毕业设计(论文)外文参考资料及译文-自动化操作的大型电力系统广大范围的市场供需和设备的是运行状况.doc
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1、毕 业 设 计(论 文)外 文 参 考 资 料 及 译 文译文题目: 自动化操作的大型电力系统广大范围 的市场供需和设备的运行状况 学生姓名: 朱礼梅 学号: 0921410039 专业: M09电气工程及其自动化 所在学院: 金陵科技学院 指导教师: 陈丽娟 职称: 2011年 3月 19 日说明:要求学生结合毕业设计(论文)课题参阅一篇以上的外文资料,并翻译至少一万印刷符(或译出3千汉字)以上的译文。译文原则上要求打印(如手写,一律用400字方格稿纸书写),连同学校提供的统一封面及英文原文装订,于毕业设计(论文)工作开始后2周内完成,作为成绩考核的一部分。AUTOMATING OPERAT
2、ION OF LARGE ELECTRIC POWER SYSTEMS OVER BROAD RANGES OF SUPPLY/DEMAND AND EQUIPMENT STATUSAbstract One of the ultimate challenges in operating todays electric power grids is in designing automation for managing the system as demand varies over broad ranges and the status of major equipment changes.
3、 These changes are often hard to predict and it is, therefore, fundamentally impossible to design for the worst case scenarios; such scenarios are not known due to the very combinatorial nature of the problem. One possible way forward is to pursue automation for facilitating systems adjustments as t
4、he conditions vary. In this chapter we propose an extension of todays hierarchical control of electric power grids as one direction toward such automation. The approach is strongly motivated by the recognition that it has become insufficient to rely solely on operators decisions; instead, more on-li
5、ne information gathering and active decision making at various layers of the grid are needed. The proposed generalization is introduced by relaxing some critical assumptions underlying current operating practices, and by deriving layers of models so that each model can capture the events and phenome
6、na in the power grid at the spatial and temporal scales that are appropriate for each level of decision. These models are used for quasi-stationary state estimation and automated control for the system to adjust smoothly to on-going changes. This is in sharp contrast to todays approach in which auto
7、mation is only used during normal operation, while during abnormal conditions major decisions are made by the humans. The resulting layered-architecture should reduce the complexity of the problem significantly. More important, it should provide the decision makers at each layer with the most releva
8、nt dynamic information that is needed for their own decision level, and at the same time provide the information necessary for the decision makers to respond and adAPPLIED MATHEMATICS FOR POWER SYSTEMS just to the overall system objectives. The layered models form a basis for an information technolo
9、gy (IT) infrastructure that can be proven to ensure pre-specified performance at various layers and in the system as a whole. An important observation is that when the assumptions typically made in todays system control are met, the proposed control generalization closely resembles current Superviso
10、ry Control and Data Acquisition (SCADA) and operating practices. In this sense, the approach is a natural outgrowth of what is already in place and should be considered for ensuring reliable and efficient operation over the broad ranges of conditions and equipment status. Keywords: IT infrastructure
11、, multi-layered electric power system models, quasistationary estimation, quasi-stationary electric power systems control, large-scale computations.1. IntroductionPossibly one of the biggest causes of insecure and inefficient operation of todays electric power systems comes from a sub-optimal use of
12、 available resources because of hard-to-predict demand variations and equipment failures. Current operating practices in dealing with both types of uncertainties have been mainly preventive and off-line, without resorting to automated responses to the events and uncertainties. The system has been au
13、tomated only to respond to relatively small demand fluctuations around historic patterns. We suggest here that this is one of the major distinctions between what it is and what it might be in the future electric power systems. These systems must become more automated over wide ranges of supply/deman
14、d patterns and equipment status. While the communications and control hardware are readily available, it is essential to pursue this inevitable automation based on systematic modeling, estimation, and control. However, moving toward more automation could defeat its own purpose unless an IT infrastru
15、cture is in place to facilitate formation and coupling of sub-networks within the grid as they define sub-objectives according to their own needs and the changing system-wide conditions. Moreover, depending on particular organizational industry structures in place, the nature of complexity of this a
16、utomation varies significantly. At least three structures are of direct interest here: The partitioning of the large electric power grid is given a priori. The main problem here is to introduce an IT infrastructure in support of monitoring and control for providing pre-cursors of extreme conditions,
17、 and to adjust available resources so that the system is Automating Operation of Large Electric Power Systems 107 adapting smoothly as the operating conditions and equipment status vary. The major portion in this chapter concerns this problem. A more futuristic problem of automation is the one in wh
18、ich the boundaries of sub-networks are allowed to evolve according to their distributed sub-objectives. The main problem here is to introduce an IT infrastructure for facilitating both distributed decision making by these sub-networks and, at the same time, provide dynamic coupling with the other su
19、b-networks so that performance objectives are met at several higher layers of the industry organization. w Finally, the most complex problem of automation is the one in which economic and regulatory and organizational signals are modeled as endogenous together with the physical and IT infrastructure
20、s. This is the problem of long-term evolution of the electric power grid as driven by regulatory, economic, and technological signals. The IT infrastructure here, in contrast with the previous two, is heterogeneous and spans broad range of time horizons and system details. The starting issue for all
21、 three cases is the fact that the overall network complexity is outside of humans ability to master at the right time and the right level of detail necessary for best decision making. The boundaries between automation and human decision making are different in the three cases above. In this chapter
22、we conceptualize an approach to the IT infrastructure for the first case. In our view, this automation for enhanced performance over a broad range of supply/demand patterns and equipment status is critical for avoiding unexpected system-wide failures such as the August 14, 2003 Northeast US blackout
23、. In the last part of this chapter we provide ideas for extendingour proposed approach to the other two cases. In this chapter we explore fundamentals of possible next generation automation for managing electric power systems over a broad range of demand/supply and equipment status. The approach bui
24、lds upon todays operating practices by conceptualizing sufficiently adaptive models with respect to time and space needed to capture relevant phenomena even when critical assumptions under which todays control is designed fail to hold. These models are grouped according to: (1) the type of operating
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