基于PMV指标的空调系统舒适控制研究
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摘要
传统的空调控制系统以室内空气的温湿度作为控制对象，而实际上影响人体热舒适的因素不仅包括温度与湿度，还有风速、平均辐射温度、人体的衣着热阻和人体的新陈代谢率，人体对环境的冷热感受是这些因素综合作用的结果，因此在很多时候系统并不能满足人体对热舒适的需要而且节能性较差。于是人们在对传统空调系统的反思以及对热舒适理论和热舒适指标的研究基础上，提出了一种新型空调控制模式：热舒适指标控制，又名舒适控制。所谓舒适控制是以热舒适指标作为HVAC系统控制目标的运行控制方式。采用舒适控制后，空调系统的作用点从室内空气转移到了人体，使空调系统的控制随着人体舒适感的变化而变化。
由于PMV指标不仅包含了与人体热舒适相关的六大因素，而且有较成熟的理论基础并经过了实践的检验，因此本文选择PMV指标作为舒适控制中的研究对象，并分析了各环境变量变化时对PMV的影响。采用舒适控制后最大的优点在于舒适与节能的和谐统一，为了与传统空调方式进行对比，建立一能耗分析模型，根据室内空气热平衡和围护结构内表面的热平衡，可以对空调房间热环境与负荷变化进行动态分析。分析结果表明采用舒适控制后，不仅能满足人体对热舒适的需求，而且具有较大的节能潜力，可以通过调节各环境参数的组合使空调系统的能耗最小。因此通过建立室内环境参数优化模型对室内环境参数进行优化组合，结果表明，经过优化后在等舒适条件下系统的节能效果显著。
舒适控制的控制策略分为直接方式与间接方式两种，直接法由于对控制算法以及空调系统的测控设备要求较高，在实现上要比间接法要难一些但却能更好地体现舒适控制的优越性。由于PMV指标的多变量、非线性特点以及HVAC的复杂性，在实现上采用基于精确数学模型的经典控制理论有一定的难度，一般采用智能控制理论实现。因此提出了一种基于模糊控制的直接热舒适指标控制策略，仿真结果表明具有较好的控制效果。
In a conventional HVAC control system, only air temperature and air humidity are controlled. As we all know, occupants' thermal sense is mainly dependent on the six factors: inside air temperature, humidity, air velocity, mean radiant temperature, clothing and metabolism rate. The traditional HVAC control system, neglecting other factors concerned with human comfort, only considering the inside air temperature and air humidity and indirectly impacting on occupants by the two parameters control, cannot satisfy the comfort requirement of occupants and is energy wasting as well. On the basis of the study on the thermal comfort theory and thermal comfort index, the so-called comfort index control(CI control) is defined as the control of HVAC system, which takes thermal comfort index as the control parameter. So if we convert the simple inside air temperature and humidity control into the thermal comfort index such as PMV as the control target in the HVAC control system which evaluates the synthetic effects of th
e thermal environment on human bodies, therefore, the HVAC system control will change with the human sense, which will bring us a real "comfortable" HVAC system.
PMV is the optimal choice of CI control, as it successfully related all the environmental variables with a person's thermal sense. Furthermore it has received comprehensive application in thermal environment engineering. For this reason this paper chooses the PMV index as the research object in the comfort control, and analysis of the influence to PMV index as the environmental variables change. In order to compare the two control strategies, a thermal energy model is established to undergo dynamic analysis to the thermal environment of the room. The result shows that comfort index control not only meet the thermal comfort requirement of human bodies, but also has large energy saving potential. An environmental variables optimization model is also established to optimize the environmental variables. The result shows that energy saving is obvious after optimization on the basis of the equal comfort lever.
