[1]赖学江、黄森炜、廖洪毅、曹智校、陈清云.基于动态负荷预测的冰蓄冷系统运行策略优化[J].福建工程学院学报,2021,19(04):372-377.[doi:10.3969/j.issn.1672-4348.2021.04.011]
 LAI Xuejiang,HUANG Senwei,LIAO Hongyi,et al.Operation strategy optimization of ice storage system based on dynamic load forecasting[J].Journal of FuJian University of Technology,2021,19(04):372-377.[doi:10.3969/j.issn.1672-4348.2021.04.011]
点击复制

基于动态负荷预测的冰蓄冷系统运行策略优化()
分享到:

《福建工程学院学报》[ISSN:2097-3853/CN:35-1351/Z]

卷:
第19卷
期数:
2021年04期
页码:
372-377
栏目:
出版日期:
2021-08-25

文章信息/Info

Title:
Operation strategy optimization of ice storage system based on dynamic load forecasting
作者:
赖学江、黄森炜、廖洪毅、曹智校、陈清云
广东海洋大学
Author(s):
LAI XuejiangHUANG SenweiLIAO HongyiCAO ZhixiaoCHEN Qingyun
School of Mechanical and Power Engineering, Guangdong Ocean University
关键词:
冰蓄冷全年动态负荷模拟预测控制
Keywords:
ice storage annual dynamic load simulation predictive control
分类号:
TU831
DOI:
10.3969/j.issn.1672-4348.2021.04.011
文献标志码:
A
摘要:
以深圳某办公楼为例,探讨冰蓄冷空调系统运行策略的优化。采用鸿业全年负荷计算及能耗分析软件(HY-EP)进行全年动态负荷模拟,对冷负荷的负荷率进行分析。在选定冰蓄冷系统后,基于模拟结果和地区的峰谷平电价的特点,采用了基于全年动态负荷结果分析预测和结合前一天的负荷作为当日的负荷预测,将全年逐日运行策略简化为4 种设备的运行方案,控制较为容易实现,且需要增加的初投资较少,是结合冰蓄冷系统与全年动态负荷模拟技术的创新应用。
Abstract:
Taking an office building in Shenzhen as an example, the operation strategy optimization of ice storage air conditioning system was discussed.Hongye annual load calculation and energy consumption analysis software (HY-EP) was used to simulate the annual dynamic load. The load rate of the cooling load was discussed. After the ice storage system was selected, based on the simulation results and the characteristics of the peak-valley TOU power price of the region, an innovative method based on the analysis and prediction of annual dynamic load results and combined with the load of the previous day is adopted as the load forecast of the day. It is an innovative application of ice storage system and annual dynamic load simulation technology, which simplifies the whole year day-to-day operation strategy to four equipment operation schemes, and the control is easier to achieve, and the initial investment that needs to be increased is less than expected.

参考文献/References:

[1] 朱雪斌, 唐朝新, 李颖, 等. 福建省某科技园冰蓄冷空调系统运行分析[J]. 制冷与空调, 2020, 20(11):92-95.[2] 徐鹏, 潘安东, 段之殷. 冰蓄冷空调系统经济性分析[J]. 西安建筑科技大学学报(自然科学版), 2021, 53(1):109-116.[3] 李兰. 某体育馆冰蓄冷空调方案经济性分析[J]. 建筑节能, 2020, 48(10):93-96.[4] 谭亮. 义乌市某办公建筑空调系统方案优化设计与节能研究[D]. 广州:广州大学,2011.[5] 王雯翡, 吕丽娜, 李晓萍, 等. 北方地区某大型博物馆关键技术节能效果分析[J]. 建筑节能, 2020, 48(10):26-31.[6] 孙悦,韩明新,任洪波等.冰蓄冷空调系统优化运行控制策略研究综述[J].制冷与空调,2020,20(11): 69-73,77[7] 任延欢. 基于群智能的冰蓄冷空调负荷预测及运行优化研究[D]. 西安:西安建筑科技大学,2020.[8] 周李鹏. 某办公楼冰蓄冷系统的线性与非线性优化对比分析[J]. 应用能源技术, 2020(4):21-26.[9] 王炳南, 崔建磊, 李洪涛. 北京三星总部大楼工程蓄冷应用技术[J]. 施工技术, 2020, 49(7):124-128.

更新日期/Last Update: 2021-08-25