  With more than 32% of the global energy used by commercial and residential
buildings, there is an urgent need to revisit traditional approaches to
Building Energy Management (BEM). With HVAC systems accounting for about 40% of
the total energy cost in the commercial sector, we propose a low-complexity
DRL-based model with multi-input multi-output architecture for the HVAC energy
optimization of open-plan offices, which uses only a handful of controllable
and accessible factors. The efficacy of our solution is evaluated through
extensive analysis of the overall energy consumption and thermal comfort levels
compared to a baseline system based on the existing HVAC schedule in a real
building. This comparison shows that our method achieves 37% savings in energy
consumption with minimum violation (<1%) of the desired temperature range
during work hours. It takes only a total of 40 minutes for 5 epochs (about 7.75
minutes per epoch) to train a network with superior performance and covering
diverse conditions for its low-complexity architecture; therefore, it easily
adapts to changes in the building setups, weather conditions, occupancy rate,
etc. Moreover, by enforcing smoothness on the control strategy, we suppress the
frequent and unpleasant on/off transitions on HVAC units to avoid occupant
discomfort and potential damage to the system. The generalizability of our
model is verified by applying it to different building models and under various
weather conditions.
