暖通空调分布式优化算法研究及软件开发
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摘要
随着暖通空调日益普及,暖通空调系统的能量消耗一般占整个建筑耗电量的50%以上,但目前实际情况:绝大多数空调处在低效下运行,能源浪费严重。造成这种现象的主要原因是由于空调系统一般都按一定的环境条件和最大负荷计算,同时现有的暖通空调控制系统都是采用定工作点和定控制器参数设计,因此在线优化暖通空调控制系统的工作点,是实现暖通空调系统的能耗的关键问题。
暖通空调系统是由几台压缩机和几十台空气处理机及几百台空气末端装置构成,这些特性各异的设备通过风系统、冷媒系统和水系统关联耦合在一起,针对暖通空调系统的多参数、非线性、多耦合复杂系统,本文通过分析HVAC系统的运行工艺过程和各环节设备的能耗特点,提出了不需要建立系统层次模型的分布式协同优化结构及协同策略,将HVAC(Heating Ventilation and Air Conditioning)系统分解到二级层次,即相对独立的几个子系统,利用子系统间的耦合关系来完成整个系统的全局协同优化。
在此基础上,同时针对目前HVAC主流控制系统,开发了系统优化控制软件包。通过详细分析了HVAC控制系统运行特点,提出了基于VC++和SQLserver2000的开发的方案,并对软件内涉及到的多任务计算,利用了多线程技术解决了协同优化算法的并行计算问题,并通过内存映射文件技术解决了多程间的通讯和协同优化算法大量中间数据的复杂运算问题。通过实验室的HVAC装置取得实际数据验证,结果表明,软件基本功能设计完备,程序结构设计合理,运行稳定。在进行设定点优化时,通过分析加入协同策略和定工作点两种方法得到的曲线图,验证了协同优化算法对HVAC系统全局优化是高效的。
With gradual popularization of heating ventilating air conditioning (HVAC), energy consumption of HVAC commonly occupies more than 50 percent of energy consumption of the whole building. In fact, a majority of HVAC systems inefficiently runs, and wastes a mass of energy. The reason of the phenomenon is that loads of HVAC are calculated according to the most loads and some environment, and it adopts invariable working point and parameters of controller to devise the whole HVAC system. so, the set point of HVAC control system is optimized by Online is the key issue that HVAC system is to achieve the reduction of energy consumption.
HVAC system is composed of several Compressors and dozens of air handler devices and hundreds of air-terminal devices,these devices which have different characteristics are associated with air system, Refrigerant system and water system. HVAC system is a complex system of multi-parameter, nonlinear,multi-coupling.In this paper,by analyzing the operation of HVAC system and energy consumption characteristics of various aspects of process equipment, it bring up not to set up system-level model of distrubuted collaborative structure and coordinated strategy,HVAC system will break down into secondary level. The global collaborative optimization of the whole system will be completed by coupling relations between subsystems. On this basic,at the same time, for the current popular HVAC control system, developed a system optimization control package.Through a detail analysis of operating characteristics of HVAC control system, development plan was proposed development plan according to VC++6.0 and SQL SERVER 2000, the problem to calculation of multi-tasking is solved by multi-threading technology which realized parallel computing of collaborative optimization algorithm. As a result , collaborative optimization calculation has amount of central data,it leads to computing complexity,wo have solved this problem by memory-mapped file technology. Through actual data to verify,the results show that the software basic function is perfected,program structure was reasonable designed,stable operation. when carrying out set-point optimization,experiments show collaborative optimization algorithm is better than fixed set-point operation mode.
