区域供冷系统节能优化运行与控制方法研究及系统实现
|
摘要
节约能源、提高能源使用效率是我国的基本国策。随着我国经济和城市化进程的快速发展，建筑能耗呈逐年上扬趋势，建筑节能意义重大。在建筑能耗中，空调能耗占有相当大的比重，是建筑节能的重点。
近年来，随着城市大型商业建筑群、CBD核心区、大学城等区域建筑群的不断涌现，区域供冷系统开始得到广泛应用。与传统中央空调系统相比，区域供冷系统具有能源综合利用效率高，可有效改善区域建筑热环境，环境友好，与冰蓄冷结合可实现移峰填谷提高电厂及电网效率等优点，是未来区域建筑群空调系统的发展方向。但是，由于区域供冷系统冷负荷大、规模大、设备数量多、系统复杂，其运行优化与控制技术水平是决定区域供冷系统运行能效高低以及节能优势能否发挥的关键。
区域供冷系统运行能效对系统运行费用、区域内高峰用电负荷与环境有较大影响。本文综合考虑区域供冷系统整体能耗、运行能效以及热舒适性三方面因素，初步探索了区域供冷系统能效综合评价方法与指标；提出了区域供冷系统运行能效的在线监测方法，设计了相应的在线监测系统，并对其需要监测的参数、监测设备及其精度、测点布置等进行了阐述。
本文针对区域供冷系统冷量输送过程滞后时间较长的特征，提出冷量精确调节控制模型，以实现区域供冷控制节能。以二级冷量交换站板式换热器一次侧量调节、二次侧质调节的冷量调节方法为例，分析了二级冷量交换站一次侧冷冻水流量对空调末端设备送风温度与空调房间平均温度的影响，建立了建筑物空调房间室内平均温度的控制模型；提出了模糊PID控制器的设计方法，解决了区域供冷系统这类大时滞、参数不确定的惯性系统采用常规PID控制方法难以获得预期控制效果的问题。
本文分析了供冷距离长、有时滞特性、冷量传递过程复杂的区域供冷系统的特征特性，发现区域供冷系统从区域供冷站到建筑物再到空调房间的冷量输送动态过程及其时滞特性；研究了空调房间冷负荷随室外气象参数的变化规律，建立了区域供冷系统冷量输送动态过程中冷量输送与冷量波动方程、区域供冷系统冷负荷增量模型，为实现系统的节能优化运行提供依据。
区域供冷系统依据设计工况确定设备的额定容量，部分负荷工况以及各建筑用冷特性的差异必然造成系统设备的容量冗余，运行调节与控制技术的不完善势必造成部分负荷下系统能效不高、能耗过大、用冷浪费等问题。针对这些问题，本文在区域供冷系统各类设备能耗模型的基础上，以系统能效最高为目标，建立了系统运行能耗优化模型，并提出了相应的求解方法及系统优化运行与控制的实现，为用户节省冷量费用支出20%以上。
最后，本文设计了节能控制系统的总体框架及其各组成部分的软件平台和硬件结构，开发了相应的软、硬件平台，研制出相应的节能优化控制系统。节能控制系统先后在区域供冷广州大学城华南理工大学、广东药学院、广东外语外贸大学、华南师范大学、广州美术学院、广州中医药大学等学校投入使用，节能效果良好。经第三方节能测试，系统可为用户节省冷量费用支出20%-40%。
The nation has pinned its basic policy that aims to encourage energy saving andimprove energy efficiency. With the rapid development of domestic economy andurbanization, recent years has witnessed a considerable growth in energy consumption inthe field of construction, and thus energy saving is in the meantime greatly motivated.Among all the sources, air-conditioning devices are listed on top of the list in terms of theamount of energy consumption. Therefore, it is critically important to impose an effectivecontrol over air conditioning systems.
Due to the recent fast emergence of large-scale commercial buildings, CBD core areas,and University Mega Town, the District Cooling Systems (DCS) have been launched invarious applications. Compared to the traditional central air-conditioning systems, the DCSis the future direction for district buildings, largely thanks to its advantages such as highenergy efficiency, being capable of improving the thermal environment of the districtbuildings, environmental friendliness, and being economically maintainable. However, theDCS, with the characteristics of heavy cooling load, large scale, multiple devices, and highcomplexity, has to meet the high standards of operational optimization and adapt to the highlevel of control technology in order to maximize its performance and well combine theoperation with energy-efficient results.
The operational efficiency of the system will considerably influence the maximumelectricity load within the region and has major impact to the environment; besides, theoperational cost of the system is subject to the level of the detected efficiency. Taking intoconsideration three factors, namely the overall energy consumption of the DCS, theoperational energy efficiency and the thermal comfort, this thesis has explored thecomprehensive assessment method and index system for the energy efficiency of the DCS,and designed the online monitoring system that aims to trace in detail the accurate values ofoperational efficiency of the system, and elaborated the parameters that have to bemonitored, the monitoring equipment and its accuracy, and the spots to be allocated for monitoring.
In order to addressed the issues of long delay and lack of a reasonable model foraccurate cold supply controlling, the author has introduced the initial quantity prioritizedadjustment and the secondary quality prioritized adjustment made by the plate heatexchanger of the secondary cold supply exchange station as a typical example forillustration. On the basis of such an empirical exemplification, the author further studied thefluctuations of the air-supplying temperature from the end equipment of the air conditionerand the average temperature of the air-conditioned room, both influenced by the quantity ofcold water flow through the secondary cold supply exchange station. Then, the author hasalso set up the controlling model of the indoor average temperature in the air-conditionedrooms of the construction, and proposed a method to design the fuzzy PID controller. As aresult, it is able to overcome the deficiency of utilizing the conventional PID controller andeven achieve an anticipated control over the inertial systems with significant time delay anduncertain parameters.
