Abstract
A model predictive control (MPC) system with an adaptive building model based on thermal-electrical analogy for the hybrid air conditioning system using the radiant floor and all-air system for heating is proposed in this paper to solve the heating supply control difficulties of the railway station on Tibetan Plateau. The MPC controller applies an off-line method of updating the building model to improve the accuracy of predicting indoor conditions. The control performance of the adaptive MPC is compared with the proportional-integral-derivative (PID) control, as well as an MPC without adaptive model through simulation constructed based on a TRNSYS-MATLAB co-simulation testbed. The results show that the implementation of the adaptive MPC can improve indoor thermal comfort and reduce 22.2% energy consumption compared to the PID control. Compared to the MPC without adaptive model, the adaptive MPC achieves fewer violations of constraints and reduces energy consumption by 11.5% through periodic model updating. This study focuses on the design of a control system to maintain indoor thermal comfort and improve system efficiency. The proposed method could also be applied in other public buildings.
Highlights
With the rapid development of the economy and urbanization, the total energy consumption of buildings has increased sharply
It presents that the total energy consumption reduces from 694,985 kWh of the PID control to 540,961 kWh of the adaptive model predictive control (MPC), achieving a 22.2% energy saving rate by the MPC as compared to the PID among which the heat source, pump and fan are reduced by 23.6%, 13.1% and 11.7%, respectively
This paper presented an adaptive model predictive control for hybrid air conditioning heating to address the problems of indoor thermal comfort and energy consumption in the railway passenger station on Tibetan Plateau
Summary
With the rapid development of the economy and urbanization, the total energy consumption of buildings has increased sharply. Joe et al [8] developed an MPC controller for hydronic radiant floor systems in office buildings, energy savings of 34% were achieved in the cooling season and. Designed an MPC controller based on supervisory for the residential HVAC systems which applied multi-zone AHU in summer and radiant floor heating systems in winter, achieving up to 50% cost savings. An MPC system is developed using an RC-model-based building dynamic model to control the hybrid air conditioning system to achieve efficient energy use and maintain human thermal comfort. (2) presents an adaptive MPC method for the hybrid air conditioning system (i.e., the radiant floor and all-air system for heating) based on data-driven updated building models The innovation spots of the work lie in: (1) develops the MPC system in the large space to solve overheating or overcooling of indoor environment problem caused by the poor control system of Tibetan Plateau heating. (2) presents an adaptive MPC method for the hybrid air conditioning system (i.e., the radiant floor and all-air system for heating) based on data-driven updated building models
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