model-based control, multi-level control, peak demand reduction, grey-box modeling
This paper presents a multi-level approach to the problem of modelling different thermal zones in a house for control applications. This problem has been treated before by modelling the whole house with a single, all-inclusive RC circuit which may have different levels of resolution. The core of the proposed methodology lies in the possibility of allowing the user to switch back and forth between models representing different control levels according to the modelling objectives. For the development of specific control algorithms for each zone, the house can be treated as a collection of interconnected zonal models, as opposed to a single, large model. This modelling approach has the advantage of maintaining a simple structure for each zone, while also taking into account the heat transfer between zones; at this control level, issues such as occupancy, thermal comfort or setpoint profiles can be examined in detail. On the other hand, if the user is interested in a quick estimate of global variables (e.g., overall thermal load over the next 24 h) then different zones or even the entire house may be combined into a single low-order model. In summary, this multi-level approach allows the user to â€œzoom in and outâ€ so that models at each control level remain manageable, easy to calibrate and easy to physically interpret. This paper uses data from an existing unoccupied test house, representative of a typical family home in QuÃ©bec, as a case study. Four zones are considered: basement, main floor, upper floor and the attached garage. For the most detailed analysis, these zones are modelled with four interconnected zone models. Alternative ways of combining zones are investigated. A global low-order house model is used to calculate the thermal load of the building. Results of thermal load calculations are compared and discussed.