Simulation and validation of indoor temperatures and relative humidity in multi-zone buildings under occupancy conditions using multi-objective calibration

Buildings are expected to be energy efficient but also to provide a comfortable environment to their occupants as well as to be durable. Indoor relative humidity influences the energy consumption, structure and the occupants' comfort and health. Therefore, it is necessary to control and predict indoor environmental conditions. This work aims to simulate indoor temperatures and relative humidity in a multi-zone building model under realistic conditions, such as occupancy and moisture gains, operation of windows and doors and mechanical ventilation. The combined multi-zone air flow model is developed with TRNSYS and TRNFLOW and it is applied to a phase of the Twin Houses extended experiment of the international energy agency, energy in buildings and communities (IEA EBC) Annex 71. The main novelty of this work is to determine the masses of surface and deep moisture buffer storage by performing a multi-objective calibration of indoor temperatures and relative humidity. Results prove that building energy simulations need to model the moisture buffering of internal materials to accurately predict indoor humidity. The error in simulating relative humidity is reduced by 69% in the house with moisture gains after calibration of the masses of buffering materials. Moreover, the calibrated multi-zone building model shows a great agreement between simulated and measured data with an average root mean square error (RMSE) among thermal zones of 0.51 degrees C and 0.48 degrees C in indoor temperatures and 3.58% and 2.21% in relative humidity for the two houses in the validation period.

Automated summary

Buildings are expected to be energy efficient, comfortable, and durable, which are influenced by indoor relative humidity. Controlling and predicting indoor environmental conditions is necessary. Simulating indoor temperature and relative humidity in a multi-zone building model can improve accuracy of building energy simulations and ensure occupants' comfort and health.