青岛华威风电场风能资源分析

根据华威风电场2008年4月1日-2009年3月31日一整年的测风仪测风资料,对风电场的风能资源各参数进行了详细地计算和分析,对风电场的风能资源进行评价,为当地的风能开发提供分析基础。     

论水处理工程中的节能

人们在污水处理厂的建设中对污水处理工艺的先进性、可靠性以及工程投资大小考虑较多,而对污水处理厂建成后的运营管理考虑较少,因而造成许多污水处理厂建成后由于运营成本过高而不能正常运行。从能耗角度出发,分析造成运行成本高的主要原因以及相应采取的措施。     

海洋环境水下电场时频特征分析

目的掌握海洋环境水下电场主要能量来源和衰减规律。方法结合理论研究环境电场幅值随时间的变化规律,重点分析水下环境电场不同频带的频谱分布,最后计算得到海洋环境水下电场不同频点的幅值在整个频带所占比重。结果海洋环境水下电场随海水电导率和海水运动强度的减弱,幅值降低,能量主要集中在0.01~1 Hz的低频以及工频处,在一定的空间范围内海洋环境水下电场的一致性较强。结论实验结果与理论分析结果具有一定的吻合度。     

北京市生活垃圾焚烧厂耗能排污特征及节能减排潜力

将生活垃圾焚烧厂从整体到局部分为场站-工艺-单元三个层次,通过现场调查,获取了北京市生活垃圾焚烧设施在2009~2011年不同层次耗能排污数据。分析表明,在焚烧工艺中焚烧单元处理单位垃圾的电耗达到60.83 kW·h,余热发电单元水耗最大,尾气处理单元的电耗和水耗相对较小。不同场站在处理单位垃圾时烟气和炉渣产量比较接近,但飞灰排放差异较大,在2.92~24.78 kg/t垃圾之间。渗沥液水量年际变化较大,水质相对稳定,MBR单元对污染物的去除效果最好,但其耗电量较大,占渗沥液处理工艺总耗电量的87.55%。焚烧工艺发电最优值为423.77 kW·h/t垃圾,产生的电能除满足自身需求外,还剩余1.8×108 kW·h的电能,可用于渗沥液处理工艺或输向场站外部。每吨渗沥液处理最多可产生中水0.962 t,全北京市每年产生中水196456 t/a,使用潜力大。     

苏州污水处理厂污泥干化工艺方案的比选

污泥处理及其处置所面临的重要问题之一,就是如何对城市污水处理厂产生的污泥进行有效减容,尽量降低对外部能源的需求。文中在掌握国内外污泥干化主要工艺技术的基础上,针对某城市污水处理厂的污泥干化工程,拟对采用燃煤烟气干燥、污泥消化一干化一体化、太阳能热泵干燥等三种不同污泥干化工艺进行物料、能量工艺核算。并在此基础上,计算初期投资与15年的运行费用总和。通过对燃料价格、环保和安全等影响因素的研究,分析比较了五种供热系统,以太阳能热泵供热系统为最优,值得大力推广和应用。     

Key factors that influence households’ tree planting behaviour

Despite a decrease in indigenous forests and a growing demand for tree products in developing countries, tree planting activities are not considerably expanding in Tanzania. In this paper, we analyse factors that influence households’ tree planting behaviour, as well as the number of trees planted. Coast and Morogoro regions in the east of Tanzania were selected as the case, and data was gathered from 202 households in 11 villages in these regions where tree planting programmes have been or still are active. A Heckman model is used to analyse the factors that drive tree planting behaviour. Results indicate that households get wood energy from forest reserves (57%), in addition to their own planted trees (9.1%). Emperical findings show that the most important factors have significantly positive effects on households’ tree planting behaviour, as well as the extent to which it was implemented. These factors include households’ land sizes, households’ awareness of tree planting programmes, tree planting for wood energy, and the age of the head of the household. The right/freedom to harvest and transport tree products, households’ attitudes towards tree planting, and family size have significantly negative effects on households’ tree planting behaviour. This paper is perhaps the first comprehensive study to analyse the factors that influence households’ tree planting behaviour in Tanzania, and it uncovers results that are useful, even for other developing countries with similar conditions.     

