Building Efficiency and Sustainability in the Tropics ( SinBerBEST ) Title Model Predictive Control Approach to Online Computation of Demand-Side Flexibility of Commercial Buildings HVAC Systems for Supply Following Permalink

Commercial buildings have inherent flexibility in how their HVAC systems consume electricity. We investigate how to take advantage of this flexibility. We first propose a means to define and quantify the flexibility of a commercial building. We then propose a contractual framework that could be used by the building operator and the utility to declare flexibility on the one side and reward structure on the other side. We then design a control mechanism for the building to decide its flexibility for the next contractual period to maximize the reward, given the contractual framework. Finally, we perform at-scale experiments to demonstrate the feasibility of the proposed algorithm.

[1]  Lorenz T. Biegler,et al.  On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming , 2006, Math. Program..

[2]  Mehdi Maasoumy.  Modeling and Optimal Control Algorithm Design for HVAC Systems in Energy Efficient Buildings , 2014 .

[3]  Pooya Soltantabar.  Annual Energy Outlook , 2015 .

[4]  Alberto L. Sangiovanni-Vincentelli,et al.  Model Predictive Control of regulation services from commercial buildings to the smart grid , 2014, 2014 American Control Conference.

[5]  David E. Culler,et al.  sMAP: a simple measurement and actuation profile for physical information , 2010, SenSys '10.

[6]  Alberto Sangiovanni-Vincentelli,et al.  Model-Based Hierarchical Optimal Control Design for HVAC Systems , 2014 .

[7]  M Morari,et al.  Energy efficient building climate control using Stochastic Model Predictive Control and weather predictions , 2010, Proceedings of the 2010 American Control Conference.

[8]  Alberto L. Sangiovanni-Vincentelli,et al.  Flexibility of Commercial Building HVAC Fan as Ancillary Service for Smart Grid , 2013, ArXiv.

[9]  Dimitri P. Bertsekas,et al.  Nonlinear Programming , 1997 .

[10]  J. Lofberg,et al.  YALMIP : a toolbox for modeling and optimization in MATLAB , 2004, 2004 IEEE International Conference on Robotics and Automation (IEEE Cat. No.04CH37508).

[11]  Alberto L. Sangiovanni-Vincentelli,et al.  Total and Peak Energy Consumption Minimization of Building HVAC Systems Using Model Predictive Control , 2012, IEEE Design & Test of Computers.

[12]  Sean P. Meyn,et al.  Ancillary service for the grid via control of commercial building HVAC systems , 2013, 2013 American Control Conference.

[13]  Philip Haves,et al.  Model predictive control for the operation of building cooling systems , 2010, Proceedings of the 2010 American Control Conference.