Data Mining

Data mining requires more than just access to the web or commercial data vendors.  Understanding this data, it's application and validity are critical to analysis.  With 35 years experience in the actual operation of power systems and the application of this information, Mr. Johnson understand this information and can evaluate it's accuracy and usefulness. 

§         Is the information reasonable?

§         What is reasonable?

§         How does this compare to other plants?

§                     Do the various pieces of information produce consistent results?

It is possible to cross validate information with sufficient knowledge of operations, economic relationships, system operations and the natural pattern of power consumption and production.  Using actual experience and knowledge allows for the validation of this information.

 

One example is how we can relate fundamental unit information to observed unit historical operations.  We can do this by the following connection of information:

 

§                     Known fuel price information and estimated heat rate imply a dispatch cost,

§                     Given that dispatch cost assumption, how would the unit stack up economically to other units,

§                     Given that stacking, what capacity factor would be implied,

§                     How does this capacity factor compare to reported information on cost, and energy production.

This is one of many ways that data can be validated.  Our practice has many such approaches developed over 35 years experience in the industry and working with over 50 different power producing entities.

 

 

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