针对小型空气源热泵中央空调系统提出一种室内外温度协同的供水温度在线优化控制策略,以提高空气源热泵系统室内热环境的控制效果并降低运行能耗。该优化策略以实时室外温度作为主参数,对供水温度进行前馈优化快速响应负荷变化,以实时室内温度作为辅参数,采用模糊自适应PI控制器进行反馈优化修正供水温度。利用TRNSYS软件建立空气源热泵中央空调系统仿真模型,代入石家庄某办公楼的设备功率和室内外温度等实测数据,验证了该优化策略下室内温度控制的精确性和鲁棒性较优。研究结果表明,在高、低两种负荷工况下,空调系统在该优化策略下的运行能耗均明显降低,高负荷时系统节能率19.64%,低负荷时系统节能率33.64%。所提出的室内外温度协同控制策略算法计算量小,易在常规温控设备中实现。
Abstract
For a small-scale air source heat pump （ASHP）-integrated central air-conditioning system, this paper proposed an online optimal control strategy for supply-water temperature based on indoor and outdoor temperature coordination. This study aims to improve the indoor thermal environment control performance as well as reduce the energy consumption of the ASHP system. In the optimal control strategy, the real-time outdoor temperature is used as the main parameter for the feedforward optimization of the supply-water temperature, which responds quickly to the coolingload. The real-time indoor temperature is used as an auxiliary parameter for feedback-based optimization by using the fuzzy adaptive PI controller to modify the calculated supply-water temperature. The simulation model of ASHP-integrated central air-conditioning system is established by using TRNSYS software, substituting measured data such as equipment power and indoor and outdoor temperatures from an office building in Shijiazhuang, Hebei Province. The simulation model is used to validate that the accuracy and robustness of the indoor temperature control under the optimization strategy are superior. The results demonstrate that the energy consumptions of the air-conditioning system is significantly reduced under both high-load and light-load conditions. The system energy saving rate is 19.64% and 33.64% for the high-load condition and the light-load conditions, respectively. The proposed indoor-outdoor temperature cooperative control strategy has advantages of small-level algorithm computational cost and easy-to-deploy in conventional temperature controller.
关键词
空气源热泵 /
温度控制 /
自适应算法 /
协同优化 /
空调节能
Key words
air source heat pumps /
temperature control /
adaptive algorithms /
collaborative optimization /
energy efficiency of air conditioning
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参考文献
[1] 陈晓宁, 李万勇, 张成全, 等. 低温环境下户式变频空气源热泵地板辐射采暖系统性能测试及分析[J]. 太阳能学报, 2018, 39(1): 57-63.
CHEN X N, LI W Y, ZHANG C Q, et al.Performance measurement and analysis of floor heating system with frequency inverter air source heat pump at low ambient temperatures[J]. Acta energiae solaris sinica, 2018, 39(1): 57-63.
[2] 谭心, 朱振经, 孙国鑫, 等. 基于模糊层次分析法的太阳能-空气源热泵复合供暖系统多目标优化[J]. 太阳能学报, 2022, 43(10): 94-103.
TAN X, ZHU Z J, SUN G X, et al.Multi-objective optimization of air-soloar source heat pump combined heating system based on fuzzy analytic hierarch process[J]. Acta energiae solaris sinica, 2022, 43(10): 94-103.
[3] 李露露, 尹应德, 刘世杰, 等. 供暖水温对低温空气源热泵制热性能影响的实验研究[J]. 太阳能学报, 2023, 44(4): 377-383.
LI L L, YIN Y D, LIU S J, et al.Experimental study on effect of heating water temperature on heating performance of low-temperature air source heat pump[J]. Acta energiae solaris sinica, 2023, 44(4): 377-383.
[4] 吴蔚. 家用中央空调调温系统的设计与应用[J]. 新经济, 2014(20): 120-121.
WU W.Design and application of temperature control system for household central air conditioning[J]. New economy, 2014(20): 120-121.
[5] 邵旭泽, 张华玲. 一种新型空气源热泵用水蓄能末端装置的传热特性[J]. 太阳能学报, 2023, 44(12): 420-424.
SHAO X Z, ZHANG H L.Heat transfer characteristics of water energy storage terminal device for new air source heat pump[J]. Acta energiae solaris sinica, 2023, 44(12): 420-424.
[6] 乐慧, 李好玥, 江亿. 用空气源热泵实现农村采暖的“煤改电” 同时为电力削峰填谷[J]. 中国能源, 2016, 38(11): 9-15.
LE H, LI H Y, JIANG Y.Realization of substituting coal with electricity and enhancing the efficiency of electricity allocation by using air source heat pump[J]. Energy of China, 2016, 38(11): 9-15.
[7] LI Z Y, MENG Q L, WEI Y A, et al.Dynamic room temperature setpoints of air-conditioning demand response based on heat balance equations with thermal comfort model as constraint: on-site experiment and simulation[J]. Journal of building engineering, 2023, 65: 105798.
[8] GRASSI B, PIANA E A, LEZZI A M, et al.A review of recent literature on systems and methods for the control of thermal comfort in buildings[J]. Applied sciences, 2022, 12(11): 5473.
[9] JIANG X J, XIAO J R, LI X Y.Energy consumption comparison of large-scale air-conditioning system with different temperature of chilled-water[J]. Procedia engineering, 2017, 205: 2100-2104.
[10] 陈霈, 牛洪海, 管晓晨, 等. 冰蓄冷系统冷冻水供水温度设定方法研究[J]. 建筑热能通风空调, 2022, 41(1): 13-16, 53.
CHEN P, NIU H H, GUAN X C, et al.Research on setting method of chilled water supply temperature of ice storage system[J]. Building energy & environment, 2022, 41(1): 13-16, 53.
[11] 范新舟, 姚晔. 集中空调水系统节能优化策略及仿真研究[J]. 制冷学报, 2021, 42(5): 64-72.
FAN X Z, YAO Y.Study on energy-saving optimization strategy and simulation of central air-conditioning water system[J]. Journal of refrigeration, 2021, 42(5): 64-72.
[12] 于军琪, 高之坤, 赵安军, 等. 中央空调冷冻水系统设备节能优化方法[J]. 哈尔滨工业大学学报, 2022, 54(12): 143-150.
YU J Q, GAO Z K, ZHAO A J, et al.Equipment energy-saving optimization method for central air-conditioning chilled water system[J]. Journal of Harbin Institute of Technology, 2022, 54(12): 143-150.
[13] 刘勇, 周振华, 厉昂, 等. 基于组态王软件的流量-液位前馈反馈控制方法研究与实现[J]. 传感器世界, 2023, 29(8): 37-43.
LIU Y, ZHOU Z H, LI A, et al.Research and implementation of flow level feedforward feedback control method based on Kingsview software[J]. Sensor world, 2023, 29(8): 37-43.
[14] 张恺, 张小松, 白建波. 模糊自适应PI法控制空调系统温度的研究[J]. 制冷空调与电力机械, 2006, 27(4): 20-23, 26.
ZHANG K, ZHANG X S, BAI J B.Research of fuzzy self-adaptive PI control in the air conditioning systems[J]. Refrigeration air conditioning & electric power machinery, 2006, 27(4): 20-23, 26.
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