%0 Conference Paper %B 2010 ACEEE Summer Study on Energy Efficiency in Buildings %D 2010 %T Development and Testing of Model Predictive Control for a Campus Chilled Water Plant with Thermal Storage %A Brian E. Coffey %A Philip Haves %A Michael Wetter %A Brandon Hencey %A Francesco Borrelli %A Yudong Ma %A Sorin Bengea %X

A Model Predictive Control (MPC) implementation was developed for a university campus chilled water plant. The plant includes three water-cooled chillers and a two million gallon chilled water storage tank. The tank is charged during the night to minimize on-peak electricity consumption and take advantage of the lower ambient wet bulb temperature. A detailed model of the chilled water plant and simplified models of the campus buildings were developed using the equation-based modeling language Modelica. Steady state models of the chillers, cooling towers and pumps were developed, based on manufacturers' performance data, and calibrated using measured data collected and archived by the control system. A dynamic model of the chilled water storage tank was also developed and calibrated. A semi-empirical model was developed to predict the temperature and flow rate of the chilled water returning to the plant from the buildings. These models were then combined and simplified for use in a MPC algorithm that determines the optimal chiller start and stop times and set-points for the condenser water temperature and the chilled water supply temperature. The paper describes the development and testing of the MPC implementation and discusses lessons learned and next steps in further research.

%B 2010 ACEEE Summer Study on Energy Efficiency in Buildings %I Omnipress %C Asilomar, California, USA %G eng %0 Conference Proceedings %B American Control Conference %D 2010 %T Model Predictive Control of Thermal Energy Storage in Building Cooling Systems %A Yudong Ma %A Francesco Borrelli %A Brandon Hencey %A Brian E. Coffey %A Sorin Bengea %A Philip Haves %X A model-based predictive control (MPC) is designed for optimal thermal energy storage in building cooling systems. We focus on buildings equipped with a water tank used for actively storing cold water produced by a series of chillers. Typically the chillers are operated at night to recharge the storage tank in order to meet the building demands on the following day. In this paper, we build on our previous work, improve the building load model, and present experimental results. The experiments show that MPC can achieve reductionin the central plant electricity cost and improvement of its efficiency. %B American Control Conference %C Baltimore, Maryland, USA %8 06/2010 %G eng %0 Journal Article %J Building Research and Information %D 2009 %T Towards a Very Low Energy Building Stock: Modeling the US Commercial Building Stock to Support Policy and Innovation Planning %A Brian E. Coffey %A Sam Borgeson %A Stephen E. Selkowitz %A Joshua S. Apte %A Paul A. Mathew %A Philip Haves %X

This paper describes the origin, structure and continuing development of a model of time varying energy consumption in the US commercial building stock. The model is based on a flexible structure that disaggregates the stock into various categories (e.g. by building type, climate, vintage and life-cycle stage) and assigns attributes to each of these (e.g. floor area and energy use intensity by fuel type and end use), based on historical data and user-defined scenarios for future projections. In addition to supporting the interactive exploration of building stock dynamics, the model has been used to study the likely outcomes of specific policy and innovation scenarios targeting very low future energy consumption in the building stock. Model use has highlighted the scale of the challenge of meeting targets stated by various government and professional bodies, and the importance of considering both new construction and existing buildings.

%B Building Research and Information %V 37:5 %G eng %& 610 %0 Conference Proceedings %B ACEEE Summer Study on Energy Efficiency in Buildings %D 2008 %T Benchmarking and Equipment and Controls Assessment for a ‘Big Box’ Retail Chain %A Philip Haves %A Brian E. Coffey %A Scott Williams %X

The paper describes work to enable improved energy performance of existing and new retail stores belonging to a national chain and thereby also identify measures and tools that would improve the performance of ‘big box' stores generally. A detailed energy simulation model of a standard store design was developed and used to:

The core enabling task of the project was to develop an energy model of the current standard design using the EnergyPlus simulation program. For the purpose of verification of the model against actual utility bills, the model was reconfigured to represent twelve existing stores (seven relatively new stores and five older stores) in different US climates and simulations were performed using weather data obtained from the National Weather Service. The results of this exercise, which showed generally good agreement between predicted and measured total energy use, suggest that dynamic benchmarking based on energy simulation would be an effective tool for identifying operational problems that affect whole building energy use. The models of the seven newer stores were then configured with manufacturers' performance data for the equipment specified in the current design and used to assess the energy and cost benefits of increasing the efficiency of selected HVAC, lighting and envelope components. The greatest potential for cost-effective energy savings appears to be a substantial increase in the efficiency of the blowers in the roof top units and improvements in the efficiency of the lighting. The energy benefits of economizers on the roof-top units were analyzed and found to be very sensitive to the operation of the exhaust fans used to control building pressurization.

%B ACEEE Summer Study on Energy Efficiency in Buildings %C Asilomar, California, USA %8 2008 %G eng