Solar power satellites

During energy crisis at the end of the Sixties, a new idea to exploit solar energy arose: Solar Power Satellites. These satellites need a huge surface to collect enough solar energy to be beamed on Earth by means of a microwave power transfer system. Different concepts appeared during last forty years and a lot of studies addressing the SPS economical feasibility have been published. In this work a particular concept is considered, the JAXA Reference Concept 2003. It is a formation flying SPS, composed by two reflectors and a central array panel. The objective of the work is to study two major problems this concept presents. Due to its dimensions, the satellite orbit will suffer from important orbital perturbations and since formation flying satellites need a tight orbit control, the first task is to derive an analytical approximation to perform relative perturbed orbit propagation for formation flying satellite. This objective is pursued starting from a H. Schaub’s formulation in which formation flying satellites unperturbed orbit is described by means of an approximated relation function of orbital element differences. This formulation is merged with another approach, developed in a previous work, which gives, analytically, orbital parameters variation when a perturbation acts on the spacecraft. The result is a very interesting algorithm, able to perform the assigned task with a relative error lower than 3% over one simulated orbit. The second objective concerns structural control. It is not possible to consider these huge satellites as rigid bodies, first natural frequencies will be certainly excited during operations. So that, the second task is the study of actuator placement optimization for flexible satellites, very useful for tight pointing requirements. A FEM model is developed modeling the SPS as a frame of beams and a global controllability index � is obtained combining modal controllability and component cost analysis. The maximization of this parameter, that depends on actuators location, maximizes the system controllability, thus it is used as cost function. Skelton’s algorithm (SKE), reference point in the literature, is compared with three stochastic optimizers (GA, DE and PSO). Even if SKE gives exactly the optimal configuration it is really slow. Stochastic optimizers are all definitely faster than it. On the other hand their performance in terms of success rate ranges from 25% (GA) to over 60% (PSO). There is no certainty to find the optimum with a stochastic algorithm but in case of very detailed system models SKE–like algorithms may become unfaisible. To have a flexible instrument able to compute, with high success rate, optimal actuators configuration is a major achievement since it coniugates the possibility to perform a great number of analysis in a short time with the capability to deal with detailed models.