擒要:通过强化节能管理等措施,重点用能单位主要产品单位能耗显著下降、节能技术进步提速、节能目标如期完成,对推动完成全国节能约束性目标做出了贡献.但在不同阶段国家重点用能单位节能专项活动中,出现了活动实施范围、目标体系设置、市场化节能作用增加等新变化,要求重点用能单位适应新要求,进一步提升能源计量、节能信息化等节能管理能力.

本文首先通过对比国外信用发展过程,指出我国信用体系建设所处的发展阶段.其次,调研了信用体系在各领域的应用,特别是在节能领域的应用现状.最后,通过对比信用体系较为完善的环保领域,并结合节能领域信用机制尝试较早的湖南省经验,提出了我国节能领域运用信用机制提高工作成效的路径建议.

本文对文献中出现的工业行业能效评价方法进行了调研,详细讨论了6种典型的能效评价方法:简单指标比对法、随机前沿分析法、数据包络法(DEA)、逼近理想值排序法(TOPSIS)、泰勒展开法和可拓物元法.简要介绍了各个评价方法的实施步骤,分析了每种方法的优缺点并将它们进行对比分析,给出了6种能效评价方法对我国工业行业开展能效评价可提供的借鉴思路.

山西省长治市是市级层面推进重点用能单位能耗在线监测系统建设先行地区之一.本文系统介绍了长治市重点用能单位能耗在线监测系统建设的做法和经验,包括系统的服务定位、主要功能、建设模式及主要任务等.本文通过一个企业实际案例,说明能耗在线监测对企业节能降本增效的促进作用.

A new hybrid methodology is introduced which is a combination of multiple regression model and generalised autoregressive conditional heteroskedasticity (GARCH) model. Comparing the new approach and the vector auto-regression (VAR) model, this paper analyses the short-term dynamics of the energy efficiency index (EEI) in response to change in the five indicator variables for thermal power plants in China. The result indicates that: (i) The new hybrid model can directly calculate the EEIs of thermal power plants without artificial intervention. (ii) It can eliminate the disturbance of residual superposition. (iii) The new method will offer more direct information on the degree of volatility among determinants and operating inefficiency. (C) 2016 Elsevier Ltd. All rights reserved.

A new hybrid methodology is introduced in this paper for analysing the energy efficiency indicators of thermal power plants.The multiple regression model and the generalised autoregressive conditional heteroskedasticity (GARCH) model are composed in this model.There are five indicators variables are employed.The examination results indicate that this new hybrid econometric analysis can not only estimate the energy efficiency indicators without manual intervention,but analyse the short-term volatility of variables.Moreover,the methodology can eliminate the disturbance of residual superposition.Furthermore,the method can provide direct information on the degree of volatility among determinants and energy efficiency indicators.The accuracy of hybrid methodology has been proved by the comparison results of vector auto-regression (VAR)model.

In this paper, both energy efficiency and environmental efficiency of coal-fired power units are studied based on the non-parametric data envelopment analysis method (DEA). Compared with energy efficiency, the emission of SO2 and NOx are taken into consideration for the environmental efficiency. The ST model is employed to calculate pure technical efficiency. And the strong disposability model is used to calculate the environmental efficiency. Analysis and comparison for energy and environmental efficiency are conducted. By comparing the influence of ownership factor on these two kinds of efficiency, it can be found that the China Guodian Corporation ranks the first in both the energy and environmental efficiency. China Datang Corporation ranks the third in energy efficiency while ranks the last one in environmental efficiency.

In this article, the non-parametric data envelopment analysis method (DEA) is employed to evaluate energy efficiency (EE) of 34 coal-fired power units in China. Input-oriented CCR (Charnes, Cooper and Rhodes) model is used for EE analysis. Two efficiency indices, generalized EE and special EE are defined and analyzed. The generalized EE is calculated based on four input parameters: coal consumption, oil consumption, water consumption and auxiliary power consumption by power units. The special EE is only based on two input parameters: coal consumption and auxiliary power consumption. Relations between these two EE indices and non-comparable factors including quality of coal, load factor, capacity factor, parameters of main steam and cooling method are studied. Comparison between EE evaluation results of the two indices is conducted. Results show that these two kinds of EE are more sensitive to the load factor than the capacity factor. The influence of the cooling method on EE is larger than that of main steam parameter. The influence of non-comparable factors on the special EE is stronger than that on the generalized EE. (c) 2015 Elsevier Ltd. All rights reserved.