暖通空调系统是由几台压缩机和几十台空气处理机及几百台空气末端装置构成,这些特性各异的设备通过风系统、冷媒系统和水系统关联耦合在一起,针对暖通空调系统的多参数、非线性、多耦合复杂系统,本文通过分析HVAC系统的运行工艺过程和各环节设备的能耗特点,提出了不需要建立系统层次模型的分布式协同优化结构及协同策略,将HVAC(Heating Ventilation and Air Conditioning)系统分解到二级层次,即相对独立的几个子系统,利用子系统间的耦合关系来完成整个系统的全局协同优化。
在此基础上,同时针对目前HVAC主流控制系统,开发了系统优化控制软件包。通过详细分析了HVAC控制系统运行特点,提出了基于VC++和SQLserver2000的开发的方案,并对软件内涉及到的多任务计算,利用了多线程技术解决了协同优化算法的并行计算问题,并通过内存映射文件技术解决了多程间的通讯和协同优化算法大量中间数据的复杂运算问题。通过实验室的HVAC装置取得实际数据验证,结果表明,软件基本功能设计完备,程序结构设计合理,运行稳定。在进行设定点优化时,通过分析加入协同策略和定工作点两种方法得到的曲线图,验证了协同优化算法对HVAC系统全局优化是高效的。
With gradual popularization of heating ventilating air conditioning (HVAC), energy consumption of HVAC commonly occupies more than 50 percent of energy consumption of the whole building. In fact, a majority of HVAC systems inefficiently runs, and wastes a mass of energy. The reason of the phenomenon is that loads of HVAC are calculated according to the most loads and some environment, and it adopts invariable working point and parameters of controller to devise the whole HVAC system. so, the set point of HVAC control system is optimized by Online is the key issue that HVAC system is to achieve the reduction of energy consumption.
HVAC system is composed of several Compressors and dozens of air handler devices and hundreds of air-terminal devices,these devices which have different characteristics are associated with air system, Refrigerant system and water system. HVAC system is a complex system of multi-parameter, nonlinear,multi-coupling.In this paper,by analyzing the operation of HVAC system and energy consumption characteristics of various aspects of process equipment, it bring up not to set up system-level model of distrubuted collaborative structure and coordinated strategy,HVAC system will break down into secondary level. The global collaborative optimization of the whole system will be completed by coupling relations between subsystems. On this basic,at the same time, for the current popular HVAC control system, developed a system optimization control package.Through a detail analysis of operating characteristics of HVAC control system, development plan was proposed development plan according to VC++6.0 and SQL SERVER 2000, the problem to calculation of multi-tasking is solved by multi-threading technology which realized parallel computing of collaborative optimization algorithm. As a result , collaborative optimization calculation has amount of central data,it leads to computing complexity,wo have solved this problem by memory-mapped file technology. Through actual data to verify,the results show that the software basic function is perfected,program structure was reasonable designed,stable operation. when carrying out set-point optimization,experiments show collaborative optimization algorithm is better than fixed set-point operation mode.
引文
[1]王健伟.中央空调系统节能研究:(硕士学位论文).上海:上海海事大学,2006.
[2]Braun James E.A general control algorithm for cooling towers in cooling plants with electric and/or gas-driven chillers[J].HVAC and R Research,2007,v13,n 4,pp 581-598
[3]Kirsner W.Designing for chilled water supply temperature-does it save energy[J].ASHRAE J,1998,40(1):37-42
[4]Chu Chimin,Jong Tailang,Huang Yue wei.A study of thermal comfort control using least enthalpy estimator on HVAC system[C]American Control Conference,2005
[5]Nassif,N.Evolutionary algorithms for multi-objective optimization in HVAC system control strategy[C].Montreal:IEEE Annual Meeting,2004
[6]Lu Lu,Cai Wenjian,Xie Lihua,Li Shujiang.HVAC system optimization-In-building section[J].Energy and Buildings,v 37,n1,January,2005,p 11-22
[7]Jian Sun & Agami Reddy.Optimal control of building HVAC&R systems using complete simulation-based sequential quadratic programming(CSB-SQP)[J].Building & Environment.2005.Volume 40.Issue 5,pp.657-669
