This paper proposes a novel fast and accurate architectural-level tool to estimate power and energy (FAcET) for heterogeneous (CPU-GPU) system architecture based platforms. FAcET consists of two components. The first is a set of generic parametrizable power models generated by characterizing the functional-level activities for different blocks of the chosen platforms. The second is a simulation-based architectural-level prototype that uses SystemC (JIT) simulators to accurately evaluate the parameters of the corresponding power models of the first component. The combination of the two components leads to a novel power and energy estimation methodology at the architectural level that provides a better balance between speed and accuracy. The efficacy of the FAcET tool is verified against measurements taken on real board platforms, which consist of low-power ARM quad-core processors (Cortex-A7, -A9 and -A15), NVIDIA GPUs (Quadro 1000M, Quadro FX5600, Tegra K1, and GTX480) and heterogeneous platforms (NVIDIA Tegra3 and NVIDIA Jetson TK1). Power and energy estimation results obtained with FAcET deviate in less than 3.6% for quad-core processors, 6.5% for GPU, 10% for heterogeneous multiprocessor based systems from the measurements and estimation is 15x faster than state-of-the-art tools.