The research of PMV comfort control strategy is the key problem in realizing comfort control. Different control strategies will produce different comfort and energy saving. In general, there are two different control strategies in comfort control as follows: Direct method and indirect method. In HVAC system, the control is of
complicacy, nonlinear, lagging and all kinds of interrupting factors, resulting in the traditional control method based on the precise mathematics model cannot reach the satisfactory dynamic-static effect. But the intelligent control offers a new way for the HVAC system control. The fuzzy logic control is an artificial intelligent method in the intelligent control. Simulation showed that this method has satisfactory dynamic-static effect.
由于PMV指标不仅包含了与人体热舒适相关的六大因素，而且有较成熟的理论基础并经过了实践的检验，因此本文选择PMV指标作为舒适控制中的研究对象，并分析了各环境变量变化时对PMV的影响。采用舒适控制后最大的优点在于舒适与节能的和谐统一，为了与传统空调方式进行对比，建立一能耗分析模型，根据室内空气热平衡和围护结构内表面的热平衡，可以对空调房间热环境与负荷变化进行动态分析。分析结果表明采用舒适控制后，不仅能满足人体对热舒适的需求，而且具有较大的节能潜力，可以通过调节各环境参数的组合使空调系统的能耗最小。因此通过建立室内环境参数优化模型对室内环境参数进行优化组合，结果表明，经过优化后在等舒适条件下系统的节能效果显著。
舒适控制的控制策略分为直接方式与间接方式两种，直接法由于对控制算法以及空调系统的测控设备要求较高，在实现上要比间接法要难一些但却能更好地体现舒适控制的优越性。由于PMV指标的多变量、非线性特点以及HVAC的复杂性，在实现上采用基于精确数学模型的经典控制理论有一定的难度，一般采用智能控制理论实现。因此提出了一种基于模糊控制的直接热舒适指标控制策略，仿真结果表明具有较好的控制效果。
In a conventional HVAC control system, only air temperature and air humidity are controlled. As we all know, occupants' thermal sense is mainly dependent on the six factors: inside air temperature, humidity, air velocity, mean radiant temperature, clothing and metabolism rate. The traditional HVAC control system, neglecting other factors concerned with human comfort, only considering the inside air temperature and air humidity and indirectly impacting on occupants by the two parameters control, cannot satisfy the comfort requirement of occupants and is energy wasting as well. On the basis of the study on the thermal comfort theory and thermal comfort index, the so-called comfort index control(CI control) is defined as the control of HVAC system, which takes thermal comfort index as the control parameter. So if we convert the simple inside air temperature and humidity control into the thermal comfort index such as PMV as the control target in the HVAC control system which evaluates the synthetic effects of th
e thermal environment on human bodies, therefore, the HVAC system control will change with the human sense, which will bring us a real "comfortable" HVAC system.
PMV is the optimal choice of CI control, as it successfully related all the environmental variables with a person's thermal sense. Furthermore it has received comprehensive application in thermal environment engineering. For this reason this paper chooses the PMV index as the research object in the comfort control, and analysis of the influence to PMV index as the environmental variables change. In order to compare the two control strategies, a thermal energy model is established to undergo dynamic analysis to the thermal environment of the room. The result shows that comfort index control not only meet the thermal comfort requirement of human bodies, but also has large energy saving potential. An environmental variables optimization model is also established to optimize the environmental variables. The result shows that energy saving is obvious after optimization on the basis of the equal comfort lever.
The research of PMV comfort control strategy is the key problem in realizing comfort control. Different control strategies will produce different comfort and energy saving. In general, there are two different control strategies in comfort control as follows: Direct method and indirect method. In HVAC system, the control is of
complicacy, nonlinear, lagging and all kinds of interrupting factors, resulting in the traditional control method based on the precise mathematics model cannot reach the satisfactory dynamic-static effect. But the intelligent control offers a new way for the HVAC system control. The fuzzy logic control is an artificial intelligent method in the intelligent control. Simulation showed that this method has satisfactory dynamic-static effect.
