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Project: T152700 #0426
 

Efficient operation of a hydropower system requires the management and processing of large amounts of data. Statistical and data analysis techniques can be used to create a better understanding of information contained in data, and thus the physical system impacting a hydropower system and its operations. The focus of this report is to review the current practices for data analysis techniques, with specific emphasis on contemporary approaches relevant to hydropower systems.

The project started with a literature review of contemporary methods that focus on applications in the hydropower field. To help identify the current industry use of statistical methods and data analysis techniques, a series of interviews were conducted with hydropower owners and research groups. These interviews allowed perspectives into current industry-level needs for applied statistical techniques beyond simply theoretical approaches. As a result, this led to detailed descriptions of applicable statistical methods and an up-to-date reference list for more detailed information.

A large assortment of specific techniques is reviewed, providing the reader with a concise collection of important details on relevant techniques. Simple examples are provided to allow contextual placement in the field of hydropower, hydrology, and systems management. Finally, several important approaches are demonstrated in a series of thorough application examples, providing step-by-step explanations and details. There are a large variety of statistical tools and approaches available to assist in the management and operation of hydropower systems, often with no single best option. Advanced understanding of the range of tools, and how they can be applied, is the first step in fully utilizing information contained in data to assist in the decision making, analysis, and operations of hydropower systems.

Keywords:

Hydropower, Statistical methods, Optimization, Uncertainty, Climate Change, Ensembles,Diagnostics, Regression, Simulation Design, Stochastic Modeling