DCS involves long-distance and delayed transport, and a complicated process of coldsupply. This thesis analysed the time-delay characteristic of the system and the dynamicprocess of cold supply that starts from the regional cold supply station, then to theconstructions and eventually to the air-conditioned rooms. To serve the practical goal ofmaintaining the comfort in the air-conditioned rooms, also investigated is the principles onhow the cooling load in air-conditioned rooms varies with respect to the outdoormeteorological parameters. Based on this, the thesis established the equation oftransportation and variation of cool supply, the dynamic equation of the variation of indoortemperature and relative humidity in air-conditioned rooms, as well as the incrementalmodel of the cooling load in air-conditioned rooms, providing a crucial basis for anenergy-efficient system with optimized operations.
The nominal capacity of the equipment is determined based on the design condition ofthe project. However, the partial load condition and the disparities of cold supply amongdifferent constructions will definitely result in redundancy in the system capacity. Moreover, the imperfect technologies for operation regulation and control will definitely lead to lowsystem efficiency, excessive energy consumption and the waste of cold supply under certainloads of the system. With the consideration of the above mentioned issues and on the basisof the energy consumption models of various types of equipment that serves the system, theauthor established the optimal operation model on energy consumption, and proposedcorresponding solutions and the overall procedure for optimal operation and control, inorder to maximize the energy efficiency of the system. This approach saves over20%expenses on cold energy.
In the end, the author proposed the general framework of District Cooling System forEnergy Efficiency, as well as the software platform and hardware structure for eachcomponent. Moreover, the author also developed the corresponding platform for bothsoftware and hardware. Several sub-systems were already applied to a University MegaTown, such as South China University of Technology, Guangdong PharmaceuticalUniversity, Guangdong University of Foreign Studies, South China Normal University andGuangzhou Univeristy of Chinese Medicine, with promising energy-saving performanceachieved. After the Third-Party Testing on energy-saving, it demonstrates our system is ableto save20%-40%expenses on cold energy.
近年来，随着城市大型商业建筑群、CBD核心区、大学城等区域建筑群的不断涌现，区域供冷系统开始得到广泛应用。与传统中央空调系统相比，区域供冷系统具有能源综合利用效率高，可有效改善区域建筑热环境，环境友好，与冰蓄冷结合可实现移峰填谷提高电厂及电网效率等优点，是未来区域建筑群空调系统的发展方向。但是，由于区域供冷系统冷负荷大、规模大、设备数量多、系统复杂，其运行优化与控制技术水平是决定区域供冷系统运行能效高低以及节能优势能否发挥的关键。
区域供冷系统运行能效对系统运行费用、区域内高峰用电负荷与环境有较大影响。本文综合考虑区域供冷系统整体能耗、运行能效以及热舒适性三方面因素，初步探索了区域供冷系统能效综合评价方法与指标；提出了区域供冷系统运行能效的在线监测方法，设计了相应的在线监测系统，并对其需要监测的参数、监测设备及其精度、测点布置等进行了阐述。
本文针对区域供冷系统冷量输送过程滞后时间较长的特征，提出冷量精确调节控制模型，以实现区域供冷控制节能。以二级冷量交换站板式换热器一次侧量调节、二次侧质调节的冷量调节方法为例，分析了二级冷量交换站一次侧冷冻水流量对空调末端设备送风温度与空调房间平均温度的影响，建立了建筑物空调房间室内平均温度的控制模型；提出了模糊PID控制器的设计方法，解决了区域供冷系统这类大时滞、参数不确定的惯性系统采用常规PID控制方法难以获得预期控制效果的问题。
本文分析了供冷距离长、有时滞特性、冷量传递过程复杂的区域供冷系统的特征特性，发现区域供冷系统从区域供冷站到建筑物再到空调房间的冷量输送动态过程及其时滞特性；研究了空调房间冷负荷随室外气象参数的变化规律，建立了区域供冷系统冷量输送动态过程中冷量输送与冷量波动方程、区域供冷系统冷负荷增量模型，为实现系统的节能优化运行提供依据。
区域供冷系统依据设计工况确定设备的额定容量，部分负荷工况以及各建筑用冷特性的差异必然造成系统设备的容量冗余，运行调节与控制技术的不完善势必造成部分负荷下系统能效不高、能耗过大、用冷浪费等问题。针对这些问题，本文在区域供冷系统各类设备能耗模型的基础上，以系统能效最高为目标，建立了系统运行能耗优化模型，并提出了相应的求解方法及系统优化运行与控制的实现，为用户节省冷量费用支出20%以上。
最后，本文设计了节能控制系统的总体框架及其各组成部分的软件平台和硬件结构，开发了相应的软、硬件平台，研制出相应的节能优化控制系统。节能控制系统先后在区域供冷广州大学城华南理工大学、广东药学院、广东外语外贸大学、华南师范大学、广州美术学院、广州中医药大学等学校投入使用，节能效果良好。经第三方节能测试，系统可为用户节省冷量费用支出20%-40%。
The nation has pinned its basic policy that aims to encourage energy saving andimprove energy efficiency. With the rapid development of domestic economy andurbanization, recent years has witnessed a considerable growth in energy consumption inthe field of construction, and thus energy saving is in the meantime greatly motivated.Among all the sources, air-conditioning devices are listed on top of the list in terms of theamount of energy consumption. Therefore, it is critically important to impose an effectivecontrol over air conditioning systems.
