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Video caching at the wireless edge is a promising approach to improve throughput and reliability of video delivery. While most existing literature considers homogeneous user preference modeling when designing caching policies, this paper investigates how to exploit statistical information on individual popularity preferences in the design of caching policies in base station assisted wireless device-to-device networks. Specifically, we formulate the caching policy design problem aiming to minimize average energy consumption and propose two approaches that solve the problem under different conditions: users can or cannot coordinatedly design their policies. By simulating systems using practical individual preference models, we show that the proposed designs are effective, and the performance gain brought by exploiting individual preferences can be clearly observed.