Mccalley Final Report s14

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    PSERC

    Risk-Based Maintenance Allocation

    and Scheduling for Bulk

    Transmission System Equipment

    Final Project Report

    Power Systems Engineering Research Center

    A National Science Foundation

    Industry/University Cooperative Research Center

    since 1996

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    Power Systems Engineering Research Center

    Risk-Based Maintenance Allocation and

    Scheduling for Bulk Transmission System

    Equipment

    Final Project Report

    Project Team

    Jim McCalley (Project Leader)Tim Van Voorhis

    Yong JiangIowa State University

    A.P. MeliopoulosGeorgia Institute ofTechnology

    PSERC Publication 03-26

    October2003

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    Information about this project

    For information about this project contact:

    James D. McCalley, Ph.D.

    ProfessorIowa State UniversityDepartment of Electrical and Computer EngineeringAmes, Iowa 50011Tel: 515-294-4844Fax: 515-294-4263Email:jdm@iast a t e.e d u

    Power Systems Engineering Research Center

    This is a project report from the Power Systems Engineering Research Center (PSERC).PSERC is a multi-university Center conducting research on challenges facing arestructuring electric power industry and educating the next generation of powerengineers. More information about PSERC can be found at the Centers website:http://p s erc .or g.

    For additional information, contact:

    Power Systems Engineering Research CenterCornell University428 Phillips HallIthaca, New York 14853Phone: 607-255-5601Fax: 607-255-8871

    Notice Concerning Copyright Material

    PSERC members are given permission to copy without fee all or part of this publicationfor internal use if appropriate attribution is given to this document as the source material.This report is available for downloading from the PSERC website.

    2003 Iowa State University. All rights reserved.

    mailto:jdm@iastate.eduhttp://www.pserc.wisc.edu/http://www.pserc.wisc.edu/http://www.pserc.wisc.edu/mailto:jdm@iastate.edu
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    Acknowledgements

    The Power Systems Engineering Research Center sponsored this two-year researchproject titled Risk-Based Maintenance Allocation and Scheduling for Bulk TransmissionSystem Equipment. We express our appreciation for the support provided by PSERCs

    industrial members and by the National Science Foundation under grant NSF EEC-0002917 received under the Industry / University Cooperative Research Center program.

    One Ph.D student, Yong Jiang, was supported in this project. He will continue to extendthis work under funding from a second and closely-related PSERC project titledAutomated Integration of Condition Monitoring and Maintenance Scheduling for CircuitBreakers and Power Transformers.

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    ii

    Executive Summary

    In todays electricity business, it is more important than ever to cost effectively maintainreliability. In this project, we developed a method for efficiently allocating economicresources among maintenance activities for bulk transmission system equipment. Thus,

    the project addresses needs associated with asset management of transmission equipment.With this method, maintenance scheduling explicitly considers risks associated with suchnetwork security problems as overloads, low voltages, cascading overloads, and voltageinstability. The methods objective is to allocate economic resources to minimize risk ofwide-area bulk transmission system failures through the optimal choice of a maintenanceschedule.

    Selection and scheduling of maintenance tasks, subject to budget and labor constraints, isperformed today with various levels of rigor. In some cases, maintenance schedules arefixed schedules, augmented when needed to address significant equipment maintenanceconcerns. In other case, maintenance is scheduled by using ranking mechanisms thatscore equipment based on weighted sums of different attributes characterizing either thefailure likelihood or the failure consequence of each piece of equipment.

    The maintenance management approach developed in this project improves upon existing practices by making two significant and unique contributions by explicitly modelingoperational security risk reduction and by computing an optimal maintenance schedule.

    Operatio n al security r i sk

    Given that available economic and labor resources for maintenance are constrainedrelative to the maintenance needs, the decision to expend resources on maintaining onepiece of equipment over another is based on their relative failure likelihoods as well astheir relative failure consequences. We formalized this procedure using cumulative-over-

    time risk, where the consequence evaluation includes operational security consequences(in particular, overload, low voltage, voltage instability, and cascading overloads).

    Opti m izati o n

    Optimization methods for maintenance scheduling have not been used widely in theindustry because of the difficulty in properly quantifying risk and the challengesassociated with nonlinear integer programming. We solved both of these problems usinga novel combination of relaxed linear programming and dynamic programming thatmaximizes maintenance-induced cumulative risk reduction under budget, labor, andoutage-risk constraints. This approachs advantages relative to a ranking approach arethat it (1) obtains optimal solutions, (2) models attributes and constraints more rigorously,and (3) increases confidence in the choice of the preferred maintenance schedule becausedecision-makers can assess alternative options before making the final schedulingdecision. In addition, the optimization software can be used to optimize resourceallocation among budget categories such as type of equipment and/or regions.

    Research-grade Matlab and C-source code implement the risk assessment andoptimization methods. This software is available from the project team.

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    Table of Contents

    1. Introduction................................................................................................................. 11.1 Taxonomy of maintenance methods ....................................................................... 11.2 Risk-based maintenance and project objective ....................................................... 21.3 Overview of risk-based maintenance approach ...................................................... 31.4 Industry significance of new maintenance orientation ........................................... 41.5 Relation to industry state-of-the-art ........................................................................ 51.6 Contents of report ................................................................................................... 6

    2. Long Term Simulation ................................................................................................ 72.1 Computation of risk ................................................................................................ 82.2 Modeling of severity ............................................................................................... 92.3 System severity function....................................................................................... 10

    2.3.1 System severity function for low voltage ...................................................... 112.3.2 System severity function for voltage collapse............................................... 112.3.3 System severity function of overload ............................................................ 122.3.4 System severity function for cascading ......................................................... 13

    2.4 Component severity functions .............................................................................. 142.5 Speed enhancement............................................................................................... 16

    2.5.1 Avoiding redundant assessments for similar operating conditions ............... 162.5.2 Contingency screening .................................................................................. 17

    2.6 Summary ............................................................................................................... 183. Risk Reduction Calculation ...................................................................................... 19

    3.1 Maintenance-induced contingency probability reductions ................................... 193.1.1 Failure modes affected by maintenance activities......................................... 193.1.2 Reduction in failure mode probability by maintenance activities ................. 19

    3.2 Risk reduction calculation..................................................................................... 223.3 Risk reduction with simultaneous-maintenance activities .................................... 24

    3.4 Summary ............................................................................................................... 264. Maintenance Selection and Scheduling .................................................................... 27

    4.1 Problem statement................................................................................................. 274.2 Possible solution methods..................................................................................... 29

    4.2.1 Heuristic method ........................................................................................... 294.2.2 Branch and Bound ......................................................................................... 304.2.3 Relaxed li