Abstract
Timely decision making for least-cost maintenance of wind turbines is a critical factor in reducing the total cost of wind energy. The current models for the wind industry as well as other industries often involve solving computationally expensive algorithms such as dynamic programming. This article presents a tractable approximation of the dynamic decision-making process to alleviate the computational burden. Based upon an examination of decision rules in stationary weather conditions, a new set of decision rules is developed to incorporate dynamic weather changes. Since the decisions are made with a set of If–Then rules, the proposed approach is computationally efficient and easily integrated into the simulation framework. It can also benefit actual wind farm operations by providing implementable control. Numerical studies using field data mainly from the literature demonstrate that the proposed method provides practical guidelines for reducing operational costs as well as enhancing the marketability of wind energy. [Supplementary materials are available for this article. Go to the publisher's online edition of IIE Transactions for detailed proofs.]
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