Philip Haves

Model Predictive Control for the Operation of Building Cooling Systems

This brief presents a model-based predictive control (MPC) approach to building cooling systems with thermal energy storage. We focus on buildings equipped with a water tank used for actively storing cold water produced by a series of chillers. First, simplified models of chillers, cooling towers, thermal storage tanks, and buildings are developed and validated for the purpose of model-based control design. Then an MPC for the chilling system operation is proposed to optimally store the thermal energy in the tank by using predictive knowledge of building loads and weather conditions. This brief addresses real-time implementation and feasibility issues of the MPC scheme by using a simplified hybrid model of the system, a periodic robust invariant set as terminal constraints, and a moving window blocking strategy. The controller is experimentally validated at the University of California, Merced. The experiments show a reduction in the central plant electricity cost and an improvement of its efficiency.

On approaches to couple energy simulation and computational fluid dynamics programs

Energy simulation (ES) and computational fluid dynamics (CFD) can play an important role in building design by providing complementary information of the building performance. However, separate applications of ES and CFD usually cannot give an accurate prediction of building thermal and flow behavior due to the assumptions used in the applications. An integration of ES and CFD can eliminate many of these assumptions, since the information provided by ES and CFD is complementary. This paper describes some efficient approaches to integrate ES and CFD, such as static and dynamic coupling strategies, in order to bridge the discontinuities of time-scale, spatial resolution and computing speed between ES and CFD programs. This investigation further demonstrates some of the strategies through two examples by using the EnergyPlus and MIT-CFD programs.

Analysis of an information monitoring and diagnostic system to improve building operations

This paper discusses a demonstration of a technology to address the problem that buildings do not perform as well as anticipated during design. We partnered with an innovative building operator to evaluate a prototype information monitoring and diagnostic system (IMDS). The IMDS consists of a set of high-quality sensors, data acquisition software and hardware, and data visualization software including a web-based remote access system, that can be used to identify control problems and equipment faults. The information system allowed the operators to make more effective use of the building control system and freeing up time to take care of other tenant needs. They report observing significant improvements in building comfort, potentially improving tenant health and productivity. The reduction in the labor costs to operate the building is about US

Model predictive control for the operation of building cooling systems

20,000 per year, which alone could pay for the information system in about 5 years. A control system retrofit based on findings from the information system is expected to reduce energy use by 20% over the next year, worth over US

A nodal model for displacement ventilation and chilled ceiling systems in office spaces

30,000 per year in energy cost savings. The operators are recommending that similar technology be adopted in other buildings.

Model-based real-time whole building energy performance monitoring and diagnostics

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 reduction in the central plant electricity cost and improvement of its efficiency.

Demand Shifting With Thermal Mass in Large Commercial Buildings: Field Tests, Simulation and Audits

Abstract A nodal model has been developed to represent room heat transfer in displacement ventilation and chilled ceiling systems. The model uses precalculated air flow rates to predict the air-temperature distribution and the division of the cooling load between the ventilation air and the chilled ceiling. The air movements in the plumes and the rest of the room are represented separately using a network of 10 air nodes. The values of the capacity rate parameters are calculated by solving the heat and mass balance equations for each node using measured temperatures as inputs. Correlations between parameter values for a range of cooling loads and supply air flow rates are presented.

Qualitative Comparison of North American and U.K. Cooling Load Calculation Methods

Building energy systems often consume approximately 16% more energy [Mills, E. 2011. “Building Commissioning: A Golden Opportunity for Reducing Energy Costs and Greenhouse Gas Emissions in the United States.” Energy Efficiency 4 (2): 145–173] than is necessary due to system deviation from the design intent. Identifying the root causes of energy waste in buildings can be challenging largely because energy flows are generally invisible. To help address this challenge, we present a model-based, real-time whole building energy diagnostics and performance monitoring system. The proposed system continuously acquires performance measurements of heating, ventilation and air-conditioning, lighting and plug equipment usage and compare these measurements in real-time to a reference EnergyPlus model that either represents the design intent for the building or has been calibrated to represent acceptable performance. A proof-of-concept demonstration in a real building is also presented.

Design and testing of a control strategy for a large, naturally ventilated office building

LBNL-58815 Demand Shifting With Thermal Mass in Large Commercial Buildings: Field Tests, Simulations and Audits Peng Xu, Philip Haves, MaryAnn Piette Lawrence Berkeley National Laboratory Leah Zagreus University of California at Berkeley Ernest Orlando Lawrence Berkeley National Laboratory 1 Cyclotron Road, MS90R3111 Berkeley, CA 94720 September 2005 This work described in this report was coordinated by the Demand Response Research Center and funded by the California Energy Commission, Public Interest Energy Research Program, under Work for Others Contract No. 500- 03-026 and by the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

BacNet and Analog/Digital Interfaces of the Building Controls Virtual Testbed

A qualitative comparison is presented between three current North American and U.K. design cooling load calculation methods. The methods compared are the ASHRAE Heat Balance Method, the Radiant Time Series Method and the Admittance Method, used in the U.K. The methods are compared and contrasted in terms of their overall structure. In order to generate the values of the 24 hourly cooling loads, comparison was also made in terms of the processing of the input data and the solution of the equations required. Specific comparisons are made between the approximations used by the three calculation methods to model some of the principal heat transfer mechanisms. Conclusions are drawn regarding the ability of the simplified methods to correctly predict peak-cooling loads compared to the Heat Balance Method predictions. Comment is also made on the potential for developing similar approaches to cooling load calculation in the U.K. and North America in the future.