基于传热模型的中央空调系统综合能效优化
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摘要
目前我国建筑能耗中空调系统的能耗已经占据了巨大的比重,而大部分中央空调系统在实际运行过程中,绝大多数时间处于部分负荷,这时的热效率远远低于额定容量下的运行效率,导致大量的能源被浪费掉。因此对中央空调系统进行优化运行对缓解能源需求有着重要的意义。由于中央空调系统庞大且复杂,要实现中央空调系统的节能高效运行,对部分设备进行优化控制的效果并不理想,必须对整个系统进行统一考虑和全面协调。针对目前中央空调系统整体优化研究较少的现状,本文从全局思想出发,研究基于传热模型的中央空调系统综合能效优化方法,希望能够达到系统总能耗降低、高效运行的目的。本文的主要创新工作及贡献包括：
1.建立了一种适用于湿工况的风机盘管的简化传热模型。基于干湿转换的方法,将风机盘管的湿工况转换为一种等价干工况,消除析湿系数对总传热系数的影响,省去湿工况下空气物性计算的过程,不涉及焓值求取。然后对传热模型进行简化,将模型简化为几个独立变量所唯一确定的形式,易于计算求解。仿真结果表明在不同工作条件下模型都具有良好的精度。
2.建立中央空调系统优化运行的数学模型。本文将中央空调系统主要能耗部件的能耗之和作为系统总能耗,设为优化目标。在此基础上建立了各主要能耗部件的能耗模型,并对影响各个部件能耗的因素进行了仿真分析,确定了优化运行参数以及取值范围。
3.本文根据优化模型的特点,提出了一种基于种间竞争的改进自适应遗传算法对中央空调系统进行优化计算,能在满足制冷负荷的前提下降低中央空调系统的总能耗,并保证系统高效运行。改进的遗传算法在基本遗传算法的基础上,基于种间竞争机制,并融入自适应技术,从而既能保证种群多样性,又能保证解的收敛性,增强了整个算法的局部寻优和全局搜索能力。采用改进遗传算法对中央空调系统能效进行优化,优化结果表明,与常规定温差运行方式以及小流量大温差的节能运行方式相比,本文方法能够明显降低系统总能耗并提高运行效率。
At present in our country, the energy consumption of air conditioning system has occupied a large proportion in the building energy consumption. And most of the air conditioning systems are always at the part load in most of the time. In this condition, the thermal efficiency is much lower than the rated capacity efficiency which leads to a large amount of energy wasted. So optimization on the central air conditioning system has important significance to relieve energy demand. Because of the central air conditioning systems is huge and complex, in order to realize the energy saving of central air conditioning system and efficient operation, optimized control effect on the part is not ideal and the entire system must be considered. In view of the overall optimization on the central air conditioning system is very less and considering the global viewpoint, energy efficiency optimization method based on the heat transfer model of the central air conditioning system was researched. It is hoped to be able to reduce the total energy consumption and efficient operation. The innovation and contributions of this thesis are as follows:
1. A simplified heat transfer model of fan coil is established for wet condition. Based on a wet-dry transformation method, the wet cooling condition was converted to an equivalent dry cooling condition of the fan coil. Eliminate the effect of overall heat transfer coefficient from dehumidifying coefficient. And this also omitted the calculation process of air properties in wet conditions, did not involve the enthalpy calculation. Then the heat transfer model was simplified that could be determined only by several independent variables. The simulation results showed that the model has good precision under different working conditions.
2. The optimal operation model of central air conditioning system was established. The overall system energy consumption was set as the optimization target which express as the sum of energy consumption of main components. On the basis of this, energy consumption model of the major energy components was set up and the analysis of the factor of energy consumption was carried out. Then the optimal operation parameters and the range were determined.
