This paper presents the results from the application of a biomimetic energy conserving/harvesting algorithm to the trajectory planning of a hypothetical fixed-wing sUAV in the 500 kg class, as it operates in a meso−γ sized wind-field. The mission comprises a complex, multi-directional, multi-elevation trajectory that simulates a realistic operation of a surveillance sUAV. The algorithm allows the energy due to atmospheric convection to be extracted to extend range and endurance. The algorithm utilizes two approaches to plan a trajectory through a wind field and selects the least cost path, minimizing the consumption of onboard energy. The approaches include a variant of the Potential Flow Method (PFM) and a variant of the Bellman-Ford method, called a Best Path Search (BPS). The energy consumption through the wind field is estimated using a finite difference scheme that utilizes advanced aircraft performance theory. The two approaches are compared to a baseline trajectory, which ignores the presence of the wind-field. The comparison yields the best path to fly. The PFM and BPS trajectories were further enhanced by allowing the algorithm to select the best airspeed to fly based on the wind field and aircraft characteristics, yielding five different trajectories to consider. Then, the resulting mission variants are flown using a 6-DOF the flight simulation, whose aerodynamic and inertial properties are inspired by an existing sUAV. It is shown that substantial improvement in fuel economy is to be expected in topography of strong mechanical convection.