期刊文献+

亚龙湾冰蓄冷区域供冷项目自控设计与应用分析 被引量:3

Automatic Control System Design and Application Analysis on Yalong Bay Ice Storage District Cooling System
原文传递
导出
摘要 冰蓄冷区域供冷系统设备多运行工况复杂,常规基于PLC的控制系统难以实现优化管理。本文以国家节能示范项目亚龙湾冰蓄冷区域供冷站为例,分析了项目特点与自控需求,采用基于能源管理的自控系统整体实现方案,创建了区域能源运营商与用户的协调管理平台,并对系统实行了逐时策略控制与运行定量分析。运行调查与实测显示,该自控系统可有效提高区域供冷系统的运行性能,实现高品质供冷、经济运行和节能减排的综合社会效益。 Ice storage district cooling system is more complex than conventional systems, and the PLC-based control system is difficult to achieve optimal management. In this paper,the automatic control system design of Yalong Bay ice storage district cooling station was introduced. Firstly, the project characteristics and automatic control demands were presented. Secondly, using the integrated solve strategy based on energy management, a coordinated management platform for the automatic control system was established. Thirdly,the quantitative analysis of hourly strategy control and real-time operation were provided. The survey and experimental results demonstrated that the presented automatic control system could achieve comprehensive social benefits of high quality cqoling supply, economic operation and energy-saving.
出处 《建筑科学》 北大核心 2012年第8期104-108,共5页 Building Science
关键词 区域供冷 冰蓄冷 自控系统 能源管理 节能示范 district cooling system, ice storage, automatic control system, energy management, energy conservation demonstration
  • 相关文献

参考文献6

二级参考文献25

  • 1许文发,赵建成,蔺洁.区域供冷系统在中关村西区的实际应用[J].建筑科学,2004,20(z1):190-193. 被引量:5
  • 2施灵.多台冷水机组空调系统的优化控制[J].暖通空调,2005,35(5):79-81. 被引量:29
  • 3地域冷暖房技術手引書[M].2版.日本地域冶暖房協會,2002,3
  • 4熱供給事業便覽[M].日本熱供袷事業協會:平成17年版(2005年版),27
  • 5Shuzo Murakami, Mark D I, Hiroshi Yoshino. Energy consumption, efficiency, conservation, and greenhouse gas, mitigation in Japan's building sector [R]. Lawrence Berkeley Laboratory,2006 : 56
  • 6Vrachopoulos M G; Filios A E, Fatsis A, et al. Determination of the thermal and cooling needs of the broader region of Athens[J]. Renewable Energy, 2008, 33(12): 2615-2622.
  • 7Aktacir M A, Buyukalaca O, Bulut H, et al. Influence of different outdoor design conditions on design cooling load and design capacities of air conditioning equipments[J]. Energy Conversion & Management. 2008, 49(6): 1766-1773.
  • 8Corgnati S P, Perino M, Fracastoro G V. Experimental and numerical analysis of air and radiant cooling systems in offices[J]. Building and Environment, 2009, 44(4): 801-806.
  • 9Ben-Nakhi Abdullatif E, Mahmoud Mohamed A. Cooling load prediction for buildings using general regression neural networks[J]. Energy Conversion & Management, 2004, 45(12/13): 2127-2141.
  • 10HOU Zhi-jian, LIAN Zhi-wei, YAO Ye. Cooling-load prediction by the combination of rough set theory and an artificial neural-network based on data-fusion technique[J]. Applied Energy, 2006, 83(9): 1033-1046.

共引文献66

同被引文献20

引证文献3

二级引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部