3. According to the feature of optimization model, an improved Genetic Algorithm based on interspecies competition using adaptive crossover technology was presented which is used to the optimization calculation of the central air conditioning system. With satisfying the cooling load, the technology reduced the total energy consumption of central air conditioning system, and ensured the efficient operation. On the basis of Standard Genetic Algorithm, the improved Genetic Algorithm based on interspecies competition and integrates adaptive crossover technology to ensure solution's convergence and distribution, thereby enhance its ability of local and global search. Apply the improved genetic algorithm on the central air conditioning system optimization and the optimization results show that compared to the fixed temperature mode and small flow with large temperature difference mode, this technology can significantly reduce energy consumption of the overall system and improve the running efficiency of the system.
1.建立了一种适用于湿工况的风机盘管的简化传热模型。基于干湿转换的方法,将风机盘管的湿工况转换为一种等价干工况,消除析湿系数对总传热系数的影响,省去湿工况下空气物性计算的过程,不涉及焓值求取。然后对传热模型进行简化,将模型简化为几个独立变量所唯一确定的形式,易于计算求解。仿真结果表明在不同工作条件下模型都具有良好的精度。
2.建立中央空调系统优化运行的数学模型。本文将中央空调系统主要能耗部件的能耗之和作为系统总能耗,设为优化目标。在此基础上建立了各主要能耗部件的能耗模型,并对影响各个部件能耗的因素进行了仿真分析,确定了优化运行参数以及取值范围。
3.本文根据优化模型的特点,提出了一种基于种间竞争的改进自适应遗传算法对中央空调系统进行优化计算,能在满足制冷负荷的前提下降低中央空调系统的总能耗,并保证系统高效运行。改进的遗传算法在基本遗传算法的基础上,基于种间竞争机制,并融入自适应技术,从而既能保证种群多样性,又能保证解的收敛性,增强了整个算法的局部寻优和全局搜索能力。采用改进遗传算法对中央空调系统能效进行优化,优化结果表明,与常规定温差运行方式以及小流量大温差的节能运行方式相比,本文方法能够明显降低系统总能耗并提高运行效率。
At present in our country, the energy consumption of air conditioning system has occupied a large proportion in the building energy consumption. And most of the air conditioning systems are always at the part load in most of the time. In this condition, the thermal efficiency is much lower than the rated capacity efficiency which leads to a large amount of energy wasted. So optimization on the central air conditioning system has important significance to relieve energy demand. Because of the central air conditioning systems is huge and complex, in order to realize the energy saving of central air conditioning system and efficient operation, optimized control effect on the part is not ideal and the entire system must be considered. In view of the overall optimization on the central air conditioning system is very less and considering the global viewpoint, energy efficiency optimization method based on the heat transfer model of the central air conditioning system was researched. It is hoped to be able to reduce the total energy consumption and efficient operation. The innovation and contributions of this thesis are as follows:
1. A simplified heat transfer model of fan coil is established for wet condition. Based on a wet-dry transformation method, the wet cooling condition was converted to an equivalent dry cooling condition of the fan coil. Eliminate the effect of overall heat transfer coefficient from dehumidifying coefficient. And this also omitted the calculation process of air properties in wet conditions, did not involve the enthalpy calculation. Then the heat transfer model was simplified that could be determined only by several independent variables. The simulation results showed that the model has good precision under different working conditions.
2. The optimal operation model of central air conditioning system was established. The overall system energy consumption was set as the optimization target which express as the sum of energy consumption of main components. On the basis of this, energy consumption model of the major energy components was set up and the analysis of the factor of energy consumption was carried out. Then the optimal operation parameters and the range were determined.
3. According to the feature of optimization model, an improved Genetic Algorithm based on interspecies competition using adaptive crossover technology was presented which is used to the optimization calculation of the central air conditioning system. With satisfying the cooling load, the technology reduced the total energy consumption of central air conditioning system, and ensured the efficient operation. On the basis of Standard Genetic Algorithm, the improved Genetic Algorithm based on interspecies competition and integrates adaptive crossover technology to ensure solution's convergence and distribution, thereby enhance its ability of local and global search. Apply the improved genetic algorithm on the central air conditioning system optimization and the optimization results show that compared to the fixed temperature mode and small flow with large temperature difference mode, this technology can significantly reduce energy consumption of the overall system and improve the running efficiency of the system.
引文
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