Due to the recent fast emergence of large-scale commercial buildings, CBD core areas,and University Mega Town, the District Cooling Systems (DCS) have been launched invarious applications. Compared to the traditional central air-conditioning systems, the DCSis the future direction for district buildings, largely thanks to its advantages such as highenergy efficiency, being capable of improving the thermal environment of the districtbuildings, environmental friendliness, and being economically maintainable. However, theDCS, with the characteristics of heavy cooling load, large scale, multiple devices, and highcomplexity, has to meet the high standards of operational optimization and adapt to the highlevel of control technology in order to maximize its performance and well combine theoperation with energy-efficient results.
The operational efficiency of the system will considerably influence the maximumelectricity load within the region and has major impact to the environment; besides, theoperational cost of the system is subject to the level of the detected efficiency. Taking intoconsideration three factors, namely the overall energy consumption of the DCS, theoperational energy efficiency and the thermal comfort, this thesis has explored thecomprehensive assessment method and index system for the energy efficiency of the DCS,and designed the online monitoring system that aims to trace in detail the accurate values ofoperational efficiency of the system, and elaborated the parameters that have to bemonitored, the monitoring equipment and its accuracy, and the spots to be allocated for monitoring.
In order to addressed the issues of long delay and lack of a reasonable model foraccurate cold supply controlling, the author has introduced the initial quantity prioritizedadjustment and the secondary quality prioritized adjustment made by the plate heatexchanger of the secondary cold supply exchange station as a typical example forillustration. On the basis of such an empirical exemplification, the author further studied thefluctuations of the air-supplying temperature from the end equipment of the air conditionerand the average temperature of the air-conditioned room, both influenced by the quantity ofcold water flow through the secondary cold supply exchange station. Then, the author hasalso set up the controlling model of the indoor average temperature in the air-conditionedrooms of the construction, and proposed a method to design the fuzzy PID controller. As aresult, it is able to overcome the deficiency of utilizing the conventional PID controller andeven achieve an anticipated control over the inertial systems with significant time delay anduncertain parameters.
DCS involves long-distance and delayed transport, and a complicated process of coldsupply. This thesis analysed the time-delay characteristic of the system and the dynamicprocess of cold supply that starts from the regional cold supply station, then to theconstructions and eventually to the air-conditioned rooms. To serve the practical goal ofmaintaining the comfort in the air-conditioned rooms, also investigated is the principles onhow the cooling load in air-conditioned rooms varies with respect to the outdoormeteorological parameters. Based on this, the thesis established the equation oftransportation and variation of cool supply, the dynamic equation of the variation of indoortemperature and relative humidity in air-conditioned rooms, as well as the incrementalmodel of the cooling load in air-conditioned rooms, providing a crucial basis for anenergy-efficient system with optimized operations.
The nominal capacity of the equipment is determined based on the design condition ofthe project. However, the partial load condition and the disparities of cold supply amongdifferent constructions will definitely result in redundancy in the system capacity. Moreover, the imperfect technologies for operation regulation and control will definitely lead to lowsystem efficiency, excessive energy consumption and the waste of cold supply under certainloads of the system. With the consideration of the above mentioned issues and on the basisof the energy consumption models of various types of equipment that serves the system, theauthor established the optimal operation model on energy consumption, and proposedcorresponding solutions and the overall procedure for optimal operation and control, inorder to maximize the energy efficiency of the system. This approach saves over20%expenses on cold energy.
In the end, the author proposed the general framework of District Cooling System forEnergy Efficiency, as well as the software platform and hardware structure for eachcomponent. Moreover, the author also developed the corresponding platform for bothsoftware and hardware. Several sub-systems were already applied to a University MegaTown, such as South China University of Technology, Guangdong PharmaceuticalUniversity, Guangdong University of Foreign Studies, South China Normal University andGuangzhou Univeristy of Chinese Medicine, with promising energy-saving performanceachieved. After the Third-Party Testing on energy-saving, it demonstrates our system is ableto save20%-40%expenses on cold energy.
引文
[1]中华人民共和国国家统计局.国民经济和社会发展统计公报[R].北京:中华人民共和国国家统计局,2010
[2]江亿.2008年中国建筑能耗年度报告[M].北京:中国建筑工业出版社,2008
[3]惠荣娜,徐奇,李德英,等.我国区域供冷的现状及发展[J].建筑节能,2007,35(03):47-50
[4]马宏权,龙惟定.区域供冷系统的应用现状与展望[J].暖通空调,2009,39(10):52-58
[5]瑞典经商参处.瑞典环境技术产业及企业情况简介[S]，2010.