[8]Xue-Cheng Xi'Aun-Neow Poo & Siaw-Kiang Chou.Support Vector Regression Model Predictive Control On a HVAC Plant[J].Control Engineering Practice,2007.Volume 15.Issue 8,pp.897-908
[9]S.A.K.Al-Assadi,M.Zaheer-uddin Robust decentralized control of HVAC systems using H_∞-performance measures[J].Journal of the Franklin Institute 2005.Volume 341.Issue 7,pp.543-569
[10]Ming He,Wen-Jian Cai & Shao-Yuan Li.Multiple fuzzy model-based temperature predictive control for HVAC systems[J].Information Sciences 2005.Volume 169.Issue 1-2,pp.155-174
[11]Yao-Wen Wang,Wen-Jian Cai,Yeng-Chai Soh,Shu-Jiang Li,Lu Lu &Lihua Xie.A simplified modeling of cooling coils for control and optimization of HVAC Systems[J].Energy Conversion & Management 2004.Volume 48.Issue 18-19,pp.2915-2930
[12]Fong K F,Hanby V I.HVAC system optimization for energy management by evolutionary programming[J].Energy and Buildings,2006,38(3):220-231
[13]Chu Chimin,Jong Tailang,Huang Yue wei.A study of thermal comfort control using least enthalpy estimator on HVAC system[C]American Control Conference,2005
[14]Timothy I.Salsbury.A new pulse modulation adaptive controller(PMAC) applied to HVAC systems[J].Control Engineering Practice,2002.Volume 10.Issue 12,pp.1357-1370
[15]Song Q,Hu W J,Zhao T N.Robust neural network controller for variable airflow volume system[C]Control Theory and Application,IEEE Proceedings,2003,150(2):112-118
[16]Semsar E,Yazdanpanah M J,Lucas C.Nonlinear control and disturbance decoupling of an HVAC system via feedback linearization and back-stepping[C]Proceedings of 2003 IEEE Conference,2003
[17]W.Huang and H.N.Lam.Using genetic algorithms to optimize controller parameters for HVAC systems[J].Energy and Buildings 1997.Volume 26.Issue 3,pp.277-282
[18]孟华,龙惟定,王盛卫.基于遗传算法的空调水系统优化控制研究[J].建筑节能,2007
[19]晋欣桥 夏清 陈刚 王盛卫 变风量空调系统中的实时优化节能控制 节能 1999
[20]徐新华 王盛卫 多区域变风量空调系统优化控制研究 建筑热能通风空调 2006
[21]王军、王雁、邵惠鹤等 一种优化控制变风量空调系统的新方法 上海交通大学学报,2006,(02).
[22]晋欣桥:孙金龙:杜志敏 变风量空调系统中基于预测的末端再热控制策略 上海交通大学学报,2006,(02)
[23]孟华、王盛卫、龙惟定 空调水系统实时在线优化控制预测模型的研究 同济大学学报2006(05)
[24]张韵辉,吕震中,张小松.冷水机组的优化运行[J].暖通空调,2004,(07)
[25]曹双华,曹家枞.基于小波变换的神经网络空调负荷预测研究[J].暖通空调 2005,(04)
[26]林星春,曹家枞,马素贞.神经网络法及其在暖通空调负荷预测中的应用[J].制冷与空调2007
[27]施志钢.应用神经元自适应PSD控制变频空调系统的仿真研究[J].暖通空调 2006
[28]白建波.空调系统的鲁棒PI控制[C]东南大学动力工程系 2005
[29]江亿.暖通空调系统的计算机控制管理[J].暖通空调 1997,27(3):45-58
[30]翁史俊.中央空调系统的自动控制设计和节能思路探讨[J].工程设计CAD与智能建筑2001(6):18-22
[31]曹秋声.新型中央空调节能控制系统研究[J].节能 2005(6):31-34
[32]Braun R D,ICroo I M.Development and application of the collaborative optimization architecture in a multidisciplinary design environment[C].International Congress on Industrial and Applied Mathematics,Hamburg,Germany,1995
[33]Fong Kwong Fai,Hanby Victor Ian,Chow Tin Tai.A robust evolutionary algorithm for HVAC engineering optimization[J]HVAC and R Research,v 14,n 5,September,2008,p 683-705
[34]Komareji M.Stoustrup J.Rasmussen H.Bidstrup,N.Svendsen P.Nielsen F.Optimal set-point synthesis in HVAC systems[C].Proceedings of the American Control Conference,Proceedings of the 2007 American Control Conference,ACC,2007,p 5076-5081
[35]Jin Guang-Yu,Cai Wen-Jian,Lu Lu,Lee Eng Lock,Chiang Andrew A simplified modeling of mechanical cooling tower for control and optimization of HVAC systems[J].Energy Conversion and Management,v 48,n 2,February,2007,p 355-365
[36]Komareji,Stoustrup,Rasmussen,idstrup,Svendsen,Nielsen,Optimal model-based control in HVAC systems[C].Proceedings of the American Control Conference,2008 American Control Conference,ACC,2008,p 1443-1448
[37]Yao-Wen Wang,Wen-Jian Cai,Yeng-Chai Soh,Shu-Jiang Li,Lu Lu &Lihua Xie.A simplified modeling of cooling coils for control and optimization of HVAC Systems[J].Energy Conversion & Management 2004.Volume 48.Issue 18-19,pp.2915-2930
[38]司小雷.我国的建筑能耗现状及解决对策[J].建筑节能,2008,36(2):71-74.
