How demand response from commercial buildings will provide the regulation needs of the grid

The statement “energy is not storable” is heard in energy conference lectures around the world, even though each person in the audience is sitting in a vast energy storage device. The heat storage in buildings is an enormous untapped resource for providing regulation services. This will be especially important as the grid is subject to more and more volatility from the introduction of power from renewable energy sources. This paper describes how regulation services can be obtained by exploiting the inherent flexibility of HVAC (Heating, Ventilation, Air Conditioning) systems in commercial buildings. A particular simulation test case is considered - A large commercial building at the University of Florida. The conclusions of this research demonstrate that, 1) A simplified model of the building that is adequate for control can be obtained from input-output measurements. In this study, the only control input considered is the supply fan power. 2) Control synthesis to regulate the building air temperature while simultaneously providing regulation to the grid can be cast as an LQR problem that admits a simple closed form solution. 3) Numerical experiments show that for this HVAC system, 15% of fan power capacity can be provided for regulation, while maintaining indoor temperature deviation to no more than ±0.2 °C. Based on these results, we conclude that the HVAC systems in 90, 000 medium-sized commercial buildings can provide the entire regulation service needed by PJM today, without any noticeable change in indoor air quality. The total regulation services that can be potentially provided by all the commercial buildings in the U.S. that have the necessary equipment in place are much higher. Our results indicate that supply fans in existing commercial buildings can provide about 70% of the current regulation capacity needed in the United States.

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

[2]  Ian A. Hiskens,et al.  Achieving Controllability of Electric Loads , 2011, Proceedings of the IEEE.

[3]  M. Piette,et al.  Peak Demand Reduction from Pre-Cooling with Zone Temperature Reset in an Office Building , 2004 .

[4]  Sila Kiliccote,et al.  Advanced Controls and Communications for Demand Response and Energy Efficiency in Commercial Buildings , 2006 .

[5]  B. Kirby,et al.  Frequency Regulation Basics and Trends , 2005 .

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

[7]  Sandia Report,et al.  Energy Storage for the Electricity Grid: Benefits and Market Potential Assessment Guide A Study for the DOE Energy Storage Systems Program , 2010 .

[8]  Donald E. Kirk,et al.  Optimal control theory : an introduction , 1970 .

[9]  Scott Backhaus,et al.  Modeling and control of thermostatically controlled loads , 2011 .

[10]  Johanna L. Mathieu,et al.  State Estimation and Control of Heterogeneous Thermostatically Controlled Loads for Load Following , 2012, 2012 45th Hawaii International Conference on System Sciences.

[11]  James E. Braun,et al.  Application of building precooling to reduce peak cooling requirements , 1997 .

[12]  R. Walawalkar,et al.  Evolution and current status of demand response (DR) in electricity markets: Insights from PJM and NYISO , 2010 .

[13]  Francesco Borrelli,et al.  Predictive Control for Energy Efficient Buildings with Thermal Storage: Modeling, Stimulation, and Experiments , 2012, IEEE Control Systems.

[14]  Sila Kiliccote,et al.  Strategies for Demand Response in Commercial Buildings , 2006 .

[15]  James E. Braun,et al.  Reducing energy costs and peak electrical demand through optimal control of building thermal storage , 1990 .