期刊
ENERGY AND BUILDINGS
卷 45, 期 -, 页码 15-27出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.enbuild.2011.09.022
关键词
Building climate control; Stochastic model predictive control; Energy efficiency; Chance-constrained control
资金
- Swisselectric Research
- Competence Center Energy and Mobility (CCEM-CH)
- Siemens Building Technologies
This paper presents an investigation of how Model Predictive Control (MPC) and weather predictions can increase the energy efficiency in Integrated Room Automation (IRA) while respecting occupant comfort. IRA deals with the simultaneous control of heating, ventilation and air conditioning (HVAC) as well as blind positioning and electric lighting of a building zone such that the room temperature as well as CO2 and luminance levels stay within given comfort ranges. MPC is an advanced control technique which, when applied to buildings, employs a model of the building dynamics and solves an optimization problem to determine the optimal control inputs. In this paper it is reported on the development and analysis of a Stochastic Model Predictive Control (SMPC) strategy for building climate control that takes into account the uncertainty due to the use of weather predictions. As first step the potential of MPC was assessed by means of a large-scale factorial simulation study that considered different types of buildings and HVAC systems at four representative European sites. Then for selected representative cases the control performance of SMPC, the impact of the accuracy of weather predictions, as well as the tunability of SMPC were investigated. The findings suggest that SMPC outperforms current control practice. (C) 2011 Elsevier B.V. All rights reserved.
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