GPP Version 6 User's Guide: A General-Purpose Postprocessor for Wind Turbine Data Analysis

GPP (pronounced "jeep") is a general-purpose postprocessor for wind turbine data analysis. The original author, Marshall Buhl, a member of the National Wind Technology Center (NWTC) of the National Renewable Energy Laboratory (NREL), developed GPP to postprocess test data and simulation predictions. Norman Weaver of InterWeaver Consulting is responsible for coding most of the recent additions to Version 6. GPP reads data into large arrays and allows the user to run many types of analyses on the data stored in memory. It runs on inexpensive computers common in the wind industry. One can even use it on a laptop in the field. We wrote the program in such a way as to make it easy to add new types of analyses and to port it to many types of computers. Although GPP is very powerful and feature rich, it is still very easy to learn and easy to use. Exhaustive error trapping prevents one from losing valuable work caused by input errors. We believe that GPP can make a significant impact on engineering productivity in the wind industry.