Affiliation:
1. Renewable Energy Research Laboratory, Dept. of Mechanical and Industrial Engineering, University of Massachusetts, 160 Governors Dr., Amherst, MA 01003
Abstract
Offshore wind energy is positioned to facilitate substantial growth in wind energy production, but further reductions in the cost of energy will strengthen its ability to compete directly with other energy generating technologies. One simple solution is the optimal use of current technologies. To this end, this study investigates the use of optimization algorithms for offshore wind farm micrositing. First, a discussion is given of five different types of optimization algorithms: gradient search, heuristic, pattern search, simulated annealing, and evolutionary algorithms. The relevance of each algorithm to wind turbine micrositing is then evaluated by considering two separate objectives: minimization of the levelized production cost and maximization of the energy production. The genetic and greedy heuristic algorithms are further evaluated through the use of design simulations. Finally, these algorithms are employed to optimize the layout of a potential, real-world offshore wind farm near Hull, Massachusetts.
Subject
Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment
Cited by
71 articles.
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