基站用相变储能空调机组性能预测及控制仿真研究

发布时间：2018-06-19 01:52

本文选题：通信基站 + 相变储能技术　；参考：《湖南大学》2015年硕士论文

【摘要】：随着电子行业以及通信技术的快速发展,通信基站的数量与日剧增。通信基站需要全天候不间断通信,导致其能耗增长迅速,在能耗构成中,空调能耗占基站总能耗的43%,因此,如何降低基站内空调能耗成为专家学者的研究热点。目前,众多专家学者从室外自然冷源利用角度对基站空调节能进行研究,但由于室外环境气温周期性变化,使得室外自然能源在利用时出现供需不平衡的现象。相变储能技术通过充分利用相变材料在相变过程时储存或释放能量的特性来解决自然冷源利用中存在时空不匹配问题,实现基站能耗降低,同时可以解决基站出现如断电原因而不能使用空调等应急问题。本文通过现有基站节能技术的发展情况,结合相变储能技术开发出相变储能空调机组,机组包括新风工况、新风储能工况以及放能工况。在焓差台实验室对机组进行储能量、放能量以及能效比实验,结果显示:机组5小时内储存26005k J冷量,平均能效比EER为11.87;释放过程中,机组3.75释放18370k J的冷量,平均能效比EER为9.64。由于相变空调机组性能实验所耗费的时间多以及代价高,本文采用BP神经网络预测模型对机组进行性能预测,减小相变储能空调机组的开发及改进成本,同时为机组的智能储放能研究作前期准备。将预测结果与实验结果对比发现所提出的预测模型能很好地对机组进行预测,几个主要性能指标的误差在接受范围内不超过2%。因相变储能空调机组处于开发阶段,考虑到实际应用的控制问题,本文结合控制节能思路采用模糊PID控制器,通过MATLAB/Simulink程序对机组在基站中的应用进行控制仿真研究,与常规PID控制器比较,结果显示:模糊PID控制效果明显优于PID控制,其调节时间更快,超调量更小,鲁棒性更强。
[Abstract]:With the rapid development of electronic industry and communication technology, the number and daily increase of communication base stations. The communication base station needs all-weather continuous communication, which leads to the rapid growth of its energy consumption. In the energy consumption composition, the energy consumption of air conditioning accounts for 43 percent of the total energy consumption of the base station. Therefore, how to reduce the energy consumption of air conditioning in the base station has become a hot research topic for experts and scholars. At present, many experts and scholars study the energy saving of base station air conditioning from the angle of outdoor natural cold source utilization. However, due to the periodic change of outdoor ambient temperature, there is imbalance between supply and demand when outdoor natural energy is used. Phase change energy storage technology solves the problem of space-time mismatch in the use of natural cold source by making full use of the characteristics of energy storage or release of phase change materials during the phase change process, thus reducing the energy consumption of base station. At the same time, it can solve the emergency problems of base station such as power failure and air conditioning. Based on the development of energy saving technology of base station and combined with phase change energy storage technology, a phase change energy storage air conditioning unit is developed in this paper. The unit includes fresh air condition, fresh air energy storage condition and release energy condition. The energy storage, release energy and energy efficiency ratio of the unit are tested in the enthalpy difference laboratory. The results show that the unit stores 26005kJ cooling capacity within 5 hours, the average EER is 11.87, and during the release process, the unit 3.75 releases 18370kJ, The average energy efficiency ratio (EER) is 9.64. Because the performance experiment of phase change air-conditioning unit is time-consuming and costly, the BP neural network prediction model is used to predict the performance of the unit to reduce the cost of development and improvement of phase change energy storage air-conditioning unit. At the same time, preparation for the intelligent energy storage and discharge research of the unit is made. By comparing the prediction results with the experimental results, it is found that the proposed prediction model can predict the units well, and the errors of several main performance indexes are not more than 2% within the accepted range. Because the phase change energy storage air conditioning unit is in the development stage, considering the actual application control problem, this paper combines the control energy saving idea to adopt the fuzzy pid controller, carries on the control simulation research to the unit in the base station through MATLAB / Simulink program. Compared with the conventional pid controller, the results show that the fuzzy pid control effect is better than pid control, the adjustment time is faster, the overshoot is smaller, and the robustness is stronger.
【学位授予单位】：湖南大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TU831

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