The primary purpose of heating, ventilating, and air-conditioning systems is to provide acceptable indoor air quality and thermal comfort. Hybrid or mixed-mode ventilation systems provide good indoor air quality and thermal climate using natural ventilation whenever the outdoor weather conditions are favorable, but revert to mechanical systems for HVAC whenever external conditions are too harsh. A hybrid building should switch between these two modes of operation according to seasonal, and diurnal variations in the indoor thermal conditions and the outdoor environment. Such a hybrid building requires an intelligent control system that can switch automatically between natural and mechanical modes in such a way that minimizes energy consumption without compromising indoor air quality or the thermal comfort of its occupants. 

Occupant comfort votes depend on their expectations (i.e., their understanding of the building concept) and on their heat balance (depending on their physiology and the physics of the indoor environment). From a scientific point of view, we will investigate when people in a mixed-mode building feel comfortable with the adaptive comfort model (valid for buildings with high occupant influence on the indoor environment) and when they feel comfortable with a comfort model based on the heat balance according to EN ISO 7730 (or ANSI/ASHRAE Std 55-2004), or whether there is an amalgam of the two which applies in such buildings. 

As the project objectives, we will develop a control algorithm for mixed-mode buildings, which:

1. •minimizes site energy consumption by means of an optimal ventilation and HVAC strategy using both low-exergy energy sources such as groundwater, ground, or cool night air as well as mechanical cooling
   

2. •potentially reduces investment costs by downsizing installed HVAC system capacities
   

3. •improves occupant acceptance/thermal comfort
   

4. •reduces sick building syndrom (AC mode only) as well as heat stress and uncomfortable room temperatures (natural ventilation mode only)
   

We will focus on offices; yet, the control algorithms may also apply to residential mixed-mode buildings. 

project team

The project team consists of a multi-national consortium of building energy experts, including:

1. •Gregor Henze, Ph.D., P.E., University of Colorado at Boulder, PI
   

2. •Peter May-Ostendorp, University of Colorado at Boulder, Research Assistant
   

3. •Clemens Felsmann, Ph.D., Technische Universität Dresden, co-PI
   

4. •Jens Pfafferott, Ph.D., Fraunhofer Institute Solar Energy Systems, co-PI
   

5. •J. Fergus Nicol, London Metropolitan University
   

6. •Richard de Dear, Ph.D., Macquarie University
   

The team also plans extensive collaboration with Gail Brager, Ph.D. of UC Berkeley's Center for the Built Environment as well as Philip Haves, Ph.D. of Lawrence-Berkeley National Laboratory.

project milestones

Phase 1: Modeling (2009 - 2010)

1. •Review of mixed-mode building experience
   

2. •Modeling of prototypical mixed-mode building
   

3. •Development of optimization interface
   

4. •Definition of optimization cases
   

5. •Optimization study
   

Phase 2: Experimentation (2010 - 2011)

1. •Selection of suitable demonstration building
   

2. •Holistic building performance rubric
   

3. •Pre-application baseline occupant survey
   

4. •Implementation of near-optimal control strategy
   

5. •Post-application occupant survey and energy impact evaluation
   

6. •Final technical report