本文对17个1000MW的火电机组的能效水平进行了综合评价.基于三个子指标:发电煤耗率、厂用电率和综合耗水率,首先采用主观的层次分析法和客观的熵权法相结合确定了各子指标的权重;其次分别采用可拓物元模型和逼近理想值的排序方法(Technique for Order Preference by Similarity to an Ideal Solution,TOPSIS)对待评价机组分别进行能效等级判断和能效水平排序.对典型机组,两种模型的实施结果与基于数据的理论分析结果相一致.如果将两种模型配合使用,可实现对火电机组能效水平的完整评价.

This study proposes a new hybrid forecasting methodology for short-term energy efficiency prediction, this new method composes stochastic frontier analysis-generalized autoregressive conditional heteroskedasticity (SFA-GARCH) model and radial basis function neural (RBFN) model. A three-step procedure is implemented. First, the selected independent variables are analysed via SFA-GARCH model, to present their casual relations. Second, regional energy efficiency level is evaluated based upon the time series data obtained from past ten years. Finally, the proposed hybrid model considers a 6-years ahead prediction of regional energy efficiency level. The result demonstrates good performance according to tail loss test when compared with normal SFA method, it proves that the hybrid methodology should be an appropriate measure.

The so-called Hierarchical-Indicator Comparison (HIC) method is introduced in this paper. It mainly serves for industrial energy conservation programs in China. A chemical industry named purified terephthalic acid (PTA) is used to outline this method. Two key points of the HIC method are the construction of energy efficiency indicators (EEI) system and the way to utilize indicators appropriately. After a brief review of EE evaluation methods in literature, the construction procedure of energy efficiency indicators (EEI) system for PTA industry is presented firstly. How to correct reference values for indicators according to non-comparable factors is discussed. Then, how to implement the HIC method based on EEI system is presented. Every indicator has its own advantages and disadvantages. Disadvantages of an indicator can be conquered by other indicators. With multiple indicators used together, more objective EE evaluation result can be obtained. Finally, some proposals for further work of this method are also presented. (C) 2014 Elsevier Ltd. All rights reserved.

In this paper, evaluation index system with two levels is established to evaluate energy efficiency of fossil-fuel power plant in a comprehensive and objective way, in order to provide detailed methods for energy-saving and emission reduction. The index system includes five indicators at the first level and two indicators at the second level. Principal component analysis (PCA) model is adopted to comprehensively evaluate energy efficiency of fossil-fuel power units. PCA is a relatively objective evaluation method, which can not only determine weights objectively, but also roundly reflect most information from multiple indicators. The method presented in this paper is implemented on seventeen 1000MW thermal power units. The results obtained agree well with the actual situation and those in the references.

In this article, the non-parametric data envelopment analysis method (DEA) is employed to evaluate energy efficiency (EE) of coal-fired power units in China. The data set contains inputs and outputs of 34 coal-fired power units with the capacity of 600MW. Input-oriented CCR (Charnes-Cooper-Rhodes) is employed. The value of CCR efficiency calculated in this paper is based on two input parameters: fuel consumption and auxiliary power consumption. The relations between EE and factors including, parameter of main steam, cooling method, capacity utilization rate and annual utilization hours are analysed. Some relation curves are fitted.

Energy consumption by industrial sectors has possessed a large proportion of total energy use in many countries especially China. For the purposes of energy conservation, the government of China has implemented long-term policies to continuously assist thermal power industries in improving the energy efficiency. This paper investigates the short- and long-term causal relationship implied by the standard coal consumption per unit product of power (SCC), the rate of electricity consumption of power plant (EC), the total water consumption per unit product of power generation (WC) and the total oil consumption per year (OC). The result indicates that there is mutual influence among variables. The SCC is significantly correlated with the EC, a large amount of EC may impact SCC heavily. The OC is proved to be a new driving factor, and it has long-run equilibrium relationship with other three variables.

