Contingency probabilities are essential in applying probabilistic methods to operations-based security assessment and related decision-making. There are two basic issues that need particular attention. One is lack of data. The other is dependence on environmental conditions. This paper describes design and implementation of a contingency probability estimator. Statistical methods employed in the estimator include maximum likelihood and linear regression. The work makes use of a limited amount of historical data together with corresponding weather and locational data, to provide contingency probabilities that appropriately reflect conditions and location of each circuit. The approach is illustrated using four years of outage data.

Contingency Probability Estimation Using Weather and Geographical Data for On-Line Security Assessment

This standard provides a methodology for the interpretation of electric generating unit performance data from various systems and to facilitate comparisons among different systems. It also standardizes terminology and indexes for reporting electric generating unit reliability, availability, and productivity performance measures. This standard is intended to aid the electric power industry in reporting and evaluating electric generating unit reliability, availability, and productivity while recognizing the power industry’s needs, including marketplace competition. Included are equations for equivalent demand forced outage rate (EFORd), newly identified outage states, discussion of commercial availability, energy weighted equations for group performance indexes, definitions of outside management control (OMC), pooling methodologies, and time-based calculations for group performance indexes.

Standard Definitions for Use in Reporting Electric Generating Unit Reliability, Availability, and Productivity

Preventing repeat victimization is an area of criminology that has shown particular promise in recent years. Based on the premise that persons once victimized are at higher risk than others for future victimization, British officials developed successful programs that focus crime prevention efforts on victims. Of all crimes, family violence may have the highest repeat rate, especially in the first weeks after an incident is reported to the police. Accordingly, New York City officials developed an intervention program to reduce repeat incidents of family abuse. Three field experiments conducted during the 1990s evaluated whether or not this program, targeted at public housing residents who reported family violence to the police, reduced the rate of subsequent victimization. The findings produced within each study were not consistent across the studies; rather, these three experiments, separately analyzed, produce varying results. Since the composition of the samples varied across studies, however, one possible explanation is that this program has different effects within different populations. This paper reports outcomes from a series of analyses of pooled data from these three studies to address the inconsistencies. The results indicate that the intervention brought about greater reporting of subsequent abuse both to authorities and to research interviewers. The results are invariant across the three studies, indicating that greater reporting of abuse is not idiosyncratic to one particular population, and are consistent across the nature and source of outcome measures. These findings suggest the need for careful monitoring by the advocates and agencies that operate these types of programs and among those designing and testing future programs.

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Preventing repeat incidents of family violence: analysis of data from three field experiments

Frequent forced outages of power transmission equipment can significantly affect the performance of industrial and commercial power systems and the processes they control. Historical transmission reliability data provides the ability to predict the performance of various transmission line configurations and assess the economic impact of forced outages on industrial and commercial power systems. The prediction methodologies are presented in IEEE Std, 493 (i.e., IEEE Gold Book). This paper presents a summary of the Canadian Electrical Association's Equipment Reliability Information System statistics on the forced outage performance characteristics of power transmission equipment (i.e., transformers, circuit breakers, cables, etc.) for Canadian utilities for the period 1988-1992. The paper reveals the structure of the database and presents relevant summary data (i.e., the frequency and duration of forced outages) necessary for the application of these reliability methodologies. A knowledge of the primary causes of the major equipment forced outages as to whether the outages are primarily due to the subcomponents of the major equipment or to its terminal equipment is essential for designing, operating and maintaining a reliable transmission system. This paper discusses and identifies for each major equipment the primary subcomponent (e.g., transformer windings) and the terminal equipment (e.g., auxiliary equipment) which dominated the forced outage statistics of the major equipment for the five year period.

Transmission equipment reliability data from Canadian Electrical Association

This paper motivates the importance of equipment failure rates in three decision problems central to the power engineering industry. Traditional methods of computing equipment failure rates are described, together with three new methods. Illustrations for each are provided

Computation of Contingency Probabilities for Electric Transmission Decision Problems

The purpose of this paper is to present and explain some fundamental concepts of pooling data to improve estimators of generating unit performance indices. These concepts were developed by a Task Force of the Application of Probability Methods Subcommittee of the Power System Engineering Committee. This paper delineates the two major reasons for pooling estimators: (1) to obtain improved estimators of unit performance when the units are homogeneous; and (2) to obtain good estimators of system performance when the system contains heterogeneous units. The paper recommends the correct method for pooling in both cases.

Pooling generating unit data for improved estimates of performance indices

The purpose of this paper is to present and explain some fundamental concepts of pooling data to improve estimators of generating unit performance indices. These concepts were developed by a Task Force of the Application of Probability Methods Subcommittee of the Power System Engineering Committee. This paper delineates the two major reasons for pooling estimators: 1. to obtain improved estimators of unit performance when the units are homogeneous, 2. to obtain good estimators of system performance when the system contains heterogeneous units. The paper recommends the correct method for pooling in both cases.

M. Mazumdar

Papers

Pooling generating unit data for improved estimates of performance indices

Pooling Generating Unit Data for Improved Estimates of Performance Indices The APM Task Force on Generator Data Pooling