In spatial audio processing, Inter-aural Level Difference Distortions (ILDD) between reference and coded signals play an important role in the perception of quality degradation. In order to reduce costs, there are efforts to develop algorithms that automatically predict the perceptual quality of multichannel/spatial audio processing operations relative to the unimpaired original without requiring extensive listening tests. Correct modelling of perceived ILDD has a great influence in the prediction performance of automated measurements. We propose an energy aware model of ILDD perception that contemplates a dependency of energy content in different spectral regions of the involved signal. Model parameters are fitted to subjective results obtained from listening test data over a synthetically generated audio database with arbitrarily induced ILDD at different intensities, frequency regions and energy levels. Finally, we compare the performance of our proposed model over two extensive databases of real coded signals along with two state-of-the-art ILDD models.