引文
[1] ASHRAE, 1985. ASHRAE Handbook of fundamentals, Chapter 8, Thermal comfort
[2] 魏润柏，徐文华．热环境．上海：同济大学出版社，1994
[3] 杨昌智，刘光大，李念平．暖通空调工程设计方法与系统分析．北京：中国建筑工业出版社，2001
[4] S. Tanabe, K. Kimura. Effects of air temperature, humidity, and air movement on thermal comfort under humid conditions. ASHRAE Trans, 1994, 100(2): 953-969
[5] A. P. Gagge, A. P. Fobelets, L. G. Berglund. A standard predictive index of human response to the thermal environment. ASHRAE Trans, 1986, 92(2): 709-731
[6] P. O. Fanger. Calculation of thermal comfort: Introduction of a basic comfort equation. ASHRAE Trans, 1973, 78:Ⅲ. 4.1-Ⅲ. 4. 16
[7] S. I. Mistry, S. S. Nair. Nonlinear HVAC computations using neual network. ASHRAE Trans, 1993, 99(1): 775-784
[8] ASHRAE, 1985. ASHRAE Handbook of fundamentals, Chapter 13, Measurement and Instruments
[9] M. A. Abdelrahman. Field evaluation of a comfort meter. ASHRAE Trans, 1990, 96(2): 212-215
[10] 范存养．热舒适评价指标PMV及其实际应用．暖通空调，1993(3)：22-26
[11] W. L. Tse, T. P. Albert. Implementation of comfort-based air-handling unit control algrithms. ASHRAE Trans, 2000, 106(1): 29-43
[12] 叶国栋．舒适空调中的热舒适指标控制研究．[湖南大学硕士论文]，长沙，2002
[13] 廖传善，等编著．空调设备与系统的节能控制．北京：中国建筑工业出版社，1984
[14] 阎斌，郭春信，程宝义等．舒适性空调室内设计参数的优化．暖通空调1999，29(1)：44-45
[15] 徐文华．确定舒适性空调室内设计参数的新方法．同济大学学报，1992，
20(4)：445-449
[16] 郭富军．热环境评价指标在HVAC中的应用研究．[湖南大学硕士论文]，长沙，2000
[17] 姚普明，陈秋芳．模糊控制在制冷空调中的应用．天津商学院学报，1996(3)：27-33
[18] 江大勇，黄道．人工神经网络在暖通空调系统中的应用．暖通空调，2000(6)：39-41
[19] 鲍世雄，等．神经网络及其在制冷空调业的应用．流体机械，1997(3)：34-37
[20] A. Kaya, C. S. Chen, S. Raina, and S. J. Alexander. Optimum control polices to minimize energy use in HVAC systems. ASHRAE Trans, 1988, 88(2): 235-248
[21] J. W. MacArthur. Humidity and predicted-mean-vote based (PMV based) comfort control. ASHRAE Trans, 1986, 92(1B): 5-17
[22] D. G. Scheatzle. The development of PMV-based control for a residence in a hot and arid climate. ASHRAE Trans, 1991, 97(2): 1002-1019
[23] H. I. Henderson, K. Rengarajian, and D. B. Shirly. The impact of comfort control on air conditioner energy use in humid climates. ASHRAE Trans, 1992, 98(2): 104-113
[24] P. Simonds. Thermal comfort and optimal energy use. ASHRAE Trans, 1993, 99(1): 1037-1048
[25] S. Funakoshi, K. Matsuo. PMV-based train air conditioning control system. ASHRAE Trans, 1995, 101(1):423-430
[26] K. H. Yang, C. H. Su. An approach to building energy savings using the PMV index. Building and Environment, 1997, Vol. 32, No. 1, pp. 25-30
