Extreme low-power embedded systems are essential in Smart Cities and the Internet of Things, once these systems are responsible for acquiring, processing, and transmitting valuable environmental data. Some of these systems should run for a very long time without any human intervention, even for batteries replacement. Energy harvesting technologies allow embedded systems to be powered up from the environment by converting surrounding energy sources into electrical energy. However, energy-harvesting embedded systems (EHES) heavily depends on the nature of the energy sources, which are mostly uncontrollable and unpredictable. To improve the evaluation of energy management techniques in EHES, we propose the emulation of I-V curves of low-power energy harvesting transducers. An FPGA-based platform controls the energy source emulation combined with an integrated logic analyzer, which allows real-time data gathering from the EHES in multiple evaluation scenarios. The experiments show that the platform replicates solar energy scenarios with only 0.56% mean error.