摘要
基于质量和能量守恒定律及传热学原理创建间接连接区域供热系统动态模型。应用此模型,模拟分析不同循环质量流量时系统动态过程,并讨论存在管道热损失、补水、换热器及散热器富裕面积对系统动态特性的影响。结合2012年2月13日~2月19日逐时室外温度对整个系统进行动态模拟。结果表明:系统特征点温度响应与实测值误差较小,证明所建动态模型的准确性和实用价值。为补偿室外温度波动对供热系统的影响,采用四种PI控制策略模拟系统动态响应和分析比较其能耗。模拟分析显示:在室内温度控制方面,锅炉燃料质量流量与末端散热装置循环质量流量联合控制具有最佳控制精度;在系统能耗方面,锅炉燃料质量流量与一次网循环水量联合控制能耗最小,且管网温度波动最小,但个别时段室内温度波动略高。
Based on mass and energy conservation principles and heat transfer theories, a set of dynamic model was developed for an indirect district heating system. Application of this model to simulate the transient process under different circulation flow rates, and the influence of the pipeline heat loss, make-up water, extra area of intermediate heat exchangers and radiators on the system dynamic characteristics were discussed. The outdoor temperatures measured from February 13-19, 2012 were applied to simulate the dynamic responses of the entire system. The results show that the differences between the simulated and measured responses of the characteristic temperatures are very small. This indicates that the dynamic model developed is of practical value and enough accuracy. To compensate the effect during the changes of outside air temperature for the district heating system, 4 types of PI controllers were applied for simulating the dynamic responses and analyzing the energy consumption of the system in this paper. Simulation results showed that, from the perspective of the indoor temperature control, the strategy of controlling fuel flow rate and the water mass flow rate into the terminals has the best control accuracy; from the aspect of system energy consumption, the strategy of controlling fuel flow rate and water mass flow rate in the primary system has the lowest energy consumption and temperature fluctuations in the piping system as well. However in this case, the indoor air temperatures fluctuate slightly higher.
出处
《热科学与技术》
CAS
CSCD
北大核心
2014年第2期142-149,共8页
Journal of Thermal Science and Technology
基金
陕西省重点科技创新团队资助项目(2012KTC-11)
关键词
区域供热系统
动态模型
控制策略
运行优化
indirect district heating system
dynamic modeling
control strategy
optimal operation