Building-to-building energy trading under the influence of occupant comfort

Peer-to-peer energy trading is becoming an efficient methodology for trading flexibility between buildings due to the increasing utilisation of small-scale generation and storage technologies. In the buildings, however, this trading mechanism could be affected by occupant comfort and uncertainty around it, affecting the building operation and consumption. This study introduces a multi-level peer-to-peer energy trading framework for residential buildings under the influence of occupants preferences. The proposed method considers the effect of occupants comfort as an important factor on the control and energy management of buildings in local markets. The robustness of the proposed real-time control framework in face of uncertainty in a real-life building parameter (i.e. occupants comfort level) is improved through the-state-of-the-art information gap decision theory technique. This method requires very little information about uncertain parameters, making it a suitable technique for dealing with the uncertainty in parameters with unknown patterns. Finally, the operational models of energy storage and electric vehicles are adopted for full utilisation of available photovoltaic generation. The simulation results show that participating in the local energy trading can increase the robustness of the control systems in the residential microgrids in face of uncertainty in the occupant comfort level. Also, results show that 0.1% increase in the uncertainty radius of occupants comfort level requires a 6% increase in the energy bill. This shows the importance of considering the occupant comfort in the conventional building energy management strategies, and uncertainty around it on the energy bill.