[39]刘金平,卖粤帮,刘雪峰.中央空调系统变水温利变水量协调优化控制研究[J].建筑科学,2007年06期
[40]Wen-Jian Cai,Guang-Yu Jin,Lu Lu,Eng Lock Lee,Chiang,A.A simplified modeling of mechanical cooling tower for control and optimization of HVAC systems Energy Conversion and Management,v 48,n 2,Feb.2007,p 355-65
[41]Shaoyuan Li,Min Xu,Wen-jian Cai,Lu Lu.Effects of a GPC-PID control strategy with hierarchical structure for a cooling coil unit Energy Conversion and Management,v 47,n 1,Jan.2006,p 132-45
[42]侯捷.WIN32多线程程序设计.武汉:华中科技大学出版社 2002(02)
[43]JEFFREY RICH.WINDOWS高级编程指南(第三版).北京:清华大学出版社 1999(06)
[2]Braun James E.A general control algorithm for cooling towers in cooling plants with electric and/or gas-driven chillers[J].HVAC and R Research,2007,v13,n 4,pp 581-598
[3]Kirsner W.Designing for chilled water supply temperature-does it save energy[J].ASHRAE J,1998,40(1):37-42
[4]Chu Chimin,Jong Tailang,Huang Yue wei.A study of thermal comfort control using least enthalpy estimator on HVAC system[C]American Control Conference,2005
[5]Nassif,N.Evolutionary algorithms for multi-objective optimization in HVAC system control strategy[C].Montreal:IEEE Annual Meeting,2004
[6]Lu Lu,Cai Wenjian,Xie Lihua,Li Shujiang.HVAC system optimization-In-building section[J].Energy and Buildings,v 37,n1,January,2005,p 11-22
[7]Jian Sun & Agami Reddy.Optimal control of building HVAC&R systems using complete simulation-based sequential quadratic programming(CSB-SQP)[J].Building & Environment.2005.Volume 40.Issue 5,pp.657-669
[8]Xue-Cheng Xi'Aun-Neow Poo & Siaw-Kiang Chou.Support Vector Regression Model Predictive Control On a HVAC Plant[J].Control Engineering Practice,2007.Volume 15.Issue 8,pp.897-908
[9]S.A.K.Al-Assadi,M.Zaheer-uddin Robust decentralized control of HVAC systems using H_∞-performance measures[J].Journal of the Franklin Institute 2005.Volume 341.Issue 7,pp.543-569
[10]Ming He,Wen-Jian Cai & Shao-Yuan Li.Multiple fuzzy model-based temperature predictive control for HVAC systems[J].Information Sciences 2005.Volume 169.Issue 1-2,pp.155-174
[11]Yao-Wen Wang,Wen-Jian Cai,Yeng-Chai Soh,Shu-Jiang Li,Lu Lu &Lihua Xie.A simplified modeling of cooling coils for control and optimization of HVAC Systems[J].Energy Conversion & Management 2004.Volume 48.Issue 18-19,pp.2915-2930
[12]Fong K F,Hanby V I.HVAC system optimization for energy management by evolutionary programming[J].Energy and Buildings,2006,38(3):220-231
[13]Chu Chimin,Jong Tailang,Huang Yue wei.A study of thermal comfort control using least enthalpy estimator on HVAC system[C]American Control Conference,2005
[14]Timothy I.Salsbury.A new pulse modulation adaptive controller(PMAC) applied to HVAC systems[J].Control Engineering Practice,2002.Volume 10.Issue 12,pp.1357-1370
[15]Song Q,Hu W J,Zhao T N.Robust neural network controller for variable airflow volume system[C]Control Theory and Application,IEEE Proceedings,2003,150(2):112-118
[16]Semsar E,Yazdanpanah M J,Lucas C.Nonlinear control and disturbance decoupling of an HVAC system via feedback linearization and back-stepping[C]Proceedings of 2003 IEEE Conference,2003
[17]W.Huang and H.N.Lam.Using genetic algorithms to optimize controller parameters for HVAC systems[J].Energy and Buildings 1997.Volume 26.Issue 3,pp.277-282
[18]孟华,龙惟定,王盛卫.基于遗传算法的空调水系统优化控制研究[J].建筑节能,2007
[19]晋欣桥 夏清 陈刚 王盛卫 变风量空调系统中的实时优化节能控制 节能 1999
[20]徐新华 王盛卫 多区域变风量空调系统优化控制研究 建筑热能通风空调 2006
[21]王军、王雁、邵惠鹤等 一种优化控制变风量空调系统的新方法 上海交通大学学报,2006,(02).
