Modeling and control optimization of photovoltaic-thermal heating system based on MPC

doi:10.3969/j.issn.2097-0706.2024.07.003

Abstract

Abstract:

To reduce the energy consumption and fight against environmental pollution crises caused by heating in northern China， and to improve the insufficient light utilization efficiency in areas with abundant or relatively abundant solar resources， a distributed energy system combining solar energy and building heating is proposed，taking the advantages of off-peak electricity and sufficient illumination. The model of the proposed photovoltaic-thermal heating system is built based on TRNSYS dynamic modeling and numerical modeling. Then， considering the time-lag of the heat-supply system for a small area and the output of each device in the system， a model predictive control（MPC） strategy is developed based on Matlab， and an MPC-based optimization control strategy which can realize real-time error correction is made. According to the analysis results： the MPC-based optimization control can keep the maximum error of tracking heat load within 4.16%，and decrease the average error by 2.79%； and the optimization control can keep the maximum deviation of indoor temperature within 1.2 ℃，which is 0.2 ℃ lower that without the control； under a solar radiation intensity approaching 800 W/m²，the difference between solar energy utilization rates with and without the optimization control goes up to a maximum of 8.9%.The results indicate that the MPC can track heat load fluctuations in buildings quickly and accurately，suppress indoor temperature fluctuations effectively and increase the utilization rate of clean energy.

Key words: photovoltaic-thermal heating system, dynamic modeling, numerical modeling, model predictive control, error correction and optimization, building heating

CLC Number:

TK51:TU241

WANG Zhe, CHENG Gang, XING Zuoxia, FU Qitong, FU Changtao. Modeling and control optimization of photovoltaic-thermal heating system based on MPC[J]. Integrated Intelligent Energy, 2024, 46(7): 21-28.

