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INFORMATION TO USERS This manuscript has been reproduced from the microfilm master. UMI films the text directly from the original or copy submitted. Thus, some thesis and dissertation copies are in typewriter face, while others may be from any type of computer printer. The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleedthrough, substandard margins, and improper alignment can adversely affect reproduction. In the unlikely event that the author did not send UMI a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion. Oversize materials (e.g., maps, drawings, charts) are reproduced by sectioning the original, beginning at the upper left-hand comer and continuing from left to right in equal sections with small overlaps. Photographs included in the original manuscript have been reproduced xerographically in this copy. Higher quality 6" x 9" black and white photographic prints are available for any photographs or illustrations appearing in this copy for an additional charge. Contact UMI directly to order. ProQuest Information and Learning 300 North Zeeb Road. Ann Arbor. Ml 48106-1346 USA 800-521-0600 Advances in distribution system reliability assessment by Nagaraj Balijepalli A dissertation submitted to the graduate faculty in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Major : Electrical Engineering (Electric Power) S. S. Venkata, Major Professor Venkataramana Ajjarapu Richard D. Christie James D. McCalley William Q. Meeker Iowa State University Ames, Iowa 2002 Copyright © Nagaraj Balijepalli, 2002. All rights reserved. UMI Number 3051448 UMT UMI Microform 3051448 Copyright 2002 by ProQuest Information and Learning Company. All rights reserved. This microform edition is protected against unauthorized copying under Title 17, United States Code. ProQuest Information and Learning Company 300 North Zeeb Road P.O. Box 1346 Ann Arbor, Ml 48106-1346 Graduate College Iowa State University This is to certify that the doctoral dissertation of Nagaraj Balijepalli has met the dissertation requirements of Iowa State University Signature was redacted for privacy. Major Professor Signature was redacted for privacy. the Major Department iii H<NW 4^4 Hik1^Tl4 RR ^cTRÏT: V&g ^^frS^TFRt ^KWdi4^ltld4i «H4IM<ci|IWH: I VRcT: f¥ qqr 5P7T r# wutitiT W ? f%% Wn^F9^ll Adi Sankara in Sivaanandalahari iv Table of Contents List of Figures ....... ***»**#*#*#**#**« List of Tables..— Acknowledgements. M»**#»######**»#*#**#*####*******#*##*****#****#*»**#******#*#*###»**#**####*####*******##*#*****» Abstract ..m..m......m..........< • XI 1. Introduction 1 1.1 Deregulation and the growing importance of distribution reliability 1 1.2 Quantitative measures of distribution system reliability 2 1.3 Review of previous work 3 1.4 Distribution system reliability during storm conditions 6 1.5 Research objective 7 1.6 Organization of the document 7 2. System Reliability Assessment: Practical Considerations for Monte Carlo Methods»9 2.1 System reliability indices 10 2.2 Simulation as a tool for analysis 11 2.3 Line segment failure and repair processes - Data analysis and modeling 12 2.4 Monte Carlo simulation for distribution system reliability 18 2.4.1 Convergence criteria (Confidence testing and time limit for simulation) 20 2.4.2 The simulation algorithm 20 2.4.3 Computational performance of Monte Carlo simulation 22 2.5 Probability histograms of the system indices 25 2.5.1 System Average Interruption Frequency Index (SAJFI) 25 2.5.2 Momentary Average Interruption-Event Frequency Index (MAIFIE) 26 2.5.3 Momentary Average Interruption Frequency Index (MAIFl) 27 2.5.4 Customer Average Interruption Frequency Index (CAIFI) 28 2.5.5 Average System Interruption Frequency Index (ASIFI) 29 V 2.5.6 System Average Interruption Duration Index (SAIDI) 29 2.5.7 Customer Average Interruption Duration Index (CAIDI) 30 2.5.8 Customer Total Average Interruption Duration Index (CTAIDI) 31 2.5.9 Average System Interruption Duration Index (ASIDl) 31 2.6 Probability plots of SAIDI and SAIFI indices 32 2.6.1 System SAJDI probability plots 32 2.6.2 System SAIFI probability plots 34 2.7 Sensitivity of SAIDI and SAIFI indices to failure and repair models 36 2.7.1 Sensitivity of reliability indices to failure models 36 2.7.2 Sensitivity of reliability indices to repair models 36 2.8 Analysis of SAIFI of individual feeders 37 2.9 Conclusions 41 3. Sensitivity Analysis of Distribution System Reliability Indices.................................... 42 3.1 Analysis of annual feeder indices 45 3.1. I Analysis of annual feeder indices 46 3.1.2 Analysis of feeder indices over two consecutive years 47 3.2 Analysis of system reliability indices 50 3.2.1 Analysis of annual system indices 53 3.2.2 Analysis of system indices over two consecutive years 54 3.2.3 Sensitivity to prevailing feeder reliability level. 