[6]日本熱供給事業協會.熱供給事業便覽[M].東京:日本熱供給事業協會,2005
[7]王刚.瑞典区域供冷技术对中国的启示[J].建筑热能通风空调,2004,23(03):24-29
[8]马一太,刘秋菊,刘圣春.空调能效比发展趋势的研究[J].制冷与空调,2007,7(03):10-13
[9]GB19577-2004,冷水机组能效限定值及能源效率等级[S].北京:中国标准出版社,2004
[10]GB50189-2005,公共建筑节能设计规范[S].北京:中国建筑工业出版社,2005
[11]GB12021.3-2004,房间空气调节器能源效率限定值及能效等级[S].北京:中国标准出版社,2004
[12]GB19576-2004,单元式空气调节机能效限定值及能源效率等级[S].北京:中国标准出版社,2004
[13]GB/T18430.1-2001,蒸汽压缩循环冷水(热泵)机组工商业用和类似用途的冷水(热泵)机组[S].北京:中国标准出版社,2001
[14]郭红军.公共建筑空调系统设计综合能效比计算方法的研究[D].重庆:重庆大学,2010
[15]杨李宁.公共建筑空调工程能效比的研究[D].重庆:重庆大学,2007
[16]刘轶.对建筑空调系统设计能效比的初步计算分析[J].暖通空调,2006,36(08):50-52
[17]肖益民,付祥钊,杨李宁,等.重庆市商场类建筑空调工程设计能效比统计分析[J].暖通空调,2007,37(08):130-134
[18]林真国,张素云,付祥钊,等.重庆市酒店类建筑空调工程设计能效比调研[J].暖通空调,2009,39(02):27-30,104
[19]黄伟,刘谨,李继路.关于空调冷冻水输送能效比计算的一点看法[J].制冷,2009,28(01):86-87
[20]龚明启,冀兆良,宋玮.水环热泵型空调系统设计及工程实例分析[J].制冷,2005,24(03):46-52
[21]赖雪梅.中央空调系统全年运行能效分析[M].北京:北京工业大学,2007
[22]CaglarSelcuk Canbaya,Arif, H.,Gulden, G. Evaluating performance indices of a shopping centre andimplementing HVAC control principles to minimize energy usage[J]. Energy and Buildings,2004,36(6):587-598
[23]GB/T17981-2007,空气调节系统经济运行[S].北京:中国标准出版社,2007
[24]文韬.空调工程运行能效检测理论与方法[D].重庆:重庆大学,2008
[25]林建泉.小型过冷式冰蓄冷多联空调系统的运行优化控制策略研究[D].武汉:华中科技大学,2009
[26]Zimmer, H. Chiller control using on-line allocation for energy conservation[R]. Houston, TX, USA:Adv Instrum,1976
[27]Chun, C.,Norden, N. Computer optimization of refrigeration systems in a textile plant: a case history[J].Automation,1982,18(6):675-683
[28]Enterline, L.,Sommer, A.,Kaya, A. Chiller optimization by distributed control to save energy[J]. ISATransactions,1984,23(2):1137-1149
[29]Lau, A.,Beckman, W. Development of computerized control strategies for a large chilled water plant[J].ASHRAE Trans,1985,91(2):766-780
[30]Braun, J.E.,Klein, S.A.,Mitchell, J.W. Methodologies for optimal control to chilled water systemswithout storage[J]. ASHRAE Trans,1989,95(1):652-662
[31]Olson, R.T. A dynamic procedure for the optimal sequencing of plant equipment plant II: validationand sensitivity analysis[J]. Engineering Optimization,1994,22(3):163-183
[32]Curtiss, P.S. Artificial neural networks for use in building systems control and energy management[D].Colorado: University of Colorado-Boulder,1992
[33]Austin, S.B. Chilled water system optimization[J]. ASHRAE,1993,35(7):50-56
[34]Lam, J.C. Regression analysis of high-rise fully air-conditioned office buildings[J]. Energy andBuildings,1997,26(2):189-197
[35]Ahn, B.C.,Mitchell, J.W. Optimal control development for chilled water plants using a quadraticrepresentation[J]. Energy and Buildings,2001,33(4):371-378
[36]Wang, S.,John, B. Online adaptive control for optimizing variable-speed pumps of indirectwater-cooled chilling systems[J]. Applied Thermal Engineering,2001,21(11):1083-1103
[37]晋欣桥.变风量空调系统的仿真及其实时优化控制研究[D].上海:上海交通大学,1999
[38]Lu, L.,Cai, W.,Yeng, C., et al. HVAC system optimization—condenser water loop[J]. EnergyConversion and Management,2004,45(4):613-630
[39]Chang, Y.,Lin, J.,Chuang, M. Optimal chiller loading by genetic algorithm for reducing energyconsumption[J]. Energy and Buildings,2005,37(2):147-155
[40]孟华,龙惟定,王盛卫.集中空调冷却水侧上位机控制器的实时控制[J].同济大学学报(自然科学版),2005,33(3):380-384
[41]杨文辉.公共建筑空调系统综合节能运行模式研究[D].重庆:重庆大学,2008
[42]Spethemann, D.H. Optimal Control for Cool Storage[J]. ASHRAR Transactions,1989,95(1):1189-1193
[43]Braun, J.E. A comparison of chiller-priority, storage-priority, and optimal control of an ice-storagesystem[J]. ASHRAE Transactions,1992,98(1):893-902
[44]Simmonds, P. Comparison of Energy Consumption for Storage-Priority and Chiller-Priority forIce-Based Thermal Storage Systems[J]. ASHRAE Transactions,1994,100(1):1746-1753
[45]Kintner-Meyer, M.,Emery, A.F. Optimal control of an HVAC system using cold storage and buildingthermal capacitance[J]. energy and buildings,1995,23(1):19-31
