Generating Availability Data System Research Articles

Resource adequacy risks to the bulk power system in North America

To keep the electric power system reliable, grid operators procure reserve generation capacity to protect against generator failures and significant deviation from the load forecast. Current methods for determining reserve requirements use historical generator availability data (recorded as failure events) to compute the fraction of the time each unit in the power system was unavailable unexpectedly. These values are then combined using analytical or simulation methods to yield a distribution of available capacity. From this distribution, the reserve capacity needed to maintain a particular reliability target may be determined. Such an approach implicitly assumes that generator failures occur independently of one another and that generator availability is not seasonal.To test these assumptions, we process the more than two million event records reported to the Generating Availability Data System (GADS) database maintained by the North American Electric Reliability Corporation (NERC) between January 1, 2012 and December 31, 2015. This allows us to construct complete availability histories (hourly time series) for each of the approximately 8000 generating units reporting to GADS during this period. Using these time series, we find strong evidence of correlated failures in most regions, even when removing Hurricane Sandy and the exceptionally cold month of January 2014 from the data. We find that correlated failures occur in all seasons. We do not find evidence of seasonality but note that seasonal structure may emerge with more data.In addition we determine the distribution of unscheduled unavailable capacity, unscheduled derating magnitudes, event durations, event arrival probabilities, and mean time between failure (MTBF) and mean time to recovery (MTTR) values. In each case, we report fit parameters to facilitate use by practitioners. The distributions of unscheduled unavailable capacity in each region are reasonably well modeled by Weibull and lognormal distributions. We find statistically significant differences in mean time between failure for small and large units for three unit types when aggregating over regions. Finally we present time series of unavailable capacity from unscheduled, maintenance, and scheduled events. These may be used in conjunction with load data to directly study resource adequacy risks without assuming independent failures or constant availability. Our findings suggest that power system resource planners should consider correlated outages as they identify reliability and reserve capacity requirements.

Research on Common-Mode and Dependent (CMD) Outage Events in Power Systems– A Review

The purpose of this paper is to present a review of some fundamental concepts and practical applications in the area of common-mode and dependent (CMD) outage events in power systems. The paper is a result of ongoing activity carried out by the Probability Applications for Common and dependent Mode Events (PACME) Working Group (WG) of the Reliability, Risk and Probability Applications Subcommittee. The PACME WG was formed in 2010 to review, advance, and present the research and practical applications in the area of CMD outage events. This paper presents state-of-the-art in research, modeling, and applications of CMD outage events in power system planning and operation. Issues considered include: data monitoring and collection, and probabilistic modeling and evaluation in the planning, and operation of power generation and transmission systems. Additionally, some results obtained from outage data statistics corresponding to CMD outage events in systems such as Generating Availability Data System, Transmission Availability Data System, and Canadian Electrical Association are presented.

The Availability Improvement Methodology (AIM) for Evaluating Power Plant Improvement Projects

The Availability Improvement Methodology (AIM) presented in this paper describes a method for calculating the increase in the power plant equivalent availability factor resulting from a proposed improvement project. AIM uses the recently developed IEEE definitions, along with other reliability parameters for establishing unit availability and performance. Additionally, AIM calculations are based primarily on data being collected for the Generating Availability Data System (GADS) of the National Electric Reliability Council. Many utilities are presently collecting equipment outage data on the GADS Performance and Event Report Forms. This data, if properly developed, is sufficient for performing AIM calculations.

Structuring Free Verbal Descriptions in Equipment Failure Reports

Information is encoded for convenience in computer sort/search routines used to manage a large number of records. The codes in use for equipment failure reports are limited due to practical considerations, and this limitation forces the reporter to leave out information to satisfy the coding requirements. The free form verbal descriptions, as found in the Generating Availability Data System (GADS) and the Nuclear Plant Reliability Data System (NPRDS), allow for reporting of this non-codable information. A systematic approach to constructing the verbal description based on rules of grammar, especially syntax, results in a structured narrative suitable for computer data management schemes. In addition, the reporter has a full range of descriptive terminology and does not have to select subjectively from a predetermined, limited vocabulary to describe the event. This paper introduces a concept that places in perspective the integration of structured, formal reporting and free form verbal description. A second benefit of this structured narrative is the systematic development of failure mode/failure cause relationships in the event.

A Power Plant Availability Improvement Methodology Based on the New NERC Generating Availability Data System (GADS)

Some utilities have begun reporting to NERC using the new GADS Reporting Manual. It is anticipated that most other reporting utilities will begin using the new system in 1982.

A Power Plant Availability Improvement Methodology Based on the New NERC Generating Availability Data System (GADS)

A Power Plant Availability Improvement Methodology Based on the New NERC Generating Availability Data System (GADS)