An Examination of Fuel Consumption Trends in Construction Projects
Environmental Science and Technology
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Environmental Science and Technology
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Operators interested in improving reliability should begin with a focus on the performance of the wind plant as a whole. To then understand the factors which drive individual turbine performance, which together comprise the plant performance, it is necessary to track a number of key indicators. Analysis of these key indicators can reveal the type, frequency, and cause of failures and will also identify their contributions to overall plant performance. The ideal approach to using data to drive good decisions includes first determining which critical decisions can be based on data. When those required decisions are understood, then the analysis required to inform those decisions can be identified, and finally the data to be collected in support of those analyses can be determined. Once equipped with high-quality data and analysis capabilities, the key steps to data-based decision making for reliability improvements are to isolate possible improvements, select the improvements with largest return on investment (ROI), implement the selected improvements, and finally to track their impact.
This report addresses the general data requirements for reliability analysis of fielded wind turbines and other wind plant equipment. The report provides a list of the data needed to support reliability and availability analysis, and gives specific recommendations for a Computerized Maintenance Management System (CMMS) to support automated analysis. This data collection recommendations report was written by Sandia National Laboratories to address the general data requirements for reliability analysis of fielded wind turbines. This report is intended to help the reader develop a basic understanding of what data are needed from a Computerized Maintenance Management System (CMMS) and other data systems, for reliability analysis. The report provides: (1) a list of the data needed to support reliability and availability analysis; and (2) specific recommendations for a CMMS to support automated analysis. Though written for reliability analysis of wind turbines, much of the information is applicable to a wider variety of equipment and a wider variety of analysis and reporting needs.
Abstract not provided.
This report documents the status of the Sandia National Laboratories' Wind Plant Reliability Database. Included in this report are updates on the form and contents of the Database, which stems from a fivestep process of data partnerships, data definition and transfer, data formatting and normalization, analysis, and reporting. Selected observations are also reported.
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JSM 2007 Proceedings
Abstract not provided.