This paper presents an approach to planning long distance autonomous soaring trajectories for small uninhabited aerial vehicles harvesting energy from the atmosphere. An A* algorithm is used with a cost function which is the weighted sum of energy required and distance to goal. The effect of varying the weight parameter on the ight paths is explored. The required initial energy for varying weight is examined, and the results are compared with a wavefront expansion planning algorithm. The weight is selected based on maximum energy utilization that is available from the atmosphere and minimizing time to reach the goal. Optimal weight is selected based on simulation results and the performance of A* is studied for a realistic wind field. Optimal energy efficient routes are predicted from a given wind field data.