Optimization of Ground Station Energy Saving in LEO Satellite Constellations for Earth Observation Applications

Orbital Edge Computing (OEC) capability on board satellites in Earth Observation (EO) constellations would surely enable a more effective usage of bandwidth, since the possibility to process images on board enables extracting and sending only useful information to the ground. However, OEC can also help to reduce the amount of energy required to process EO data on Earth. In fact, even though energy is a valuable resource on satellites, the on-board energy is pre-allocated due to the presence of solar panels and batteries and it is always generated and available, regardless of its actual need and use in time. Instead, energy consumption on the ground is strictly dependent on the demand, and it increases with the increase in EO data to be processed by ground stations. In this work, we first define and solve an optimization problem to jointly allocate resources and place processing within a constellation-wide network to leverage in-orbit processing as much as possible. This aims to reduce the amount of data to be processed on the ground, and thus, to maximize the energy saving in ground stations. Given the NP hardness of the proposed optimization problem, we also propose the Ground Station Energy-Saving Heuristic (GSESH) algorithm to evaluate the energy saving we would obtain in ground stations in a real orbital scenario. After validating the GSESH algorithm by means of a comparison with the results of the optimal solution, we have compared it to a benchmark algorithm in a typical scenario and we have verified that the GSESH algorithm allows for energy saving in the ground station up to 40% higher than the one achieved with the benchmark solution.