘法构造电压崩溃的概率模型.对电压崩溃动态过程进行概率分析,对暂态和稳态过程中对电压稳定和电压质量有所影响的因素进行经济量化,提出了稳态运行费用和暂态运行费用的总和最小为目标函数的无功补偿综合优化模型.在此基础上通过动态仿真与静态分析相结合的方法逐步迭代求解最优补偿容量.华南某电网实际算例中的应用表明,综合无功补偿优化的结果具有最小的年运行费用和最大的故障后负荷裕度,可以显著改善受端系统运行的经济性和安全性.     

煤质多变下火电厂最经济煤种决策

我国火电厂大多无法燃烧设计煤种,煤质变差、煤价高涨和锅炉磨损爆管事故频发。为定量得到煤质变差后给火电厂带来的综合经济损失的计算模型,在某电厂进行了煤种变化对全厂经济性影响的试验研究。试验结果表明：设备维修费用、助燃油量、爆管泄漏的频率均与灰分呈指数关系变化;综合考虑标煤单价、设备维护费用、排放成本等各项因素,找到该厂当前最经济煤种,煤质参数介于设计煤种和劣质煤之间;并提出煤价波动体系下一种快捷的求取火电厂最经济煤种的计算方法。     

Optimal power flow using differential evolution algorithm

This paper presents an efficient and reliable evolutionary-based approach to solve the optimal power flow (OPF) problem. The proposed approach employs differential evolution algorithm for optimal settings of OPF problem control variables. The proposed approach is examined and tested on the standard IEEE 30-bus test system with different objectives that reflect fuel cost minimization, voltage profile improvement, and voltage stability enhancement. The proposed approach results are compared with the results reported in the literature. The results show the effectiveness and robustness of the proposed approach.     

基于FPGA低成本动目标侦测系统的设计与实现

对智能视频监控中常用的基于混合高斯背景模型的动目标侦测技术进行了研究分析,针对其运算量、模型数据两个关键的实时化难点,采用低成本FPGA与DDR的硬件架构,设计出适合并行处理特性的动目标侦测系统.在Altera的CycloneⅢ 系列FPGA实现了实物系统算法验证,实验表明,该低成本设计完全满足监控系统的实时性要求.     

基于BOM的目标成本决策系统设计与实现

目标成本是企业成本控制的奋斗目标，将成本控制在预定的目标之内，是提高企业竞争能力的重要环节，目标成本的制定是在综合考虑到未来一定时间内的有关产品的品种、数量、价格、税金、利润等诸多因素从而确定的成本水平，既可用于原有产品的生产、改造，也可应用于新开发产品的设计、试制。本系统是在物料清单的基础上，进行目标成本的分解，将改进后的成本与目标成本进行比较，找出差异进行反馈，以便分析挖潜，采取措施降低成本。     

Effective Location Based Services with Dynamic Data Management in Mobile Environments

With the proliferation of mobile computing technologies, location based services have been identified as one of the most promising target application. We classify mobile information service domains based on feature characteristics of the information sources and different patterns of mobile information access. By carefully examining the service requirements, we identify the dynamic data management problem that must be addressed for effective location based services in mobile environments. We then devise a general architecture and cost model for servicing both location independent and location dependent data. Based on the architecture and cost model, we propose a set of dynamic data management strategies that employs judicious caching, proactive server pushing and neighborhood replication to reduce service cost and improve response time under changing user mobility and access patterns. Detail behavior analysis helps us in precisely capturing when and how to apply these strategies. Simulation results suggest that different strategies are effective for different types of data in response to different patterns of movement and information access. Shiow-yang Wu is an associate professor of the Department of Computer Science and Information Engineering at National Dong Hwa University, Hualien, Taiwan, R.O.C. He received the BS and MS degrees in computer engineering from National Chiao Tung University, Hsinchu, Taiwan, ROC, and the PhD degree in computer science from the University of Texas at Austin in 1984, 1986, and 1995, respectively. His research interests include data/knowledge bases, mobile computing, distributed processing, intelligence information systems, and electronic commerce. Kun-Ta Wu was born in Taipei, Taiwan, R.O.C., in 1976. He received the B.S. degree in computer science from Soochow University, Taipei, Taiwan, R.O.C., in 1999 and the M.S. degree in computer science and information engineering from National Dong Hwa University, Hualien, Taiwan, R.O.C., in 2001. Currently, he is an Assistant Researcher in the Domestic Division at Science and Technology Information Center, National Science Council, R.O.C., as a member of Information Gathering and Analysis Group of National Information and Communication Security Taskforce. His research interests include mobile computing, wireless network and information security.