机械制造企业能源消耗模型及节能项目评价方法研究
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摘要
能源问题已经成为我国经济发展中的战略问题。为了缓解能源约束与长期增长之间的矛盾,节能成为当前的必然选择。机械制造企业是我国国民经济重要的支柱产业,也是实施节能降耗的重要载体。要实现机械制造企业节能,从系统角度深入研究企业的能源消耗模型,详细了解企业目前的能源消耗状况,预测未来的能源需求状况具有重要意义。此外,针对企业新引进的节能项目,迫切需要研究合理的评价方法。本论文结合国家科技支撑计划重大项目课题“绿色制造共性技术研究及应用”(2006BAF02A01),对机械制造企业能源消耗分析模型和预测模型及节能项目评价方法进行了研究。
首先,在介绍能源消耗状况的基础上,分析了机械制造企业能耗特点,包括能耗部门多、耗能设备多、消耗能源种类多及能源消耗量差异性大等,并介绍了机械制造企业节能策略,包括技术节能策略和管理节能策略。
其次,结合机械制造企业能源消耗特点,基于投入产出理论建立了机械制造企业能源消耗分析模型,该模型以企业消耗的各种能源作为输入,各生产部门的能源消耗作为输出,可以用于支持企业内能耗分析比较与评价、企业内时间方向能耗分析比较与评价、企业间能耗分析比较与评价以及能源价格对企业能耗的影响分析等。
此外,基于BP神经网络建立了机械制造企业能源消耗预测模型,该模型以影响企业能源消耗的设备月运行小时数、产品月产量、工人月工作小时数作为输入,以企业能源月消耗量作为输出,并对企业能耗实测值、BP神经网络预测值、多元线性回归模型预测值进行方差分析,以验证BP神经网络模型的预测效果。
再次,针对企业节能项目评价的不确定性,提出不确定环境下机械制造企业节能项目评价方法,分析了企业节能项目评价中的能源价格和政府决策等不确定性因素,提出不确定性因素分析方法,建立了包括经济性指标、技术性指标、资源性指标、环境性指标的企业节能项目评价指标体系,并提出了各个指标的权重确定方法,介绍了不确定环境下企业节能项目评价步骤。
最后,以某重型机械制造企业为工程背景,将所提出的能源消耗模型及节能项目评价方法进行了实践验证和应用研究。
In China, energy has become one of strategy problems in economic development. Energy conservation is the inevitable choice in order to mitigate the conflict between growth and energy constraints. Mechanical manufacturing enterprises are one of important industries in national ecomony. And they are also one of important parts of energy conservation. Analysis and forecasting of energy consumption and evaluatin method of energy conservation projects for mechanical manufacturing enterprises are researched.
Firstly, the characteristics of energy consumption of mechanical manufacturing enterprises are analyzed, including the number of energy consumption sectors and energy consumption equipments, kinds of energy consumed and the difference of energy consumption quantities and so on. Then energy conservation strategies including technology and management strategies are introduced.
Secondly, an analysis model for mechanical manufacturing enterprises based on input-output theory is built in which the input and output variables are respectively energy consumed by an enterprise and energy consumption of production departments. Then, some applications of the anslysis model are introduced, including comparison of energy consumption in a enterprise, comparison of energy consumption in time direction in a enterprise, evaluation of energy consumption between enterprises and effect analysis of energy price to energy consumption in a enterprise.
Besides, A BP neural networks (BPNN) model is presented for forecasting monthly energy consumption in mechanical manufacturing enterprises. The inputs of the model are monthly total running time of every kind of equipments, monthly total mass of every kind of products and monthly total labor hours of operators. The output of the model is monthly total consumption of every kind of energy. To asses the performance of BPNN, actual data are compared with BPNN and conventional regression model through analysis of variance (ANOVA).
