The robust optimization presented in this paper is formulated to assist in early-stage wind farm development. It can help wind farm developers predict project viability and can help landowners predict where turbines will be placed on their land. A wind farm layout is optimized under multiple sources of uncertainty. Landowner participation is represented with a novel uncertain model of willingness-to-accept monetary compensation. An uncertain wind shear parameter and economies-of-scale cost reduction parameter are also included. Probability Theory, Latin Hypercube Sampling, and Compromise Programming are used to form the robust design problem and minimize the two objectives: the normalized mean and standard deviation of Cost-of-Energy. The results suggest that some landowners that will only accept high levels of compensation are worth pursuing, while others are not.

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