Accurate model reduction and control of radiator for performance enhancement of room heating system

Wang, Yaran; You, Shijun; Zheng, Xuejing; Zhang, Huan

doi:10.1016/j.enbuild.2016.12.034

Cited by 18 publications

(4 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Wang [15] proposed that two-degrees-of-freedom H∞ control can be applied to the radiator control. Fatemeh Tahersima [16] used a gain scheduling controller based on the current parameter change model of radiation dynamics.…”

Section: Literature Reviewmentioning

confidence: 99%

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

Zhou

Zhao³

2022

Journal of Asian Architecture and Building Engineering

View full text Add to dashboard Cite

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.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

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

Zhou

Zhao³

2022

Journal of Asian Architecture and Building Engineering

View full text Add to dashboard Cite

show abstract

“…According to the standard EN215 [29] and researches in [28,30], the water flow rate through the TV depends on the difference between measured indoor air temperature and the closing temperature or opening temperature of TV. To simplify the control process, proportional integral (PI) controller is applied to approximate the performance of the TV in [31,32]. The PI controller in the TV model is shown in Fig.…”

Section: Thermostatic Valve Modelmentioning

confidence: 99%

Operation strategies to achieve low supply and return temperature in district heating system

Nord

2019

E3S Web Conf.

View full text Add to dashboard Cite

Low temperature is the most significant feature of the future district heating (DH) - the 4th generation district heating (4GDH). The revolutionary temperature level (50–55/25°C) will improve the efficiency of heat sources, thermal storages, and distribution systems, meanwhile, bring huge potentials to renewable energies. One challenge of transition to the future DH is the compatibility of current customer installations and the future temperature level. The aim of this study was to find the temperature potential of Norwegian residential buildings for the future DH system. A reference apartment was created, and typical space heating (SH) system was designed. A detailed building and SH system model were built in Modelica® language, and simulation was conducted via Dymola environment. Different operation strategies: PI control of the supply temperature, weather compensated control of the supply temperature, and PI control of the return temperature were tested. The results of the study showed the average supply temperature could be as low as 56~58°C, and only limited time the temperature was above 60 °C, when the controlled supply temperature strategies were applied. For the case with controlled return temperature strategies, the average return temperature were 30 and 37°C, while the average required supply temperature could be 72 and 94°C. The conclusion was that the low supply temperature could be achieved through optimized operation strategies. Whereas, the low return temperature was not able to be achieved only by improving the operation strategy.

show abstract

“…In recent years, the indoor temperature control system of central heating has made a lot of progress [7]. For example, for the robust control of the radiator heating system [8], a gain scheduling controller based on the current parameter variation model of radiation dynamics is proposed for the instability of the constant temperature radiator valve [9]. In view of the lag of room temperature change in the control process, model predictive control uses mathematical models to predict and control the heat load of buildings to minimize heating energy consumption [10].…”

Section: Introductionmentioning

confidence: 99%

Application and effect analysis of heating system based on tri-network joint regulation and control technology

Zhang

2021

THERM SCI

View full text Add to dashboard Cite

In recent years, the state promotes intelligent heating and clean heating, which aims to achieve energy saving, emission reduction, cost reduction and efficiency, and improve the social and economic benefits of heating enterprises on the premise of ensuring the heat demand of the terminal heat users of the heating system. This paper first introduces the current situation of the heating system, analyzes the main problems and causes of the current heating system, and then analyzes the practical application and operation data of the three-network joint control technology of the heating system independently developed by Jilin Yuheng Industrial Electric Co., Ltd in Changchun Lianhuashan Thermal Power Co., Ltd., and finally comes to the conclusion that the application of this technology makes the heating system energy-saving effect is remarkable. It can adapt to all kinds of complex heating systems and has good market prospect and application value.

show abstract

Accurate model reduction and control of radiator for performance enhancement of room heating system

Cited by 18 publications

References 21 publications

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

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

Operation strategies to achieve low supply and return temperature in district heating system

Application and effect analysis of heating system based on tri-network joint regulation and control technology

Contact Info

Product

Resources

About