This paper presents a general approach to compute energy optimal flight paths for unmanned aerial vehicle (UAV) in urban environments. To minimize the energy required, the flight path is optimized by exploiting local wind phenomena, i.e.,
upwind and tailwind areas from the airflow around buildings. A realistic wind field of a model urban environment typical for continental Europe is generated using PALM, a Large Eddy Simulation tool. The calculated wind field feeds into the flight path planning algorithm to minimize the energy required. A specifically tailored A-Star-Algorithm is used to optimize flight trajectories. The approach is demonstrated on a delivery UAV benchmark scenario. Energy optimal flight paths are compared to shortest way trajectories for 12 different scenarios. It is shown that energy can be saved significantly while flying in a city using knowledge of the current wind field.