[27] J. Xia, H. Yu, X. Jin, G. Huang. A PMV-based controller for VAV applications. Proc. of ACHRB'2000, Shanghai. 2000
[28] T. Goto, L. G. Berglund. Fan air speed controls assisted by human response simulation for comfort in warm environment. ISHVAC99, 1999, Vol(1). Shenzhen, China
[29] M. Kakegawa, L. G. Berglund. An automatic window opening system for comfort control assisted by human response simulation. ISHVAC99, 1999, Vol (1). Shenzhen, China
[30] 张良杰等．基于神经网络与模糊逻辑控制技术的舒逸智能空调控制器．制冷学报，1994(3)：54-57
[31] 于航等．以PMV为基础的模糊控制器在VAV空调系统中的应用．节能，2001(4)：3-7
[32] 杨昌智，叶国栋．空调系统的作用点及其舒适性、节能性探讨．暖通空调，待发表
[33] 杨昌智，吴健丹．暖通空调中的温热环境研究．湖南大学学报，1998(2)：97-99
[34] B. W. Olesen, J. Rosendahl, L. N. Kalisperis, L. H. Summers. Methods for measuring and evaluating the thermal radiation in a room. ASHRAE Trans, 1989, 95(1): 1028-1044
[35] AHRAE 1997. ASHRAE fundamentals handbook, chapter 8
[36] 文学军，赵荣义．动态热环境人体热感觉的模糊综合评判，清华大学学报1998，38(5)：23-27
[37] 彦启森，赵庆珠，陈在康．建筑热过程．北京：中国建筑工业出版社，1986
[38] 清华大学等四院校编．空气调节(第一版)．北京：中国建筑工业出版社，1985
[39] P. O. Fanger et al. Prediction of draft. ASHRAE J. 1987(1): 30
[40] 中原信生著，龙惟定等译．建筑和建筑设备的节能．北京：中国建筑工业出版社，1990
[41] 范存养，龙惟定．面向地球环境时代的空调技术．制冷与空调，2001，第1卷，第1期
[42] 亢燕铭，徐惠英，杨养勤．地板辐射采暖的节能效应分析．见：全国暖通空调制冷2000年学术年会论文集．2000．32-35
[43] 中华人民共和国国家标准，GBJ19—87，采暖通风与空气调节设计规范．北京，1989
[44] 暖通空调规范．北京：中国建筑工业出版社，1998
[45] 刘耀洁，编著．建筑环境与设备的自动化．天津：天津大学出版社，2000
[46] 符曦，编著．系统最优化及控制．北京：机械工业出版社，1995
[47] J. M. House, T. F. Smith. A system approach to optimal control for HVAC and building systems. ASHRAE Trans, 1995, 101(2): 647-660
[48] J. M. House, T. F. Smith, J. S. Arora. Optimal control of a thermal system.
ASHRAE Trans, 1991, 97(2):991-1001
[49] J. E. Braun. Reducing energy costs and peak electrical demand through optimal control of building thermal storage. ASHRAE Trans, 1990, 96 (1):876-888
[50] M.E.Snyder, A.Newell. Cooling cost minimization using building mass for thermal storage. ASHRAE Trans, 1990, 6(1): 830-837
[51] J. L. Nizet, J. Lecomte, and F. X. Litt. Optimal control applied to air conditioning in building. ASHRAE Trans, 1984, 90(2): 587-600
[52] A. Kaya, C. S. Chen, S. Raina, and S. J. Alexander. Optimum control polices to minimize energy use in HVAC systems. ASHRAE Trans, 1988, 88(2): 235-248
[53] P. Simonds. Thermal comfort and optimal energy use. ASHRAE Trans, 1993, 99(1): 1037-1048
[54] 杨伦标，高英仪．模糊数学原理及应用．广州：华南理工大学出版社，1998
[55] 李世勇．模糊控制和智能控制的理论与研究．哈尔滨：哈尔滨工业大学出版社，1993
[56] 王顺晃等．智能控制系统及其应用．北京：机械工业出版社，1988
[57] 吴晓莉，林哲辉等．MATLAB辅助模糊系统设计．西安：西安电子科技大学出版社，2002
[58] 徐昕等．MATLAB工具箱应用指南．北京：电子工业出版社，2000
