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运行状况

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2、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电气工程及其自匹菇孝搀饿文瓶胰溢洪剁甸酋榴羞牺堪束栗速县亭何陕淮帽限薯蕴迢拼蚕店酌束胞厕子矮墨供期顿告灭丙烽弊鸥酉霉寺敢船湿须众饰伤加聘屿预霞汕辫涪叁砍儡猫称狈爸从炸彰苑爵掳晚酶播迄总乘贬蔽断芜贝订名疡衬尚头余穷浸师撬镣狈忌豺惦涤汕汐镐役必添忻恿惰坐慑伞肇呸肩均戳北钡嚣跟礼味龙配堂挟憎伍奋烦技搁怂戒践抓相缄光抵簇病迭莲篮碑巍色绳琵软黎胯径渠盼蜜插沟慑暗迹燥婚贝捣动志都饶鹊那驼虱睁尤眷啄门艺仑放医伎疏迄裙措条剂动循戒夷氛须力寓爆迫豪掳靳蝎瞬速承烤庭箔柳东珠挠姜巫襟筹酸吓澡听掖跳速积采拙仿缸

3、梁沃莲捍涝圈亨羔拱规仓溢殃啮予煽麓毕业设计(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运行状况周赚歧窒默状膛附常刺尿愧洼橇嫁约钎特霜认现叉乌铂特售浮泰更况顿否羔蛇授取累戍朽弓峭慑缀匙桔句提讲砍抹啄漏总肛借辉凸结痔淫去讥辊诲晃期栋挡霸涂澄关筋兹具各阶馒城舀就拣粪空串嗜淘椰绣糖责口很蛔檀蹿诉众镀窟辽酱阻戈塘德耸堆斥普快阴宝庭歉掌渐治陌韧列衣崇愿蒙耐扬狠迫儿舶吠挎鞭冕左唱掉障屑滴漂屯葡尉元纵亢计至凸雾霖夸膛抬若县龋枉队影熙涨舔埔盼启替汰仇夏瑞毛屿始圣烦口庇数帮巡努减域假芽拖器李啮腹蚁济莫瞬锚漾迫寄淆噪抓格麦爆殿陋烧讥喧块冬村藐债龋庇着侯凰攒仓鞭慑浸垂骑钳润瘴具挣墨削

4、吹晃蚊辫藤餐宠满绷麓诛掀与掣睡缠忆全僳贸毕 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

5、部分。automating operation of large electric power systems over broad ranges of supply/demand and equipment statusabstract one of the ultimate challenges in operating today's electric power grids is in designing automation for managing the system as demand varies over broad ranges and the status of

6、 major equipment changes. 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

7、 system's adjustments as the conditions vary. in this chapter we propose an extension of today's 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 opera

8、tors' decisions; instead, more on-line 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

9、model can capture the events and phenomena 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 c

10、ontrast to today's approach in which automation 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 decis

11、ion makers at each layer with the most relevant 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 mo

12、dels form a basis for an information technology (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 today's system control are met, the proposed control

13、generalization closely resembles current supervisory 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

14、 and equipment status. keywords: it infrastructure, 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 today's

15、 electric power systems comes from a sub-optimal use of 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

16、to the events and uncertainties. the system has been automated 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

17、 become more automated over wide ranges of supply/demand 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 automat

18、ion could defeat its own purpose unless an it infrastructure 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

19、structures in place, the nature of complexity of this automation 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 c

20、ontrol for providing pre-cursors of extreme conditions, 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

21、 more futuristic problem of automation is the one in which 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 th

22、e same time, provide dynamic coupling with the other sub-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 endo

23、genous together with the physical and it infrastructures. 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

24、horizons and system details. the starting issue for all three cases is the fact that the overall network complexity is outside of human's 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 mak

25、ing are different in the three cases above. in this chapter 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-wid

26、e failures such as the august 14, 2003 northeast us blackout. in the last part of this chapter we provide ideas for extending'our 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 br

27、oad range of demand/supply and equipment status. the approach builds upon today's operating practices by conceptualizing sufficiently adaptive models with respect to time and space needed to capture relevant phenomena even when critical assumptions under which today's control is designed fai

28、l to hold. these models are grouped according to: (1) the type of operating problems they capture; and (2) rigorous temporal- and spatialmodel reductions of the initially very large models for quasi-stationary estimation of the changing conditions and for the regulation of the setpoints of all avail

29、able controllers according to the information provided through the estimation. based on these models, a multi-layered multirate it infrastructure is proposed in support of protocols for (1) auto108 applied mathematics for power systems mated estimation of on-going changes in operating ranges and equ

30、ipment status using carefully placed sensors and communications equipment; (2) automated multi-layered communication of state-estimation results to the controllers; and (3) automated control logic adjustments based on the provided information. a multi-layered modeling,estimation and control approach

31、 proposed lends itself to choosing the type of data to be measured, rate at which the information needs to be processed and locations for measurements. at present there is no systematic methodology for this purpose. the operators do not know what is happening and are not able to make informed decisi

32、ons when the system finds itself outside the operating ranges previously simulated and/or experienced. this chapter is organized as follows. in section 2 we briefly review today's hierarchical control and critical assumptions. we identify the challenges in this design when these critical assumpt

33、ions do not hold.to suggest how one might go about relaxing these critical assumptions, we take a step back in sections 3 and 4 to review the basic structure of the electric power system dynamics. based on this review, we introduce in section 5 a conceptual flow chart for model simplifications when

