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Power intermittency and maintenance cost are the major challenges in harvesting wind energy. This paper proposes a multicriteria optimization model to design and operate a wind-based distributed generation (DG) system. The goal is to determine the equipment sizing, siting, and maintenance schedules so that the system cost is minimized while the turbine reliability is maximized. System cost comprises initial capital, operations, maintenance, downtime losses, and environmental penalty. The study makes an early attempt to incorporate the maintenance policy of generating units into the planning model. The moment method and the central limit theorem are used to characterize the power intermittency and the load uncertainty. A genetic algorithm is developed to search the nondominant solution set for the equipment siting, sizing, and maintenance intervals. The proposed model is demonstrated on the IEEE 37-node distribution network considering independent and correlated wind speed scenarios.