Model predictive control of indoor microclimate: existing building stock comfort improvement.
We analyze how model predictive control (MPC) applied to microclimate control in buildings that cannot be substantially modified, can provide energy-efficient solutions to the problem of occupants' comfort in a variety of situations principally imposed by external weather. For this purpose we define an objective function for the energy consumption, and we consider two illustrative cases: one building designed and built in recent times with modern HVAC equipment, and one designed and built several decades ago with poor thermal and ventilation characteristics. Our model includes various physical effects such as, e.g., air infiltration and indoor "inertia mass", and also accounts for the impact of human presence essentially as heat and CO$_2$ sources. Further, the influence of forecast horizons and that of uncertainties due to inaccuracies in the weather and room occupancy forecasts on the numerical results are analyzed. We solve the non-convex optimization problems using a linear and a nonlinear optimizer. Full MPC performance is compared to both linearized MPC and a standard on/off controller. The main advantage of MPC is its ability to provide satisfactory solutions for microclimate control at the least possible energy cost for both modern and old buildings. As old buildings are usually not properly ventilated, an inflow ventilation system installation is proposed as a quite advantageous solution for significant air quality improvement in light of our simulation results.
Publisher URL: http://arxiv.org/abs/1806.08999
DOI: arXiv:1806.08999v1
Keeping up-to-date with research can feel impossible, with papers being published faster than you'll ever be able to read them. That's where Researcher comes in: we're simplifying discovery and making important discussions happen. With over 19,000 sources, including peer-reviewed journals, preprints, blogs, universities, podcasts and Live events across 10 research areas, you'll never miss what's important to you. It's like social media, but better. Oh, and we should mention - it's free.
Researcher displays publicly available abstracts and doesn’t host any full article content. If the content is open access, we will direct clicks from the abstracts to the publisher website and display the PDF copy on our platform. Clicks to view the full text will be directed to the publisher website, where only users with subscriptions or access through their institution are able to view the full article.