Smart Buildings in the Smart Grid: Contract-Based Design of an Integrated Energy Management System

In a supply-following “smart” grid scenario, buildings can exploit remotely controllable thermostats and “smart” meters to communicate with energy providers, trade energy in real-time and offer frequency regulation services, by leveraging the flexibility in the energy consumption of their heating, ventilation and air conditioning (HVAC) systems. The realization of such a scenario is, however, strongly dependent on our ability to radically re-think the way both the grid and the building control algorithms are designed. In this work, we regard the grid as an integrated, distributed, cyber-physical system, and propose a compositional framework for the deployment of an optimal supply-following strategy. We use the concept of assume-guarantee contracts to formalize the requirements of the grid and the building subsystem as well as their interface. At the building level, such formalization leads to the development of an optimal control mechanism to determine the HVAC energy flexibility while maximizing the monetary incentive for it. At the grid level, it allows formulating a model predictive control scheme to optimally control the ancillary service power flow from buildings, while integrating constraints such as ramping rates of ancillary service providers, maximum available ancillary power, and load forecast information. Simulation results illustrate the effectiveness of the proposed design methodology and the improvements brought by the proposed control strategy with respect to the state of the art.

[1]  Roberto Passerone,et al.  Multiple Viewpoint Contract-Based Specification and Design , 2008, FMCO.

[2]  Dejan Nickovic,et al.  Monitoring Temporal Properties of Continuous Signals , 2004, FORMATS/FTRTFT.

[3]  Frank D. Valencia,et al.  Formal Methods for Components and Objects , 2002, Lecture Notes in Computer Science.

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

[5]  Johanna L. Mathieu,et al.  Modeling and Control of Aggregated Heterogeneous Thermostatically Controlled Loads for Ancillary Services , 2011 .

[6]  Goran Strbac,et al.  Demand side management: Benefits and challenges ☆ , 2008 .

[7]  C. Woo,et al.  Now that California has AMI, what can the state do with it? , 2008 .

[8]  Xuening Sun,et al.  Methodology for the Design of Analog Integrated Interfaces Using Contracts , 2012, IEEE Sensors Journal.

[9]  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.

[10]  Thomas A. Henzinger,et al.  Interface automata , 2001, ESEC/FSE-9.

[11]  Alberto L. Sangiovanni-Vincentelli,et al.  A Contract-Based Methodology for Aircraft Electric Power System Design , 2014, IEEE Access.

[12]  Alberto L. Sangiovanni-Vincentelli,et al.  Library-based scalable refinement checking for contract-based design , 2014, 2014 Design, Automation & Test in Europe Conference & Exhibition (DATE).

[13]  Mehdi Maasoumy Haghighi,et al.  Controlling Energy-Efficient Buildings in the Context of Smart Grid: A Cyber Physical System Approach , 2013 .

[14]  Yassine Lakhnech,et al.  Formal Techniques, Modelling and Analysis of Timed and Fault-Tolerant Systems , 2004, Lecture Notes in Computer Science.

[15]  Alberto L. Sangiovanni-Vincentelli,et al.  Contract-based design of control protocols for safety-critical cyber-physical systems , 2014, 2014 Design, Automation & Test in Europe Conference & Exhibition (DATE).

[16]  Atif S. Debs,et al.  Modern power systems control and operation , 1988 .

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

[18]  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.

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

[20]  Alberto L. Sangiovanni-Vincentelli,et al.  Taming Dr. Frankenstein: Contract-Based Design for Cyber-Physical Systems , 2012, Eur. J. Control.

[21]  P. Kundur,et al.  Power system stability and control , 1994 .

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

[23]  Alberto L. Sangiovanni-Vincentelli,et al.  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 , 2014 .

[24]  B. J. Kirby,et al.  Spinning Reserve From Responsive Loads , 2003 .

[25]  Johan Löfberg,et al.  YALMIP : a toolbox for modeling and optimization in MATLAB , 2004 .

[26]  Alberto L. Sangiovanni-Vincentelli,et al.  Let's Get Physical: Computer Science Meets Systems , 2014, FPS@ETAPS.

[27]  B. Kirby,et al.  Providing Reliability Services through Demand Response: A Preliminary Evaluation of the Demand Response Capabilities of Alcoa Inc. , 2009 .

[28]  Arthur R. Bergen,et al.  Power Systems Analysis , 1986 .

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

[30]  Mehdi Maasoumy,et al.  Controlling Energy-Efficient Buildings in the Context of Smart Grid: A Cyber Physical System Approach , 2014 .

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

[32]  Amir Pnueli,et al.  The temporal logic of programs , 1977, 18th Annual Symposium on Foundations of Computer Science (sfcs 1977).

[33]  Alberto L. Sangiovanni-Vincentelli,et al.  Quo Vadis, SLD? Reasoning About the Trends and Challenges of System Level Design , 2007, Proceedings of the IEEE.

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