Urban winds are a serious hazard for low-altitude autonomous aerial operations in urban airspaces. Previous methods for motion planning in urban winds require global knowledge of the obstacles and flow field and do not lend themselves to real-time application. In this paper, a planning and control framework is proposed for safe and energy-efficient navigation through urban flow fields that strictly relies on onboard sensing. The algorithm incorporates predictions of local wind flow fields into a receding horizon optimal controller, balancing energy consumption with obstacle avoidance on the fly to reach a goal destination. Simulation studies on a procedurally generated urban map with diverse wind conditions demonstrate that the energy-aware motion planner reduces energy consumption by as much as 30% and results in 32% fewer crashes on average compared to the wind-agnostic baseline. Comparisons to a global wind-aware planner indicate only minor trade-offs associated with planning on a local horizon.