Thirdly, evaluation method of energy conservation projects under uncertain environment for mechanical manufacturing enterprises is proposed. The uncertain factors such as energy price and government decision are introduced, and the analysis method for uncertain factors is presented. Then evaluation indices including economical, technological, resource and environmental indices and the method for calculating their weights are proposed. The steps for evaluation of energy conservation projects under uncertain environment are described.
Finally, a case study has been conducted to demonstrate how the energy consumpton models and evaluation method are applied to a mechanical manufacturing enterprise.
首先,在介绍能源消耗状况的基础上,分析了机械制造企业能耗特点,包括能耗部门多、耗能设备多、消耗能源种类多及能源消耗量差异性大等,并介绍了机械制造企业节能策略,包括技术节能策略和管理节能策略。
其次,结合机械制造企业能源消耗特点,基于投入产出理论建立了机械制造企业能源消耗分析模型,该模型以企业消耗的各种能源作为输入,各生产部门的能源消耗作为输出,可以用于支持企业内能耗分析比较与评价、企业内时间方向能耗分析比较与评价、企业间能耗分析比较与评价以及能源价格对企业能耗的影响分析等。
此外,基于BP神经网络建立了机械制造企业能源消耗预测模型,该模型以影响企业能源消耗的设备月运行小时数、产品月产量、工人月工作小时数作为输入,以企业能源月消耗量作为输出,并对企业能耗实测值、BP神经网络预测值、多元线性回归模型预测值进行方差分析,以验证BP神经网络模型的预测效果。
再次,针对企业节能项目评价的不确定性,提出不确定环境下机械制造企业节能项目评价方法,分析了企业节能项目评价中的能源价格和政府决策等不确定性因素,提出不确定性因素分析方法,建立了包括经济性指标、技术性指标、资源性指标、环境性指标的企业节能项目评价指标体系,并提出了各个指标的权重确定方法,介绍了不确定环境下企业节能项目评价步骤。
最后,以某重型机械制造企业为工程背景,将所提出的能源消耗模型及节能项目评价方法进行了实践验证和应用研究。
In China, energy has become one of strategy problems in economic development. Energy conservation is the inevitable choice in order to mitigate the conflict between growth and energy constraints. Mechanical manufacturing enterprises are one of important industries in national ecomony. And they are also one of important parts of energy conservation. Analysis and forecasting of energy consumption and evaluatin method of energy conservation projects for mechanical manufacturing enterprises are researched.
Firstly, the characteristics of energy consumption of mechanical manufacturing enterprises are analyzed, including the number of energy consumption sectors and energy consumption equipments, kinds of energy consumed and the difference of energy consumption quantities and so on. Then energy conservation strategies including technology and management strategies are introduced.
Secondly, an analysis model for mechanical manufacturing enterprises based on input-output theory is built in which the input and output variables are respectively energy consumed by an enterprise and energy consumption of production departments. Then, some applications of the anslysis model are introduced, including comparison of energy consumption in a enterprise, comparison of energy consumption in time direction in a enterprise, evaluation of energy consumption between enterprises and effect analysis of energy price to energy consumption in a enterprise.
Besides, A BP neural networks (BPNN) model is presented for forecasting monthly energy consumption in mechanical manufacturing enterprises. The inputs of the model are monthly total running time of every kind of equipments, monthly total mass of every kind of products and monthly total labor hours of operators. The output of the model is monthly total consumption of every kind of energy. To asses the performance of BPNN, actual data are compared with BPNN and conventional regression model through analysis of variance (ANOVA).
Thirdly, evaluation method of energy conservation projects under uncertain environment for mechanical manufacturing enterprises is proposed. The uncertain factors such as energy price and government decision are introduced, and the analysis method for uncertain factors is presented. Then evaluation indices including economical, technological, resource and environmental indices and the method for calculating their weights are proposed. The steps for evaluation of energy conservation projects under uncertain environment are described.
Finally, a case study has been conducted to demonstrate how the energy consumpton models and evaluation method are applied to a mechanical manufacturing enterprise.
引文
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