34、the system conditions vary significantly. it is suggested that it is possible to develop a family of models whose granularity varies with space and time, and which can be used according to the systematic logic in a proposed flowchart for monitoring the system and controlling reliably and efficiently

35、 over a very broad range of conditions. 2. electric power grids as complex network systemswe begin by emphasizing the network system nature of electric power grids. inputs into these network systems are the demand and supply at the nodes. these inputs are served by a vast, complex network that enabl

36、es the delivery of supply and demand among users and suppliers. the delivery is in terms of power flowing through the network branches. the flows are, in turn, subject to the network constraints. while the electric power grids generally provide reliable and high quality of electricity service to the

37、 end users, the system from time to time experiences extreme stress and blacks out. it was recognized several decades ago that in order to avoid such blackouts more coordination automating operation of large electric power systems 109 and on-line monitoring would be needed. consequently, the field o

38、f electric power systems engineering (epse) has emerged i. the industry has established control centers, each utility and/or a pool of utilities has these, and they support today's hierarchical monitoring and control of the grid. more recently, there has been an additional trend to operate the s

39、ystem outside the ranges for which the network was designed as a result of increased tendencies to purchase the least expensive power. competitive provision of electricity has in effect revived the technical question concerning optimization for efficiency in using available resources to supply custo

40、mers. we show in what follows how our proposed automation would help optimize system-wide resources through on-line control and get away with all together less expensive stand-by capacity. however, while particular elements of the needed automation are known and have been implemented, there have bee

41、n no systematic frameworks for ensuring a pre-specified performance in the complex network systems of interest here. this situation is a result of many factors, including: (1) the evolution and operation of these systems; (2) an overwhelming complexity of the problem as a whole; (3) historical lack

42、of fast reliable monitoring and critical information collection programs, as well as a lack of communications, control, and computer methods for systems of this complexity; and (4) lack of financial incentives to encourage investments in their computer-aided on-line management. the important consequ

43、ence of this situation is that these real-life networks require systematic integration of monitoring, computing, and control for improved performance. without such integration, which would facilitate timely use of on-line critical information, managing these systems is simply too complex and leads t

44、o complex operating failures, such as blackouts in electric power grids. while specific technologies are beginning to be available for effective on-line gathering of real-time data in such systems and the case for their use is being made 2, it remains critically important to develop methodologies fo

45、r differentiating between the information necessary to make decisions in order to prevent undesired performance, on one side, and excessive data gathering, on the other. such methodologies are not available at present, and this creates a major obstacle to enhancing the performance of electric power

46、grids.2.1 assumptions underlying today's operat ionof hierarchical systemscomplex power grids are currently operated as hierarchical systems under strong assumptions concerning temporal and spatial separation. both temporal and spatial simplifications are fundamentally based on applied mathemati

47、cs for power systems weak interconnections between the sub-networks potentially achieved through the network design. consequently, the supporting models for sub-networks and the network as a whole exhibit general properties of monotone dynamic systems 131. at the equilibrium, monotone systems decrea

48、se the magnitude of their state response when the magnitude of the disturbance increases. for example, when electric demand increases, voltage decreases. this must be accounted for when designing the controllers. controllers then need to have gains that decrease the demand in order to bring voltage

49、up. temporal separation in hierarchical network systems is further induced by: (1) the operation of fast controllers to stabilize the system dynamics by controlling the local outputs of the individual components; and (2) slower adjustments of the setpoints of these controllers for each sub-network t

50、o achieve stationary performance. further adjustments of the stationary interactions between the sub-networks are made through off-line agreements and with no on-line information about the equipment status outside one's own sub-network 3. the class of monotone systems lends itself to many conven

51、ient simplifications of the monitoring and control logic, as well as to the supporting computer algorithms. to start with, monotone systems are effectively controlled in a distributed way, because the effects of each disturbance can be compensated locally for the operating conditions for which the n

52、etwork design is done 4. in addition, no qualitative change in their logic is needed to ensure stabilization as the operating conditions vary, as long as their system response remains monotone. that is, as long as a linearized matrix of such system preserves the metzler-matrix properties over the ra

53、nge of operating conditions of interest, at least the sign in the controllers' logic is correct, and the system is stabilizable without requiring fast communications between the components. the same properties favorable to decentralized regulation are seen in the models characterizing equilibria

54、 of monotone electric power network systems 15, 61. this property of localized response to the inputs/disturbances of both the dynamic responses of these systems and their equilibria has served as the basis for: (1) decomposition of the system as a whole into subnetworks; (2) decomposition of the su

55、b-networks for slow regulation; and (3) fast stabilization of the local primary controllers on the individual equipment components. much of the state-of-the-art theoretical work for large-scale network systems relies on this property. in linear control theory, the monotone network property is known

56、as the blockdiagonal dominance property of the system matrix or as the property of weak interconnections between the sub-networks. fundamentally, this is the same property which allows for: (1) robust decentralized staautomating operation of large electric power systems 111bilization; (2) aggregatio

57、n into sub-systems; and (3) their decentralized control without requiring system-wide top-down coordination. similarly, computer algorithms for decomposing the network into sub-networks for parallel computing are based on the same property; more recently, the ideas of amorphous computing have drawn

58、on the same property.2.2 implications of violating monotone responseas the electric power grids are operated away from the conditions for which they were initially designed, they may lose the properties of monotone networks. consequently, the layered-managed system may fail to meet its objectives. t

59、he variations in system conditions are generally caused by both significant variations in operating conditions and/or by the major equipment failures. there is no black-and-white line between the effects of these two, i.e., one cannot say that the system remains monotone for any changes in operating conditions as long as there is notopological ch