TEMPERATURE CONTROL RESEARCH OF SOLAR-AIR SOURCE HEAT PUMP HEATING SYSTEM BASED ON ANFIS

Yu Qihui; Tan Xin; Wu Linfeng; Liu Zejiang; Wang Yahui; Sun Guoxin

doi:10.19912/j.0254-0096.tynxb.2022-1609

PDF(2431 KB)

Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (2) : 16-22. DOI: 10.19912/j.0254-0096.tynxb.2022-1609

TEMPERATURE CONTROL RESEARCH OF SOLAR-AIR SOURCE HEAT PUMP HEATING SYSTEM BASED ON ANFIS

Tan Xin, Wu Linfeng, Yu Qihui, Liu Zejiang, Wang Yahui, Sun Guoxin

Author information +

History +

Abstract

An improved fuzzy control method based on adaptive neuro-fuzzy inference system （ANFIS） is proposed in order to address the issue that the operation environment of solar-air source heat pump heating systems is complex and variable, and the design of fuzzy controller heavily depends on artificial experience. This technique establishes the off-working condition ANFIS model of the combined heating system, generates the fuzzy rule base that adapts to the system performance, and passes it to the fuzzy controller for execution. It makes use of the benefits of ANFIS in complex system modeling, along with the temperature response characteristics of the heating system and the actual operation data. According to the findings of the Matlab/Simulink simulation, the control precision and response speed of this approach are greater by 17.65% and 36.4%, respectively, when compared to a single fuzzy control.

Key words

solar energy / air source heat pump / district heating / fuzzy control / temperature control / ANFIS

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Tan Xin, Wu Linfeng, Yu Qihui, Liu Zejiang, Wang Yahui, Sun Guoxin. TEMPERATURE CONTROL RESEARCH OF SOLAR-AIR SOURCE HEAT PUMP HEATING SYSTEM BASED ON ANFIS[J]. Acta Energiae Solaris Sinica. 2024, 45(2): 16-22 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1609

References

[1] HUANG B J, LEE C P.Long-term performance of solar-assisted heat pump water heater[J]. Renewable energy, 2004, 29(4): 633-639.
[2] KAYGUSUZ K, AYHAN T.Experimental and theoretical investigation of combined solar heat pump system for residential heating[J]. Energy conversion and management, 1999, 40(13): 1377-1396.
[3] CARBONI C, MONTANARI R.Solar thermal systems: advantages in domestic integration[J]. Renewable energy, 2008, 33(6): 1364-1373.
[4] 孙先鹏, 郭康权, 邹志荣, 等. 太阳能联合空气源热泵系统温室供热实验研究[J]. 太阳能学报, 2016, 37(3): 658-665.
SUN X P, GUO K Q, ZOU Z R, et al.System investigation of a solar combined with air-source heat pump system for greenhouse heating[J]. Acta energiae solaris sinica, 2016, 37(3): 658-665.
[5] POPPI S, BALES C, HEINZ A, et al.Analysis of system improvements in solar thermal and air source heat pump combisystems[J]. Applied energy, 2016, 173: 606-623.
[6] 王晓天. 基于模糊PID温度控制算法的建筑节能调温系统[J]. 科技创新与应用, 2022, 12(17): 6-10.
WANG X T.Energy-saving temperature regulating system based on fuzzy PID temperature control algorithm[J]. Technology innovation and application, 2022, 12(17): 6-10.
[7] KNUUTINEN J, BÖÖK H, RUUSKANEN V, et al. Ground source heat pump control methods for solar photovoltaic-assisted domestic hot water heating[J]. Renewable energy, 2021, 177: 732-742.
[8] GOUDA M M, DANAHER S, UNDERWOOD C P.Quasi-adaptive fuzzy heating control of solar buildings[J]. Building and environment, 2006, 41(12): 1881-1891.
[9] MENDI F, BORAN K, KULEKCI M K.Fuzzy controlled central heating system[J]. International journal of energy research, 2002, 26(15): 1313-1322.
[10] 张志红, 韩直, 肖盛燮, 等. 基于ANFIS交通流实时预测及在MATLAB中的实现[J]. 重庆交通学院学报, 2007, 26(3): 112-115.
ZHANG Z H, HAN Z, XIAO S X, et al.Real-time forecast of traffic flow based on ANFIS and its realization by MATLAB[J]. Journal of Chongqing Jiaotong university, 2007, 26(3): 112-115.
[11] QIAO J F, ZHANG W, HAN H G.Self-organizing fuzzy control for dissolved oxygen concentration using fuzzy neural network 1[J]. Journal of intelligent & fuzzy systems: applications in engineering and technology, 2016, 30(6): 3411-3422.
[12] DAI Y, ZHU X A, ZHOU H B, et al.Trajectory tracking control for seafloor tracked vehicle by adaptive neural-fuzzy inference system algorithm[J]. International journal of computers communications & control, 2018, 13(4): 465-476.
[13] ELHOSSEINI M A, EL SEHIEMY R A, SALAH A H, et al. Modeling and control of an interconnected combined cycle gas turbine using fuzzy and ANFIS controllers[J]. Electrical engineering, 2018, 100(2): 763-785.
[14] 吴小舟, 赵加宁, 魏建民. 供暖型风机盘管散热量计算方法的探讨[J]. 暖通空调, 2010, 40(7): 63-66.
WU X Z, ZHAO J N, WEI J M.Study of heat release calculation method of heating-only fan coil unit[J]. Heating ventilating & air conditioning, 2010, 40(7): 63-66.
[15] TAN X, ZHU Z J, SUN G X, et al.Modeling and simulation of layered water tank based on MATLAB/SIMULINK[J]. Journal of physics: conference series, 2022, 2173(1): 012005.
[16] TAN X, ZHU Z J, SUN G X, et al.Room thermal load prediction based on analytic hierarchy process and back-propagation neural networks[J]. Building simulation, 2022, 15(11): 1989-2002.
[17] 王振浩, 杜虹锦, 李国庆. 基于模糊控制的风电场群并网点电压调节方法[J]. 太阳能学报, 2019, 40(8): 2205-2211.
WANG Z H, DU H J, LI G Q.Voltage regulation method on PCC of wind farms based on fuzzy coordination[J]. Acta energiae solaris sinica, 2019, 40(8): 2205-2211.
[18] 崔高健, 曲永利, 凡东生. 基于模糊控制的集中供热控制器的研究[J]. 建筑节能, 2011, 39(4): 9-10, 28.
CUI G J, QU Y L, FAN D S.Controller analysis of centralized heating system based on fuzzy control[J]. Building energy efficiency, 2011, 39(4): 9-10, 28.
[19] 彭玉楼, 路秋静. 基于自适应神经模糊推理系统的微波炉温度控制[J]. 陕西科技大学学报, 2004, 22(2): 42-44, 85.
PENG Y L, LU Q J.Temperature control of micro-wave oven based on anfis[J]. Journal of Shaanxi University of Science & Technoloy, 2004, 22(2): 42-44, 85.
[20] WANG W C, TAI C C.Magnetic induction of hyperthermia by a modified self-learning fuzzy temperature controller[J]. The review of scientific instruments, 2017, 88(7): 074702.
[21] 赵刚, 张九根, 杨珊珊, 等. 基于改进遗传算法的模糊温度控制在空调中的应用[J]. 科技通报, 2017, 33(8): 156-161.
ZHAO G, ZHANG J G, YANG S S, et al.Application of fuzzy temperature control in air-condition based on improved GA[J]. Bulletin of science and technology, 2017, 33(8): 156-161.