Multi-objective optimization of an unmoored wind energy system substructure

Abstract: 
While near-shore offshore wind further penetrates energy markets in the midst of the energy transition, a vast untapped resource lies in the deep offshore environment. A novel unmoored and autonomous wind energy concept which may harness the deep-offshore resource is discussed, particularly the optimization of the concept's trimaran substructure. A multi-objective optimization scheme, derived from Nondominated Sorting Genetic Algorithm (NSGA-II), is implemented to characterize the substructure's basic geometry, and the implications of various geometries on the competing (two) objectives: energy performance in the deep offshore environment and the structural steel mass required for construction.


Bio:

Aaron’s research considers fluid fuel energy storage coupled with floating offshore wind energy. Currently, his graduate research focuses on simulating and designing unmoored floating offshore wind energy platforms for deep offshore environment.

Born and raised in Hardwick, MA, Aaron developed a deep appreciation for a rural lifestyle, which the Amherst is ideal for. UMASS is also his undergraduate alma mater, and where he was first introduced to Wind Energy while studying wind turbine infrasound emissions of Massachusetts wind energy developments under Dr. James Manwell. In the fall of 2017, Aaron was pleased to continue wind energy study as a PhD student under Dr. Manwell and Dr. Matthew Lackner. When not in the Wind Energy Center, he enjoys writing music and backpacking in local mountain ranges.

 

Date: 
Thursday, November 18, 2021 - 4:00pm
Location: 
Virtually ZOOM
Year: 
2021
Semester: