This paper describes an energy-aware scheduling approach intended for use in heterogeneous multiprocessors supporting hardware acceleration with Dynamic and Partial Re-configuration. Scheduler decisions rely on pragmatic power and energy models to map the load across cores and reconfigurable regions with regards to the actual power costs. Results on a multithreaded H.264/AVC profile decoder with three possible hardware functions on a Xilinx Zynq based platform report energy gains up to 44.1% over full software execution and 49.6% over static hardware / software execution, while ensuring real-time decoding requirement.