[46]Henze, G. Evaluation of optimal control for active and passive building thermal storage[J].International Journal of Thermal Sciences,2004,43(2):173-183
[47]Murai, M.,Sakamoto, Y.,Shinozaki, T. Optimizing control for district heating and cooling plant[A].IEEE Conference on Control Application–Proceedings[C]. IEEE,1999:600-604
[48]Sakamoto, Y.,Nagaiwa, A.,Kobayasi, S., et al. An optimization method of district heating and coolingplant operation based on genetic algorithm[J]. ASHRAE Transactions,1999,105(part A):104-115
[49]陈晓,张国强,文进希.区域供冷系统中制冷机系统的优化配置探讨[J].流体机械,2003,31(06):55-61
[50]闫军威,刘飞龙,朱冬生,等.广州大学城区域供冷系统质调节的节能分析[J].建筑科学,2007,23(12):27-29,34
[51]Chan, A.L.S.,Tin-Tai, C.,Square, K.F.F., et al. Performanceevaluation of districtcoolingplant withicestorage[J]. Energy,2006,31(14):2750-2762
[52]GB/T18430.1-2007,蒸气压缩循环冷水(热泵)机组第1部分：工业或商业用及类似用途的冷水(热泵)机组[S].北京:中国标准出版社,2007
[53]陆耀庆.暖通空调设计指南[M].北京:中国建筑工业出版社,1996
[54]ASHRAE. ASHRAE Handbook2008: HVAC systems and equipment[M]. Atlanta: ASHRAE Inc,2008
[55]ASHRAE. ASHRAE Handbook Fundamentals[M]. Atlanta: American Soeiety of Heating,2005
[56]GBJ15-51-2007,公共建筑节能设计标准广东省实施细则[S].北京:中国建筑工业出版社,2007
[57]李运华.大型公共建筑运行能耗测试、评价与数据库管理系统开发[D].哈尔滨:哈尔滨工业大学,2006
[58]刘洋.大型公共建筑空调系统能效监测、诊断与性能优化探讨[D].哈尔滨:哈尔滨工业大学,2006
[59]余晓平,付祥钊,杨李宁,等.重庆市办公建筑空调工程设计能效比统计分析[J].暖通空调,2007,37(12):41-45
[60]余晓平,付祥钊,肖益民.既有公共建筑空调工程能效诊断方法问题探讨[J].暖通空调,2010,40(02):33-38
[61]闵晓丹,戎向阳.公共建筑空调冷源系统季节能效比研究[J].暖通空调,2010,40(11):63-67
[62]陈超,渡边俊行,谢光亚,等.日本的建筑节能概念与政策[J].暖通空调,2002,32(06):40-43
[63]闵晓丹.公共建筑空调系统运行能效比分析和优化[D].重庆:重庆大学,2008
[64]陈万仁,王保东.热泵与中央空调节能技术[M].北京:化学工业出版社,2010
[65]薛志峰,江亿.商业建筑的空调系统能耗指标分析[J].暖通空调,2005,35(01):37-41
[66]ANSI/ASHRAE55-1992, Thermal environmental conditions for human occupancy[S]. Atlanta:American Soeiety of Heating,1992
[67]王昭俊,赵加宁,刘京.室内空气环境[M].北京:化学工业出版社,2006
[68]朱立.空气调节技术[M].北京:高等教育出版社,2008
[69]唐鑫.中央空调冷冻水系统一种智能控制方式的研究[D].重庆:重庆大学,2009
[70]林利瓦,徐小勇,张军,等.中央空调变流量PLC控制系统设计[J].自动化仪表,2009,30(09):56-59
[71]郭阳宽,王正林.过程控制系统仿真[M].北京:电子工业出版社,2009
[72]康英姿,左政.区域供冷系统二次管网的冷量损失分析[J].暖通空调,2009,39(11):31-36
[73]贾晶.供冷管道与设备保冷计算和分析[D].哈尔滨:哈尔滨工业大学,2006
[74]赵哲身,何方毅.公共建筑楼宇控制系统能耗监测和节能分析[J].建设科技,2008,(09):36-38
[75]彦启森,石文星,田长青.空气调节用制冷技术[M].北京:中国建筑工业出版社,2004
[76]马宏权,龙惟定.区域供冷系统的能源效率[J].暖通空调,2008,38(11):59-64,40
[77]谭福太.广州大学城区域供冷系统的节能优化[J].节能技术,2009,27(04):371-374
[78]胡寿松.自动控制原理[M].北京:科学出版社,2007
[79]Astrom, K.J.,Hagglund, T. PID controllers: theory, design, and tuning[M].2nd ed. Research TrianglePark, NC: Instrument Society of America,1995
[80]Glickman, S.,Nudelman, G.,Kulessky, R. Identification-based PID control tuning for power stationprocesses[J]. IEEE Trans. on Control SystemsTechnology,2004,12(1):123-132
[81]Kosko, B. Neural networks and fuzzy systems[M]. Prentice: Prentice hail,1993
[82]丁坚.模糊PID控制器的研究[D].哈尔滨:哈尔滨工程大学,2009
[83]Tanaka, K.,Michio, S. Stabilityanalysis and design of fuzzycontrolsystems[J]. Fuzzy Sets and Systems,1992,45(2):135-156
[84]李先峰,杨国华,李建春.基于模糊PID的电阻炉温度控制器的设计与仿真研究[J].微型机与应用,2010,29(10):81-83
[85]丁坚.模糊PID控制器的研究[D].哈尔滨:哈尔滨工程大学,2009
[86]李卷兴,样石中,陆倩倩.变体积空气调节系统的自适应模糊-PID温度控制器[J].,2010,(6):20-23
[87]Curtiss, P.S. Artificial neural networks for use in building systems control and energy management[D].Colorado: University of Colorado-Boulder,1992
[88]何厚键.中央空调水系统的建模与优化研究[D].沈阳:沈阳工业大学,2005
[89]徐庆伟.智能大厦中央空调优化运行与节能管理[D].北京:北京理工大学,2001
[90]胥海伦.空调水系统变流量运行管理的节能措施[D].成都:西南交通大学,2002
[91]朱孟标.空调水系统节能研究[D].南京:南京理工大学,2003
[92]李玉云.中央空调水系统节能技术措施的探讨[J].节能,2003,(02):12-16
[93]晋欣桥,李晓锋,惠广海,等.中央空调水系统控制的优化分析[J].系统仿真学报,2003,15(08):1113-1115
[94]孟华,龙惟定,王盛卫.中央空调水系统优化控制研究的发展及现状[J].建筑热能通风空调,2002,(06):29-32
[95]Bernier, M.A.,Bernard, B. Pumping energy and Variable frequency drives[J]. ASHRAE Journal,1999,41(12):37-40
[96]清华大学Dest开发组.建筑环境系统模拟分析方法—Dest[S].北京:中国建筑工业出版社，2006.
