运输航空公司能耗监测方法研究与框架设计

发布时间：2018-09-17 17:07

【摘要】：随着航空运输规模的不断扩大,民航业对能源需求的压力日益增大。“十三五”规划提出绿色发展的理念,民航节能减排的任务更加繁重。航空公司的能源消耗占全民航业的90%以上,因此航空公司的节能工作是行业节能减排的重中之重。航空公司能耗监测体系的建设使得能源消耗情况透明化,能为节能减排工作的开展提供一定的决策支持。本文以某航空公司的能耗数据为基础,从航空公司能耗结构的角度出发,分析能耗的影响因素,选定监测指标。先获取能耗数据,再分事前和事后对监测到的能耗数据分析比较,逐步实现对能耗的合理监测。从节能减排工作的管理层面和执行层面两方面考虑,实现能耗监测框架的设计。本文的研究能为航空公司的能耗监测工作提供参考。本文的主要研究工作有:首先,分析运输航空公司能耗结构,并按照空侧和地侧将航空公司的能耗分为飞行能耗和地面能耗,再考虑其各自的影响因素并提出节约用能的措施。参考中国民航节能减排的指标,从航空公司的角度出发,建立能耗监测指标体系。其次,提出航空公司能耗监测方法并分析其意义。飞行能耗按照航线、航段、机型划分;地面能耗分别划分为电力、天然气、外购热力等分类能耗,由用能的系统或区域不同再进一步将分类能耗数据分解为分项能耗。再从时间维度和空间维度不同的角度考虑,分别提出相应的监测方法,如果能耗出现异常,能准确快速地分析出具体出现能耗异常的点源。再次,从节能减排的管理层面考虑,区分不同部门扮演的角色,设计能耗监测组织结构的框架。从航空运输过程分析入手,设计监测的具体流程,并分析监测的技术手段。监测框架的重点是分事前和事后将能耗数据与基准值的比较,找出航空公司的能耗水平与指标的差距,并深入分析其原因,提出相应的应对措施以达到节能的目的。最后,根据监测到的历史数据,建立合适的预测模型,便于节能进展的预判与决策、能源需求的科学规划。选用ARIMA模型、灰色马尔科夫、GM-ARMA组合模型、灰色马尔科夫-ARMA组合模型分别预测航空公司的月度综合能耗,并分析每个预测模型适用的数据特征。预测模型的特点是滑动预测。结果显示,灰色马尔科夫-ARMA组合模型能较好地描述对航空公司能耗序列。
[Abstract]:With the expansion of the scale of air transportation, the pressure on energy demand of civil aviation industry is increasing day by day. The third five-year Plan put forward the concept of green development, civil aviation energy-saving and emission reduction tasks are more arduous. The energy consumption of airlines accounts for more than 90% of the total civil aviation industry, so the energy saving work of airlines is the top priority of energy saving and emission reduction. The construction of energy consumption monitoring system of airlines makes energy consumption transparent and can provide decision support for energy saving and emission reduction. Based on the energy consumption data of a certain airline, this paper analyzes the influencing factors of energy consumption and selects the monitoring index from the point of view of the energy consumption structure of the airline. The energy consumption data are obtained first and then analyzed and compared before and after the monitoring to realize the reasonable monitoring of energy consumption step by step. The design of energy consumption monitoring framework is realized from the aspects of management and implementation of energy saving and emission reduction. The research in this paper can provide a reference for the energy consumption monitoring of airlines. The main research work of this paper is as follows: firstly, the energy consumption structure of transport airlines is analyzed, and the energy consumption of airlines is divided into flight energy consumption and ground energy consumption according to the air side and ground side, then considering their respective influence factors and putting forward the measures to save energy. According to the index of energy saving and emission reduction of CAAC, the energy consumption monitoring index system is established from the point of view of airline. Secondly, the monitoring method of airline energy consumption is put forward and its significance is analyzed. Flight energy consumption is divided according to route, section and type; ground energy consumption is divided into electric power, natural gas, outsourced heat consumption and so on. The classified energy consumption data are further decomposed into itemized energy consumption by different energy consuming systems or regions. Considering the difference of time dimension and space dimension, the corresponding monitoring methods are put forward. If the energy consumption is abnormal, the point source of the energy consumption anomaly can be analyzed accurately and quickly. Thirdly, from the management level of energy saving and emission reduction, the role of different departments is distinguished, and the framework of energy consumption monitoring organization structure is designed. Starting with the analysis of air transportation process, the monitoring process is designed and the technical means of monitoring are analyzed. The focus of the monitoring framework is to compare the energy consumption data with the reference value in advance and afterwards, to find out the gap between the energy consumption level and the index of the airline company, and to analyze the reasons and put forward the corresponding countermeasures to achieve the purpose of energy saving. Finally, according to the monitored historical data, a suitable prediction model is established, which is convenient for the prediction and decision of energy conservation progress and the scientific planning of energy demand. The ARIMA model, the grey Markov GM-ARMA combined model and the grey Markov ARMA combination model are used to predict the monthly comprehensive energy consumption of the airlines, respectively, and the data characteristics applicable to each prediction model are analyzed. The prediction model is characterized by sliding prediction. The results show that the grey Markov-ARMA combined model can describe the energy consumption sequence of airlines.
【学位授予单位】：中国民航大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：V35;TP274

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