[2] 魏润柏，徐文华．热环境．上海：同济大学出版社，1994
[3] 杨昌智，刘光大，李念平．暖通空调工程设计方法与系统分析．北京：中国建筑工业出版社，2001
[4] S. Tanabe, K. Kimura. Effects of air temperature, humidity, and air movement on thermal comfort under humid conditions. ASHRAE Trans, 1994, 100(2): 953-969
[5] A. P. Gagge, A. P. Fobelets, L. G. Berglund. A standard predictive index of human response to the thermal environment. ASHRAE Trans, 1986, 92(2): 709-731
[6] P. O. Fanger. Calculation of thermal comfort: Introduction of a basic comfort equation. ASHRAE Trans, 1973, 78:Ⅲ. 4.1-Ⅲ. 4. 16
[7] S. I. Mistry, S. S. Nair. Nonlinear HVAC computations using neual network. ASHRAE Trans, 1993, 99(1): 775-784
[8] ASHRAE, 1985. ASHRAE Handbook of fundamentals, Chapter 13, Measurement and Instruments
[9] M. A. Abdelrahman. Field evaluation of a comfort meter. ASHRAE Trans, 1990, 96(2): 212-215
[10] 范存养．热舒适评价指标PMV及其实际应用．暖通空调，1993(3)：22-26
[11] W. L. Tse, T. P. Albert. Implementation of comfort-based air-handling unit control algrithms. ASHRAE Trans, 2000, 106(1): 29-43
[12] 叶国栋．舒适空调中的热舒适指标控制研究．[湖南大学硕士论文]，长沙，2002
[13] 廖传善，等编著．空调设备与系统的节能控制．北京：中国建筑工业出版社，1984
[14] 阎斌，郭春信，程宝义等．舒适性空调室内设计参数的优化．暖通空调1999，29(1)：44-45
[15] 徐文华．确定舒适性空调室内设计参数的新方法．同济大学学报，1992，
20(4)：445-449
[16] 郭富军．热环境评价指标在HVAC中的应用研究．[湖南大学硕士论文]，长沙，2000
[17] 姚普明，陈秋芳．模糊控制在制冷空调中的应用．天津商学院学报，1996(3)：27-33
[18] 江大勇，黄道．人工神经网络在暖通空调系统中的应用．暖通空调，2000(6)：39-41
[19] 鲍世雄，等．神经网络及其在制冷空调业的应用．流体机械，1997(3)：34-37
[20] A. Kaya, C. S. Chen, S. Raina, and S. J. Alexander. Optimum control polices to minimize energy use in HVAC systems. ASHRAE Trans, 1988, 88(2): 235-248
[21] J. W. MacArthur. Humidity and predicted-mean-vote based (PMV based) comfort control. ASHRAE Trans, 1986, 92(1B): 5-17
[22] D. G. Scheatzle. The development of PMV-based control for a residence in a hot and arid climate. ASHRAE Trans, 1991, 97(2): 1002-1019
[23] H. I. Henderson, K. Rengarajian, and D. B. Shirly. The impact of comfort control on air conditioner energy use in humid climates. ASHRAE Trans, 1992, 98(2): 104-113
[24] P. Simonds. Thermal comfort and optimal energy use. ASHRAE Trans, 1993, 99(1): 1037-1048
[25] S. Funakoshi, K. Matsuo. PMV-based train air conditioning control system. ASHRAE Trans, 1995, 101(1):423-430
[26] K. H. Yang, C. H. Su. An approach to building energy savings using the PMV index. Building and Environment, 1997, Vol. 32, No. 1, pp. 25-30
[27] J. Xia, H. Yu, X. Jin, G. Huang. A PMV-based controller for VAV applications. Proc. of ACHRB'2000, Shanghai. 2000
