Analysis on energy saving measures of heat exchange station in central heating system

Gao, Bin; Zhang, Linfang; Tian, Yanfa; Zhou, M.

doi:10.1016/j.proeng.2017.10.422

Cited by 6 publications

(1 citation statement)

References 3 publications

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“…The heat exchange station also provides heat for the indoor radiator, and the control mode of its heating water pumps is a key factor affecting indoor thermal comfort. The centralized water pump control model [11] cannot provide accurate heating to meet the needs of residential buildings. To ensure a comfortable indoor temperature of all households, each water pump distributes the heat supply evenly, resulting in an indoor temperature that is excessively high for users situated close to the heat supply source, which not only fails to achieve human comfort but is also a waste of energy.…”

Section: Introductionmentioning

confidence: 99%

Distributed model predictive control for central heating of high-rise residential buildings

Zhou

Zhao³

2022

Journal of Asian Architecture and Building Engineering

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Central heating system faults affect building energy consumption and indoor thermal comfort significantly. To aim at the balance between thermal comfortable and energy-saving of the heating system for high-rise residential buildings, this paper proposes a method for the central heating system of high-rise residential buildings based on distributed model predictive control. The method analyzes the coupling factors between adjacent rooms' temperature. Based on the state space method, a multivariable indoor temperature model is established and verified.The distributed model predictive control method is used to control and optimize the indoor temperature, and the load distribution of the circulating water pump in the heat exchange station is optimized according to the predicted heat demand. The results demonstrate that the indoor temperature after distributed model predictive control can stable near the set value. Compared with the centralized control methods, the proposed methodology can reduce energy consumption by 14.28%. Meanwhile, the efficiency of water pumps is increased by 16.74% after using the distributed control strategy.

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Section: Introductionmentioning

confidence: 99%