A multi-scale modeling framework combining finite volume method (FVM) and lattice Boltzmann method (LBM) previously developed by our group is used to predict electrochemical transport reaction in proton exchange membrane fuel cell (PEMFC) cathode with a parallel gas channel (GC), a gas diffusion layer (GDL) with porous structures and a catalyst layer (CL) with idealized microstructures. In this framework, the PEMFC cathode is divided into two sub-domains, one is GC and the other contains GDL and CL. The FVM is used to simulate transport phenomena in the GC sub-domain, while the LBM is employed for pore-scale transport phenomena in the GDL and CL as well as proton conduction in the CL in the other sub-domain. Two reconstruction operators are adopted to transfer macro density, velocities and concentration in the FVM to density distribution functions and concentration distribution functions in the LBM at the interface between the two sub-domains. Simulation results show that the coupled (hybrid) simulation strategy developed is able to predict transport phenomena in the GC and to capture the pore-scale transport processes in porous GDL and CL. In addition, some techniques to save the computational resources and to improve the efficiency of the coupled (hybrid) simulation strategy are discussed.

Energy and carbon emission problems have become the key issues around the world now. Energy saving and emission reduction are the responsibility of the whole social society. The improvement of energy efficiency of high energy-consumption industries can make great contribution to emission reduction. The construction of energy efficiency indicator system can provide a scale tool for the measurement of energy efficiency, and provide a criterion for the execution of national policy on energy saving and emission reduction. This paper takes two high energy-consumption industries (thermal power plant and pure terephthalic acid industry) for example, the construction method of energy efficiency indicator system are studied. The "induction & screening method" is used for the construction of energy efficiency indicator system of thermal power plant, while the "reference method" is used for PTA (pure terephthalic acid) industry.

In this paper, a concentration distribution function reconstruction operator is derived to lift macroscopic parameter concentration to concentration distribution function in lattice Boltzmann method (LBM). Combined with a density–velocity distribution function reconstruction operator previously derived by the author’s group, the coupled finite volume method and LBM scheme (CFVLBM), previously proposed by the authors’ group is extended to simulate both fluid flow and mass transport processes. The accuracy of concentration distribution function reconstruction operator and the feasibility of CFVLBM are validated by two numerical examples, diffusion–convection–reaction problem and natural convection in a square cavity induced by concentration gradient. Finally, the CFVLBM is further adopted to simulate fluid flow and mass transport in the gas channel (GC) and gas diffusion layer (GDL) of a proton exchange membrane fuel cell (PEMFC). It is found that the CFVLBM can capture the pore-scale information of fluid flow and species transport in porous GDL and can save the computational resources.

RNGκ-e model was employed to simulate the three dimensional flow field of the marine oil-fired boiler.The results of numerical computation which was taken under the normal condition(0.101MPa,20℃)were compared with PIV experimental results.The agreement of radial scale and pressure drop proved the reliability of the computation model used in this paper.This model was then applied in the running conditions: 100%BMCR and 50%BMCR.On the plane perpendicular to axis,they both have the similar M-shaped dimensionless tangential and axial velocity profile.But there is weak symmetry for tangential profile due to the asymmetrical distribution holes in the bluff-body.Compared with 100%BMCR,the axial and radial scale of 50%BMCR decreased by 1.59% and 4.55%,the maximum reflux speed decreased by 53%,and the pressure drop decreased by 75%.The pressure drop computed by simulation agreed well with empirical formula results.This paper can provide reference for the design and optimization of the air-distributed organ.

For optimizing recirculation zone of the air distributed organ,CFD numerical simulation study on the flow fields and the recirculation zone distribution in the air distributed organ of oil-fired boilers are implemented using κ-e model.The simulation result agrees well with the analytic results.It is showed that the size of the recirculation zone and the pressure loss decrease,while the angle degree of the inlet decreases;and the size of the recirculation zone and the pressure loss decrease,while the velocity of the inlet decreases;and the size of the recirculation zone increases,and the pressure loss decreases,while the temperature increases.