[28] T. Goto, L. G. Berglund. Fan air speed controls assisted by human response simulation for comfort in warm environment. ISHVAC99, 1999, Vol(1). Shenzhen, China
[29] M. Kakegawa, L. G. Berglund. An automatic window opening system for comfort control assisted by human response simulation. ISHVAC99, 1999, Vol (1). Shenzhen, China
[30] 张良杰等．基于神经网络与模糊逻辑控制技术的舒逸智能空调控制器．制冷学报，1994(3)：54-57
[31] 于航等．以PMV为基础的模糊控制器在VAV空调系统中的应用．节能，2001(4)：3-7
[32] 杨昌智，叶国栋．空调系统的作用点及其舒适性、节能性探讨．暖通空调，待发表
[33] 杨昌智，吴健丹．暖通空调中的温热环境研究．湖南大学学报，1998(2)：97-99
[34] B. W. Olesen, J. Rosendahl, L. N. Kalisperis, L. H. Summers. Methods for measuring and evaluating the thermal radiation in a room. ASHRAE Trans, 1989, 95(1): 1028-1044
[35] AHRAE 1997. ASHRAE fundamentals handbook, chapter 8
[36] 文学军，赵荣义．动态热环境人体热感觉的模糊综合评判，清华大学学报1998，38(5)：23-27
[37] 彦启森，赵庆珠，陈在康．建筑热过程．北京：中国建筑工业出版社，1986
[38] 清华大学等四院校编．空气调节(第一版)．北京：中国建筑工业出版社，1985
[39] P. O. Fanger et al. Prediction of draft. ASHRAE J. 1987(1): 30
[40] 中原信生著，龙惟定等译．建筑和建筑设备的节能．北京：中国建筑工业出版社，1990
[41] 范存养，龙惟定．面向地球环境时代的空调技术．制冷与空调，2001，第1卷，第1期
[42] 亢燕铭，徐惠英，杨养勤．地板辐射采暖的节能效应分析．见：全国暖通空调制冷2000年学术年会论文集．2000．32-35
[43] 中华人民共和国国家标准，GBJ19—87，采暖通风与空气调节设计规范．北京，1989
[44] 暖通空调规范．北京：中国建筑工业出版社，1998
[45] 刘耀洁，编著．建筑环境与设备的自动化．天津：天津大学出版社，2000
[46] 符曦，编著．系统最优化及控制．北京：机械工业出版社，1995
[47] J. M. House, T. F. Smith. A system approach to optimal control for HVAC and building systems. ASHRAE Trans, 1995, 101(2): 647-660
[48] J. M. House, T. F. Smith, J. S. Arora. Optimal control of a thermal system.
ASHRAE Trans, 1991, 97(2):991-1001
[49] J. E. Braun. Reducing energy costs and peak electrical demand through optimal control of building thermal storage. ASHRAE Trans, 1990, 96 (1):876-888
[50] M.E.Snyder, A.Newell. Cooling cost minimization using building mass for thermal storage. ASHRAE Trans, 1990, 6(1): 830-837
[51] J. L. Nizet, J. Lecomte, and F. X. Litt. Optimal control applied to air conditioning in building. ASHRAE Trans, 1984, 90(2): 587-600
[52] A. Kaya, C. S. Chen, S. Raina, and S. J. Alexander. Optimum control polices to minimize energy use in HVAC systems. ASHRAE Trans, 1988, 88(2): 235-248
[53] P. Simonds. Thermal comfort and optimal energy use. ASHRAE Trans, 1993, 99(1): 1037-1048
[54] 杨伦标，高英仪．模糊数学原理及应用．广州：华南理工大学出版社，1998
[55] 李世勇．模糊控制和智能控制的理论与研究．哈尔滨：哈尔滨工业大学出版社，1993
[56] 王顺晃等．智能控制系统及其应用．北京：机械工业出版社，1988
[57] 吴晓莉，林哲辉等．MATLAB辅助模糊系统设计．西安：西安电子科技大学出版社，2002
[58] 徐昕等．MATLAB工具箱应用指南．北京：电子工业出版社，2000
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