Multisource energy harvesters are a promising, robust alternative to power the future Internet of Nano Things (IoNT), since the network elements can maintain their operation regardless of the fact that one of its energy sources might be temporarily unavailable. Interestingly, and less explored, when the energy availability of the energy sources present large temporal variations, combining multiple energy sources reduce the overall sparsity. As a result, the performance of a multiple energy harvester powered device is significantly better compared to a single energy source even if they harvest the same amount of energy. In this context, a framework to model and characterize the area for multiple source energy harvesting (EH) powered systems is proposed. This framework takes advantage of this improvement in performance to provide the optimal amount of energy harvesters, the requirements of each energy harvester, and the required energy buffer capacity, such that the overall area or volume is minimized. On top of these results, self-tunable energy harvesters are explored as a solution and compared to multisource EH platforms. As the results show, by conducting a joint design of the energy harvesters and the energy buffer, the overall area or volume of an EH powered device can be significantly reduced.