Figures/Tables 9

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References 25

[1]	国家能源局. 关于建立健全清洁能源消纳长效机制的指导意见[EB/OL].(2020-05-18)[2024-02-02]. http://www.nea.gov.cn/2020-05/19/c_139069819.htm.
[2]	史云乾. 分布式能源系统建模及动态仿真研究[D]. 北京: 华北电力大学, 2023.
	SHI Yunqian. Study on modeling and dynamic simulation of distributed energy system[D]. Beijing: North China Electric Power University, 2023.
[3]	韩鑫. 分布式能源系统构造及建模研究[D]. 太原: 太原理工大学, 2015.
	HAN Xin. The research on construction and optimization of distributed enemy systems[D]. Taiyuan: Taiyuan University of Technology, 2015.
[4]	汪峰. 楼宇式分布式能源系统设计与优化研究[D]. 南京: 南京师范大学, 2020.
	WANG Feng. Research on the design and optimization of building-type distributed energy system[D]. Nanjing: Nanjing Normal University, 2020.
[5]	刘艳峰, 唐欢龙, 王登甲, 等. 分布式“源汇一体”太阳能供暖新系统探索[J]. 暖通空调, 2023, 53(8):124-130.
	LIU Yanfeng, TANG Huanlong, WANG Dengjia, et al. Exploration of a new distributed solar heating system with"integrated source-sink"[J]. Heating Ventilating & Air Conditioning, 2023, 53(8): 124-130.
[6]	窦子慧, 刘景霞, 李宝利. 严寒地区太阳能跨季节蓄热热泵系统研究[J]. 综合智慧能源, 2023, 45(4):52-58. doi: 10.3969/j.issn.2097-0706.2023.04.008
	DOU Zihui, LIU Jingxia, LI Baoli. Study on the solar-assisted ground-source heat pump system with seasonal heat storage in cold regions[J]. Integrated Intelligent Energy, 2023, 45(4): 52-58. doi: 10.3969/j.issn.2097-0706.2023.04.008
[7]	郭锦伟, 谭心, 虞启辉, 等. 太阳能供暖系统室内热舒适性的研究[J]. 机械设计与制造, 2022(8):37-42.
	GUO Jinwei, TAN Xin, YU Qihui, et al. Study on indoor thermal comfort of solar heating system[J]. Machinery Design & Manufacture, 2022(8): 37-42.
[8]	李雪欣. 长短期耦合水蓄热太阳能供暖系统优化与经济性研究[D]. 大连: 大连理工大学, 2021.
	LI Xuexin. Optimization and economical study of solar heating system with pit and tank thermal storage[D]. Dalian: Dalian University of Technology, 2021.
[9]	ASVADI-KERMANI O, MOMENI H. A constrained distributed time-series neural network MPC approach for HVAC system energy saving in a medium-large building[J]. Journal of Building Performance Simulation, 2021, 14(4): 383-400.
[10]	CHEN L L, ZHANG Y. Accelerated distributed model predictive control for HVAC systems[J]. Control Engineering Prac tice, 2021, 110: 104782.
[11]	RAMAN N S, CHEN B, BAROOAH P. On energy-efficient HVAC operation with model predictive control:A multiple climate zone study[J]. Applied Energy, 2022, 324: 119752.
[12]	LI Y C, ZHANG L, FENG B. Optimization of thermal performance of high temperature sensible heat thermal energy storage system for direct steam generation: A simulation work[J]. Applied Thermal Engineering, 2022, 217: 119225.
[13]	FRATE G F, FERRARI L, DESIDERI U. Multi-criteria investigation of a pumped thermal electricity storage (PTES) system with thermal integration and sensible heat storage[J]. Energy Conversion and Management, 2020, 208: 112530.
[14]	BADENHORST H. Optimising graphite composites and plate heat exchangers for latent thermal energy storage using measurements and simulation[J]. Journal of Energy Storage, 2020, 9: 101347.
[15]	陈娟. 能源互联网背景下的区域分布式能源系统规划研究[D]. 北京: 华北电力大学, 2017.
	CHEN Juan. Research on planning of regional distributed energy system under energy internet[D]. Beijing: North China Electric Power University, 2017.
[16]	李国帅. 直通式全玻璃真空集热器热性能研究[D]. 南京: 东南大学, 2020.
	LI Guoshuai. Research on thermal performance of straight through all-glass evacuated collector[D]. Nanjing: Southeast University, 2020.
[17]	代佳豪. 基于太阳能空气布雷顿循环与光伏蓄电池多能互补发电系统优化与仿真[D]. 杭州: 浙江大学, 2022.
	DAI Jiahao. Optimization and simulation of multi energy complementary power generation system with solar air Brayton cycle,photovoltaic and battery[D]. Hangzhou: Zhejiang University, 2022.
[18]	杨胜利. 基于模糊PID参数自整定的电加热炉温度控制系统设计[D]. 哈尔滨: 哈尔滨工业大学, 2018.
	YANG Shengli. Design of temperature control system for electric heating furnace based on fuzzy PID parameter self-tuning[D]. Harbin: Harbin Institute of Technology, 2018.
[19]	于志鹏, 张峰, 李国杰. 考虑热系统热力学属性的电-热综合能源系统建模[J]. 电气自动化, 2020, 42(3):83-86.
	YU Zhipeng, ZHANG Feng, LI Guojie. Modeling of an electric-thermal integrated energy system considering thermodynamic properties of the thermal system[J]. Electrical Automation, 2020, 42(3):83-86.
[20]	赵靖英, 胡劲, 张雪辉, 等. 基于锂电池模型和分数阶理论的SOC-SOH联合估计[J]. 电工技术学报, 2023, 38(17):4551-4563.
	ZHAO Jingying, HU Jin, ZHANG Xuehui, et al. Joint estimation of the SOC-SOH based on lithium battery model and fractional order theory[J]. Transactions of China Electrotechnical Society, 2023, 38(17): 4551-4563.
[21]	谢志林. 基于模型预测控制的多变量内模控制器设计[D]. 杭州: 浙江大学, 2022.
	XIE Zhilin. The design of multivariable internal model controller based on model predictive control[D]. Hangzhou: Zhejiang University, 2022.
[22]	张怡, 房方. 基于随机模型预测控制的智能楼宇能量管理方法[J]. 综合智慧能源, 2022, 44(10):83-90. doi: 10.3969/j.issn.2097-0706.2022.10.011
	ZHANG Yi, FANG Fang. Smart building energy management strategy based on stochastic model predictive control[J]. Integrated Intelligent Energy, 2022, 44(10):83-90. doi: 10.3969/j.issn.2097-0706.2022.10.011
[23]	姜翠翠, 罗万春. 浅谈数学建模中的灰色预测GM(1,1)模型的构建与应用[J]. 高等数学研究, 2023, 26(4):31-33.
	JIANG Cuicui, LUO Wanchun. Construction and application of GM(1,1) model in mathematical modeling[J]. Studies in College Mathematics, 2023, 26(4):31-33.
[24]	MAGADUM C G, BAPAT M S. An approximation method to solve coupled system ODEs of order second using fuzzy transform[J]. Computational and Applied Mathematics, 2022, 41(8): 380.
[25]	高淑芳. 基于MPC方法的电锅炉蓄热系统优化控制研究[D]. 北京: 北京建筑大学, 2023.
	GAO Shufang. Study on the optimal control of electric boiler heat storage system based on MPC method[D]. Beijing: Beijing University of Civil Engineering and Architecture, 2023.