Python for Wind Energy

Date and Time: 
2015 April 13 @ 2:00pm
FL2-1022 Large Auditorium
Katherine Dykes

Authors: Katherine Dykes, Peter Graf, Rick Damiani, George Scott, Andrew Ning, Yi Guo, Taylor Parsons, Ryan King, and Paul Veers

This paper introduces the development of a new software capability for research, design, and development of wind energy systems which is meant to 1) represent a full wind plant including all components, turbines, and balance of system up to the grid interconnection point, 2) allow use of interchangeable models of varying fidelity for different aspects of the system, and 3) support analyses ranging from sensitivity studies and parameter scans to optimization and uncertainty quantification. This paper describes the design of the overall Wind-Plant Integrated Systems Engineering and Design (WISDEM) model that is built on the Python-based software Open Multidisciplinary Design Analysis and Optimization (OpenMDAO) and illustrates the use of the software for analysis of wind plant performance and cost. Analysis is performed for an offshore wind project based on the NREL 5 MW reference turbine aero-elastic model at a specific mid-Atlantic location. The ability to perform uncertainty analyses and MDAO is demonstrated for several cases of interest for wind turbine and plant design.


Speaker Description: 

The NREL NWTC wind energy systems engineering initiative has developed a Python-based analysis platform to leverage its research capabilities toward integrating wind energy engineering and cost models across wind plants. This Wind-Plant Integrated System Design & Engineering Model (WISDEMâ„¢) platform captures the important interactions between various subsystems to achieve a better understanding of how to improve system-level performance and achieve system-level cost reductions. This work illustrates a few case studies with WISDEM that focus on the design and analysis of wind turbines and plants at different system levels.

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