Asset management is an important activity in present day distribution system planning and operation. Utilities are constantly striving to optimize the use of resources available for maintenance while ensuring system reliability is within satisfactory limits. This paper proposes a method to allocate maintenance resources to various distribution system assets. To determine the effects of maintenance, a predictive reliability assessment tool is developed. This paper describes the model on which this tool is based. The results obtained from reliability assessment can be used along with an optimizer to allocate resources to various maintenance tasks in a distribution system.

Section IV. Section V provides an illustration, and Section Abstract-This paper introduces a risk-based optimal VI concludes. strategy for distribution asset management preventive maintenance resource allocation. Three hierarchical decision III. RISK AND RISK-REDUCTION problems are addressed: total resource planning for maintenance, resource allocation to maintenance categories, The risk index for power system reliability is a measure and task selection within each category. The Lagrange of the system's exposure to failure. Consequently, the risk relaxation and dynamic programming methods are used to index accounts for both probability and severity of a power solve these three level problems efficiently. A test system is system contingency. For distribution systems, a provided that considers resource allocation for wood poles, contingency, e.g. an outage event, can be caused by the reclosers, and tree trimming.failure of one or several types of components, e.g., treecontact, pole failure, a protection failure. Such failures have Keywords: asset management, budget planning, dynamic undesirable consequences, and the failure probability in a programming, Lagrange relaxation, optimization, risk cesrtai e multipled by an qanicationto its certain time multiplied by a quantification of its consequence results in a measure of risk, i.e., I. NOMENCLATURE Risk(k) = Pr(k). Sev(k) (1) where k is the component number, and Pr(k) is the Budget: The total investment the organization will make to probability of the component to fail within the next budget perform preventive maintenance in a specified time period, cycle, typically one year. Sev(k) is the failure consequence typically one year.which captures the effect of failure on customer Program or category: A budgetary category within the asset satisfaction, loss of revenue, cost of repair or replacing a management group. Programs are typically identified by damaged device, and cost of regulatory penalty. A detailed equipment type. e.g., tree trimming, recloser maintenance, composite risk index due the multiple consequences is wood pole maintenance.given below, each term of which contains the probability Task or project: A maintenance activity that for purposes of part and severity part explicitly or implicitly.decision is not to be further divided into subtasks, for Customer satisfaction Lost revenue example the tree-trimming for a particular feeder section.

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This paper introduces a degradation-path model for utility wood pole asset management that facilitates estimation of failure probability and time to failure, indicators which are useful in maintenance decisions. This model requires degradation data, which for wood poles are measurements of the residual strength around the ground line. Non-destructive measurement methods of the residual strength are well developed and enable application of this model. The method is illustrated using actual measurement records.