[97]ASHRAE. ASHRAE applications handbook[M]. Atlanta: ASHRAE,1999
[98]康英姿.区域供冷系统集成建模与优化设计[D].广州:华南理工大学,2008
[99]孟华.集中空调水系统的仿真及上位机控制器的实时优化控制研究[D].上海:同济大学,2004
[100]颜永民.建筑冷热源系统自适应优化控制模型的研究[D].长沙:湖南大学,2004
[101]高自友.现代物流与交通运输:模型与方法[S].北京:人民交通出版社，2005.
[102]尹洪超,施光燕,于福东.过程综合混合整数非线性规划的罚函数-凑整算法[J].大连理工大学学报,1997,37(1):49-52
[103]罗向龙,华贲,张冰剑.基于管网模拟的蒸汽动力系统多周期运行优化[J].石油学报（石油化工）,2006,22(5):56-62
[104]Sakawa, M.,Matsui, T. Fuzzy multiobjective nonlinear operation planning in district heating andcooling plants[J]. Fuzzy Sets and Systems,2011, doi:10.1016/j.fss.2011.10.020
[105]茅艳.人体热舒适气候适应性研究[D].:西安建筑科技大学,2007
[106]GB50019-2003,采暖通风与空气调节设计规范[S].北京:2004
[107]薜殿华.空气调节[M].北京:清华大学出版社,2004
[108]龚明启.中央空调系统动态运行节能优化策略研究[D].广州:广州大学,2006
[109]刘传瑞.基于ZigBee和地磁传感器的新型无线交通监控系统的研究与实[D].成都:电子科技大学,2011
[2]江亿.2008年中国建筑能耗年度报告[M].北京:中国建筑工业出版社,2008
[3]惠荣娜,徐奇,李德英,等.我国区域供冷的现状及发展[J].建筑节能,2007,35(03):47-50
[4]马宏权,龙惟定.区域供冷系统的应用现状与展望[J].暖通空调,2009,39(10):52-58
[5]瑞典经商参处.瑞典环境技术产业及企业情况简介[S]，2010.
[6]日本熱供給事業協會.熱供給事業便覽[M].東京:日本熱供給事業協會,2005
[7]王刚.瑞典区域供冷技术对中国的启示[J].建筑热能通风空调,2004,23(03):24-29
[8]马一太,刘秋菊,刘圣春.空调能效比发展趋势的研究[J].制冷与空调,2007,7(03):10-13
[9]GB19577-2004,冷水机组能效限定值及能源效率等级[S].北京:中国标准出版社,2004
[10]GB50189-2005,公共建筑节能设计规范[S].北京:中国建筑工业出版社,2005
[11]GB12021.3-2004,房间空气调节器能源效率限定值及能效等级[S].北京:中国标准出版社,2004
[12]GB19576-2004,单元式空气调节机能效限定值及能源效率等级[S].北京:中国标准出版社,2004
[13]GB/T18430.1-2001,蒸汽压缩循环冷水(热泵)机组工商业用和类似用途的冷水(热泵)机组[S].北京:中国标准出版社,2001
[14]郭红军.公共建筑空调系统设计综合能效比计算方法的研究[D].重庆:重庆大学,2010
[15]杨李宁.公共建筑空调工程能效比的研究[D].重庆:重庆大学,2007
[16]刘轶.对建筑空调系统设计能效比的初步计算分析[J].暖通空调,2006,36(08):50-52
[17]肖益民,付祥钊,杨李宁,等.重庆市商场类建筑空调工程设计能效比统计分析[J].暖通空调,2007,37(08):130-134
[18]林真国,张素云,付祥钊,等.重庆市酒店类建筑空调工程设计能效比调研[J].暖通空调,2009,39(02):27-30,104
[19]黄伟,刘谨,李继路.关于空调冷冻水输送能效比计算的一点看法[J].制冷,2009,28(01):86-87
[20]龚明启,冀兆良,宋玮.水环热泵型空调系统设计及工程实例分析[J].制冷,2005,24(03):46-52
[21]赖雪梅.中央空调系统全年运行能效分析[M].北京:北京工业大学,2007
[22]CaglarSelcuk Canbaya,Arif, H.,Gulden, G. Evaluating performance indices of a shopping centre andimplementing HVAC control principles to minimize energy usage[J]. Energy and Buildings,2004,36(6):587-598
[23]GB/T17981-2007,空气调节系统经济运行[S].北京:中国标准出版社,2007
[24]文韬.空调工程运行能效检测理论与方法[D].重庆:重庆大学,2008
[25]林建泉.小型过冷式冰蓄冷多联空调系统的运行优化控制策略研究[D].武汉:华中科技大学,2009
[26]Zimmer, H. Chiller control using on-line allocation for energy conservation[R]. Houston, TX, USA:Adv Instrum,1976
[27]Chun, C.,Norden, N. Computer optimization of refrigeration systems in a textile plant: a case history[J].Automation,1982,18(6):675-683
[28]Enterline, L.,Sommer, A.,Kaya, A. Chiller optimization by distributed control to save energy[J]. ISATransactions,1984,23(2):1137-1149
[29]Lau, A.,Beckman, W. Development of computerized control strategies for a large chilled water plant[J].ASHRAE Trans,1985,91(2):766-780
[30]Braun, J.E.,Klein, S.A.,Mitchell, J.W. Methodologies for optimal control to chilled water systemswithout storage[J]. ASHRAE Trans,1989,95(1):652-662
[31]Olson, R.T. A dynamic procedure for the optimal sequencing of plant equipment plant II: validationand sensitivity analysis[J]. Engineering Optimization,1994,22(3):163-183