[22]晋欣桥:孙金龙:杜志敏 变风量空调系统中基于预测的末端再热控制策略 上海交通大学学报,2006,(02)
[23]孟华、王盛卫、龙惟定 空调水系统实时在线优化控制预测模型的研究 同济大学学报2006(05)
[24]张韵辉,吕震中,张小松.冷水机组的优化运行[J].暖通空调,2004,(07)
[25]曹双华,曹家枞.基于小波变换的神经网络空调负荷预测研究[J].暖通空调 2005,(04)
[26]林星春,曹家枞,马素贞.神经网络法及其在暖通空调负荷预测中的应用[J].制冷与空调2007
[27]施志钢.应用神经元自适应PSD控制变频空调系统的仿真研究[J].暖通空调 2006
[28]白建波.空调系统的鲁棒PI控制[C]东南大学动力工程系 2005
[29]江亿.暖通空调系统的计算机控制管理[J].暖通空调 1997,27(3):45-58
[30]翁史俊.中央空调系统的自动控制设计和节能思路探讨[J].工程设计CAD与智能建筑2001(6):18-22
[31]曹秋声.新型中央空调节能控制系统研究[J].节能 2005(6):31-34
[32]Braun R D,ICroo I M.Development and application of the collaborative optimization architecture in a multidisciplinary design environment[C].International Congress on Industrial and Applied Mathematics,Hamburg,Germany,1995
[33]Fong Kwong Fai,Hanby Victor Ian,Chow Tin Tai.A robust evolutionary algorithm for HVAC engineering optimization[J]HVAC and R Research,v 14,n 5,September,2008,p 683-705
[34]Komareji M.Stoustrup J.Rasmussen H.Bidstrup,N.Svendsen P.Nielsen F.Optimal set-point synthesis in HVAC systems[C].Proceedings of the American Control Conference,Proceedings of the 2007 American Control Conference,ACC,2007,p 5076-5081
[35]Jin Guang-Yu,Cai Wen-Jian,Lu Lu,Lee Eng Lock,Chiang Andrew A simplified modeling of mechanical cooling tower for control and optimization of HVAC systems[J].Energy Conversion and Management,v 48,n 2,February,2007,p 355-365
[36]Komareji,Stoustrup,Rasmussen,idstrup,Svendsen,Nielsen,Optimal model-based control in HVAC systems[C].Proceedings of the American Control Conference,2008 American Control Conference,ACC,2008,p 1443-1448
[37]Yao-Wen Wang,Wen-Jian Cai,Yeng-Chai Soh,Shu-Jiang Li,Lu Lu &Lihua Xie.A simplified modeling of cooling coils for control and optimization of HVAC Systems[J].Energy Conversion & Management 2004.Volume 48.Issue 18-19,pp.2915-2930
[38]司小雷.我国的建筑能耗现状及解决对策[J].建筑节能,2008,36(2):71-74.
[39]刘金平,卖粤帮,刘雪峰.中央空调系统变水温利变水量协调优化控制研究[J].建筑科学,2007年06期
[40]Wen-Jian Cai,Guang-Yu Jin,Lu Lu,Eng Lock Lee,Chiang,A.A simplified modeling of mechanical cooling tower for control and optimization of HVAC systems Energy Conversion and Management,v 48,n 2,Feb.2007,p 355-65
[41]Shaoyuan Li,Min Xu,Wen-jian Cai,Lu Lu.Effects of a GPC-PID control strategy with hierarchical structure for a cooling coil unit Energy Conversion and Management,v 47,n 1,Jan.2006,p 132-45
[42]侯捷.WIN32多线程程序设计.武汉:华中科技大学出版社 2002(02)
[43]JEFFREY RICH.WINDOWS高级编程指南(第三版).北京:清华大学出版社 1999(06)