02003nas a2200193 4500008004100000022001800041245011000059210006900169260004100238520131100279100002201590700001801612700002001630700002001650700002401670700001501694700001801709856008201727 2010 eng d a0-918249-60-000aDevelopment and Testing of Model Predictive Control for a Campus Chilled Water Plant with Thermal Storage0 aDevelopment and Testing of Model Predictive Control for a Campus aAsilomar, California, USAbOmnipress3 a

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.

1 aCoffey, Brian, E.1 aHaves, Philip1 aWetter, Michael1 aHencey, Brandon1 aBorrelli, Francesco1 aMa, Yudong1 aBengea, Sorin uhttps://simulationresearch.lbl.gov/publications/development-and-testing-model01213nas a2200169 4500008004100000245008300041210006900124260003800193520061000231100001500841700002400856700002000880700002200900700001800922700001800940856008500958 2010 eng d00aModel Predictive Control of Thermal Energy Storage in Building Cooling Systems0 aModel Predictive Control of Thermal Energy Storage in Building C aBaltimore, Maryland, USAc06/20103 aA 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.1 aMa, Yudong1 aBorrelli, Francesco1 aHencey, Brandon1 aCoffey, Brian, E.1 aBengea, Sorin1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/model-predictive-control-thermal01592nas a2200169 4500008004100000245013000041210006900171490000900240520096100249100002201210700001801232700002701250700002101277700002101298700001801319856008501337 2009 eng d00aTowards a Very Low Energy Building Stock: Modeling the US Commercial Building Stock to Support Policy and Innovation Planning0 aTowards a Very Low Energy Building Stock Modeling the US Commerc0 v37:53 a

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.

1 aCoffey, Brian, E.1 aBorgeson, Sam1 aSelkowitz, Stephen, E.1 aApte, Joshua, S.1 aMathew, Paul, A.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/towards-very-low-energy-building02680nas a2200133 4500008004100000245008800041210006900129260003600198520216900234100001802403700002202421700002002443856008302463 2008 eng d00aBenchmarking and Equipment and Controls Assessment for a ‘Big Box’ Retail Chain0 aBenchmarking and Equipment and Controls Assessment for a Big Box aAsilomar, California, USAc20083 a

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.

1 aHaves, Philip1 aCoffey, Brian, E.1 aWilliams, Scott uhttps://simulationresearch.lbl.gov/publications/benchmarking-and-equipment-and