[32]Curtiss, P.S. Artificial neural networks for use in building systems control and energy management[D].Colorado: University of Colorado-Boulder,1992
[33]Austin, S.B. Chilled water system optimization[J]. ASHRAE,1993,35(7):50-56
[34]Lam, J.C. Regression analysis of high-rise fully air-conditioned office buildings[J]. Energy andBuildings,1997,26(2):189-197
[35]Ahn, B.C.,Mitchell, J.W. Optimal control development for chilled water plants using a quadraticrepresentation[J]. Energy and Buildings,2001,33(4):371-378
[36]Wang, S.,John, B. Online adaptive control for optimizing variable-speed pumps of indirectwater-cooled chilling systems[J]. Applied Thermal Engineering,2001,21(11):1083-1103
[37]晋欣桥.变风量空调系统的仿真及其实时优化控制研究[D].上海:上海交通大学,1999
[38]Lu, L.,Cai, W.,Yeng, C., et al. HVAC system optimization—condenser water loop[J]. EnergyConversion and Management,2004,45(4):613-630
[39]Chang, Y.,Lin, J.,Chuang, M. Optimal chiller loading by genetic algorithm for reducing energyconsumption[J]. Energy and Buildings,2005,37(2):147-155
[40]孟华,龙惟定,王盛卫.集中空调冷却水侧上位机控制器的实时控制[J].同济大学学报(自然科学版),2005,33(3):380-384
[41]杨文辉.公共建筑空调系统综合节能运行模式研究[D].重庆:重庆大学,2008
[42]Spethemann, D.H. Optimal Control for Cool Storage[J]. ASHRAR Transactions,1989,95(1):1189-1193
[43]Braun, J.E. A comparison of chiller-priority, storage-priority, and optimal control of an ice-storagesystem[J]. ASHRAE Transactions,1992,98(1):893-902
[44]Simmonds, P. Comparison of Energy Consumption for Storage-Priority and Chiller-Priority forIce-Based Thermal Storage Systems[J]. ASHRAE Transactions,1994,100(1):1746-1753
[45]Kintner-Meyer, M.,Emery, A.F. Optimal control of an HVAC system using cold storage and buildingthermal capacitance[J]. energy and buildings,1995,23(1):19-31
[46]Henze, G. Evaluation of optimal control for active and passive building thermal storage[J].International Journal of Thermal Sciences,2004,43(2):173-183
[47]Murai, M.,Sakamoto, Y.,Shinozaki, T. Optimizing control for district heating and cooling plant[A].IEEE Conference on Control Application–Proceedings[C]. IEEE,1999:600-604
[48]Sakamoto, Y.,Nagaiwa, A.,Kobayasi, S., et al. An optimization method of district heating and coolingplant operation based on genetic algorithm[J]. ASHRAE Transactions,1999,105(part A):104-115
[49]陈晓,张国强,文进希.区域供冷系统中制冷机系统的优化配置探讨[J].流体机械,2003,31(06):55-61
[50]闫军威,刘飞龙,朱冬生,等.广州大学城区域供冷系统质调节的节能分析[J].建筑科学,2007,23(12):27-29,34
[51]Chan, A.L.S.,Tin-Tai, C.,Square, K.F.F., et al. Performanceevaluation of districtcoolingplant withicestorage[J]. Energy,2006,31(14):2750-2762
[52]GB/T18430.1-2007,蒸气压缩循环冷水(热泵)机组第1部分：工业或商业用及类似用途的冷水(热泵)机组[S].北京:中国标准出版社,2007
[53]陆耀庆.暖通空调设计指南[M].北京:中国建筑工业出版社,1996
[54]ASHRAE. ASHRAE Handbook2008: HVAC systems and equipment[M]. Atlanta: ASHRAE Inc,2008
[55]ASHRAE. ASHRAE Handbook Fundamentals[M]. Atlanta: American Soeiety of Heating,2005
[56]GBJ15-51-2007,公共建筑节能设计标准广东省实施细则[S].北京:中国建筑工业出版社,2007
[57]李运华.大型公共建筑运行能耗测试、评价与数据库管理系统开发[D].哈尔滨:哈尔滨工业大学,2006
[58]刘洋.大型公共建筑空调系统能效监测、诊断与性能优化探讨[D].哈尔滨:哈尔滨工业大学,2006
[59]余晓平,付祥钊,杨李宁,等.重庆市办公建筑空调工程设计能效比统计分析[J].暖通空调,2007,37(12):41-45
[60]余晓平,付祥钊,肖益民.既有公共建筑空调工程能效诊断方法问题探讨[J].暖通空调,2010,40(02):33-38