56 3.3 Discussion 58 3.4 Conclusions 60 4. Lightning Storm Reliability Assessment for Distribution Systems 61 4.1 A brief review of how lightning flashes cause power outages 62 4.2 An introduction to lightning detection 63 4.3 Motivation for current research 64 4.4 Modeling lightning storm intensity and duration 68 4.4.1 The philosophy of parametric modeling. 69 4.4.2 An example of parametric modeling 70 vi 4.4.3 Bootstrap sampling for lightning storms. 72 4.5 Lightning storms and line flashover rate: The IEEE standard method 73 4.5.1 Direct flashover failure rate 73 4.5.2 Induced flashover rate 75 4.6 Monte Carlo simulation for lightning storm reliability 76 4.7 Application to a practical system 78 4.7.1 Lightning data analysis 79 4.7.2 Momentary and sustained outages 80 4.7.3 Simulation results... 81 4.8 Conclusions 85 5. Summary, Conclusions and Directions for Future Research........................................ 86 5.1 Summary and conclusions 86 5.2 Main contributions 88 5.3 Directions for future research 88 5.3.1 Impact of reliability standards on load point indices 88 5.3.2 Effect of Dispersed Storage and Generation (DSG) facilities on distribution reliability 89 5.3.3 Reliability of networked distribution systems. 89 5.3.4 Modeling of faults caused by wind storms 89 5.3.5 Analytical storm reliability assessment 89 5.3.6 Including storm-caused outages in vegetation maintenance scheduling 90 5.3.7 Integration of statistical distribution of reliability indices in system design 90 5.3.8 Statistical modeling of line segment outage rate 90 Appendix .............................................................................................................................. 91 Terminology and Definitions of Reliability Indices 91 Example 97 Reliability Assessment Using FMEA Method: 97 Historical Reliability Assessment Method ( Used in Monte Carlo Simulation) 100 References 104 vii List of Figures Figure 2.1 Cumulative fault count vs. Operating time 15 Figure 2.2 Time between failures 17 Figure 2.3 Interruption duration 17 Figure 2.4 System after preprocessing procedure 20 Figure 2.5 Monte Carlo simulation for reliability assessment 21 Figure 2.6 Computational performance of the Monte Carlo algorithm 23 Figure 2.7 Convergence properties of the simulation 24 Figure 2.8 Number of faults simulated for convergence 24 Figure 2.9 Probability histogram of SAIFI 26 Figure 2.10 Probability histogram of system MAIFIE 27 Figure 2.11 Probability histogram of MAIFI 28 Figure 2.12 Probability histogram of system CAIFI 28 Figure 2.13 Probability histogram of system ASIFI 29 Figure 2.14 SAIDI Probability histogram 30 Figure 2.15 Probability histogram of system CAIDI 30 Figure 2.16 Probability histogram of system CTAIDI 31 Figure 2.17 Probability histogram of system ASIDI 32 Figure 2.19 Probability plots of system SAIDI 33 Figure 2.20 Probability plots of system SAIFI 34 Figure 2.20 (Cont.) Probability plots of system SAIFI 35 Figure 2.21 Probability density function plots of SAIFI 36 Figure 2.22 Probability density function plots of SAIFI 37 Figure 2.23 Topology of Feeder F84A 38 Figure 2.24 SAIFI probability histogram for feeder F84A 39 Figure 2.25 SAIFI probability histogram for the redesigned feeder F84A 40 Figure 3.1 Probability plot of SAIDI for feeder F78B 45 Figure 3.2 Probability plot of SAIFI for feeder F78B 46 Figure 3.3 Probability plot of system SAIDI 51 viii Figure 3.4 Probability plot of system SAIFI 51 Figure 3.5 Relative standard deviation of SAIFI and SAIDI vs. system size 52 Figure 3.6 SO measure for SAIDI vs. system size 54 Figure 3.7 SO measure for SAIFI vs. system size 54 Figure 3.8 SI measure for SAIDI vs. system size 55 Figure 3.9 SI measure for SAIFI vs. system size 55 Figure 3.10 Relative standard deviation of SAIDI vs. failure rate 56 Figure 3.11 SO measure for SAIDI vs. failure rate 57 Figure 3.12 SO measure for SAIFI vs. failure rate 57 Figure 4.1 Lightning intensity distribution 71 Figure 4.2 Lightning storm duration distribution 71 Figure 4.3 Number of induced flashovers of overhead distribution lines vs. CFO 76 Figure 4.4 Storm reliability assessment module for distribution systems 78 Figure 4.5 Sustained outages and permanent faults vs Number of lightning flashes 81 Figure 4.6 MAIFI histogram 83 Figure 4.7 MAIFIE histogram 84 Figure 4.8 SAIFI histogram 84 Figure 4.9 SAIDI histogram 84 Figure Al. Example system for calculation of reliability indices 97 ix List of Tables Table l.l Comparative assessment of computational performance 23 Table 3.1 FO measure for feeder SAIDI and SAIFI 47 Table 3.2. The 10 worst performing feeders based on SAIDI 49 Table 3.3. The 10 worst performing feeders based on SAIFI 49 Table 3.4 SAIDI and SAIFI of different systems 52 Table 3.5 Storm types and their characteristics (66 months of data) 59 Table 4.1 Reliability indices due to lightning storms (2000 years of simulation) 83 Table 4.2 Mean and standard deviation (std) of reliability indices 83 Table AI.

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