[61]闵晓丹,戎向阳.公共建筑空调冷源系统季节能效比研究[J].暖通空调,2010,40(11):63-67
[62]陈超,渡边俊行,谢光亚,等.日本的建筑节能概念与政策[J].暖通空调,2002,32(06):40-43
[63]闵晓丹.公共建筑空调系统运行能效比分析和优化[D].重庆:重庆大学,2008
[64]陈万仁,王保东.热泵与中央空调节能技术[M].北京:化学工业出版社,2010
[65]薛志峰,江亿.商业建筑的空调系统能耗指标分析[J].暖通空调,2005,35(01):37-41
[66]ANSI/ASHRAE55-1992, Thermal environmental conditions for human occupancy[S]. Atlanta:American Soeiety of Heating,1992
[67]王昭俊,赵加宁,刘京.室内空气环境[M].北京:化学工业出版社,2006
[68]朱立.空气调节技术[M].北京:高等教育出版社,2008
[69]唐鑫.中央空调冷冻水系统一种智能控制方式的研究[D].重庆:重庆大学,2009
[70]林利瓦,徐小勇,张军,等.中央空调变流量PLC控制系统设计[J].自动化仪表,2009,30(09):56-59
[71]郭阳宽,王正林.过程控制系统仿真[M].北京:电子工业出版社,2009
[72]康英姿,左政.区域供冷系统二次管网的冷量损失分析[J].暖通空调,2009,39(11):31-36
[73]贾晶.供冷管道与设备保冷计算和分析[D].哈尔滨:哈尔滨工业大学,2006
[74]赵哲身,何方毅.公共建筑楼宇控制系统能耗监测和节能分析[J].建设科技,2008,(09):36-38
[75]彦启森,石文星,田长青.空气调节用制冷技术[M].北京:中国建筑工业出版社,2004
[76]马宏权,龙惟定.区域供冷系统的能源效率[J].暖通空调,2008,38(11):59-64,40
[77]谭福太.广州大学城区域供冷系统的节能优化[J].节能技术,2009,27(04):371-374
[78]胡寿松.自动控制原理[M].北京:科学出版社,2007
[79]Astrom, K.J.,Hagglund, T. PID controllers: theory, design, and tuning[M].2nd ed. Research TrianglePark, NC: Instrument Society of America,1995
[80]Glickman, S.,Nudelman, G.,Kulessky, R. Identification-based PID control tuning for power stationprocesses[J]. IEEE Trans. on Control SystemsTechnology,2004,12(1):123-132
[81]Kosko, B. Neural networks and fuzzy systems[M]. Prentice: Prentice hail,1993
[82]丁坚.模糊PID控制器的研究[D].哈尔滨:哈尔滨工程大学,2009
[83]Tanaka, K.,Michio, S. Stabilityanalysis and design of fuzzycontrolsystems[J]. Fuzzy Sets and Systems,1992,45(2):135-156
[84]李先峰,杨国华,李建春.基于模糊PID的电阻炉温度控制器的设计与仿真研究[J].微型机与应用,2010,29(10):81-83
[85]丁坚.模糊PID控制器的研究[D].哈尔滨:哈尔滨工程大学,2009
[86]李卷兴,样石中,陆倩倩.变体积空气调节系统的自适应模糊-PID温度控制器[J].,2010,(6):20-23
[87]Curtiss, P.S. Artificial neural networks for use in building systems control and energy management[D].Colorado: University of Colorado-Boulder,1992
[88]何厚键.中央空调水系统的建模与优化研究[D].沈阳:沈阳工业大学,2005
[89]徐庆伟.智能大厦中央空调优化运行与节能管理[D].北京:北京理工大学,2001
[90]胥海伦.空调水系统变流量运行管理的节能措施[D].成都:西南交通大学,2002
[91]朱孟标.空调水系统节能研究[D].南京:南京理工大学,2003
[92]李玉云.中央空调水系统节能技术措施的探讨[J].节能,2003,(02):12-16
[93]晋欣桥,李晓锋,惠广海,等.中央空调水系统控制的优化分析[J].系统仿真学报,2003,15(08):1113-1115
[94]孟华,龙惟定,王盛卫.中央空调水系统优化控制研究的发展及现状[J].建筑热能通风空调,2002,(06):29-32
[95]Bernier, M.A.,Bernard, B. Pumping energy and Variable frequency drives[J]. ASHRAE Journal,1999,41(12):37-40
[96]清华大学Dest开发组.建筑环境系统模拟分析方法—Dest[S].北京:中国建筑工业出版社，2006.
[97]ASHRAE. ASHRAE applications handbook[M]. Atlanta: ASHRAE,1999
[98]康英姿.区域供冷系统集成建模与优化设计[D].广州:华南理工大学,2008
[99]孟华.集中空调水系统的仿真及上位机控制器的实时优化控制研究[D].上海:同济大学,2004
[100]颜永民.建筑冷热源系统自适应优化控制模型的研究[D].长沙:湖南大学,2004
[101]高自友.现代物流与交通运输:模型与方法[S].北京:人民交通出版社，2005.
[102]尹洪超,施光燕,于福东.过程综合混合整数非线性规划的罚函数-凑整算法[J].大连理工大学学报,1997,37(1):49-52
[103]罗向龙,华贲,张冰剑.基于管网模拟的蒸汽动力系统多周期运行优化[J].石油学报（石油化工）,2006,22(5):56-62
[104]Sakawa, M.,Matsui, T. Fuzzy multiobjective nonlinear operation planning in district heating andcooling plants[J]. Fuzzy Sets and Systems,2011, doi:10.1016/j.fss.2011.10.020
[105]茅艳.人体热舒适气候适应性研究[D].:西安建筑科技大学,2007
[106]GB50019-2003,采暖通风与空气调节设计规范[S].北京:2004
[107]薜殿华.空气调节[M].北京:清华大学出版社,2004
[108]龚明启.中央空调系统动态运行节能优化策略研究[D].广州:广州大学,2006
[109]刘传瑞.基于ZigBee和地磁传感器的新型无线交通监控系统的研究与实[D].成都:电子科技大学,2011