Suitable error evaluation criteria selection in the wind energy assessment via the K-means clustering algorithm

In this paper, wind energy potential of four locations in Xinjiang region is assessed. The Weibull distribution as well as the Logistic and the Lognormal distributions are applied to describe the distributions of the wind speed at different heights. In determining the parameters in the Weibull distribution, four intelligent parameter optimization approaches including the differential evolutionary, the particle swarm optimization, and two other approaches derived from these two algorithms and combined advantages of these two approaches are employed. Then the optimal distribution is chosen through the Chi-square error (CSE), the Kolmogorov–Smirnov test error (KSE), and the root mean square error (RMSE) criteria. However, it is found that the variation range of some criteria is quite large, thus these criteria are analyzed and evaluated both from the anomalous values and by the K-means clustering method. Anomaly observation results have shown that the CSE is the first one should be considered to be eliminated from the consequent optimal distribution function selection. This idea is further confirmed by the K-means clustering algorithm, by which the CSE is clustered into a different group with KSE and RMSE. Therefore, only the reserved two error evaluation criteria are utilized to evaluate the wind power potential.     

The effect of industry activities on public support for ‘fracking’

Research suggests that previous, current, and prospective extractive industry activities influence perceptions of new development. Studies that have drawn this conclusion, however, have usually focused on specific projects in specific communities. Here, these factors are examined on an aggregate, national scale. Combining geospatial data on extractive industry activities and survey data from a nationally representative sample (N = 1061), the influence of extractive industry activities on support for fracking is studied. While limited evidence is found for the impact of proximity to oil and gas wells or production on support for fracking, employment levels in the natural resources and mining sector in the respondent’s county and residence in an area experiencing active oil and gas development significantly increase support for fracking. The results highlight the role of spatial and community factors in shaping support for energy development.     

城镇化与工业化对能源强度影响的实证研究——基于截面相关和异质性回归系数的非平衡面板数据模型

城镇化、工业化对中国能源强度的影响如何?如何在快速推进城镇化、工业化进程的同时确保节能减排目标的实现?论文以能源强度指标代替传统的能源消费指标来反映能源综合利用效率,并应用考虑截面相关性和异质性回归系数的非平衡面板数据模型,使用共同相关效应组均值(CCEMG)估计方法对中国1978-2014年城镇化、工业化与能源强度之间的关系进行分析。研究结果表明:人均实际GDP增长1%,能源强度将会降低0.412%,工业化水平增长1%,能源强度将会上升0.630%,而由于生产消费等经济活动的增加、高度集中化以及规模经济的综合作用,使得城镇化对能源强度的影响并不确定。联系研究结论,本文提出政策建议:我国应加快产业结构升级,转变经济增长方式;构建绿色制造体系,推进"五化"协同发展;推进绿色、循环、低碳发展的新型城镇化建设,提高城镇化质量,提升我国整体的能源效率,确保节能减排目标的实现,推动经济全面、协调、可持续发展。     

Rebound effect and its decomposition – an analysis based on energy types in China

Rebound effect derived from energy efficiency improvement has been widely invested. However, most of studies focus on the rebound effect of the energy composite level and neither distinguish nor compare different energy types. We compare the differences in energy saving and energy rebound between primary and secondary energy sources, and further decompose the rebound effect into production rebound part and final demand component. To do so, we add a module for rebound into a comparative state China-CGE model. We design and test two simulation scenarios using the model. In Scenario 1, all production sectors’ energy efficiency of using primary energy increases by 5%. In Scenario 2, all production sectors’ energy efficiency of using secondary energy increases by 5%. The results show that Scenario 2 leads to more GDP growth and more energy saving. Our scenarios show rebound effects range between 9.6% and 27.9%, and in general are higher when energy efficiency of using primary energy sources is improved. Our decomposition analysis shows that improving energy efficiency in production sectors would stimulates energy use of final demand. Indeed, the consumption side has significant contribution to rebound in secondary energy use, especially in crude oil and gas. This study reveals that improving efficiency of using secondary energy is better than improving that of primary energy, both in terms of economic impact and energy rebound. And complementary policies that prevent energy services prices from falling too much can be adopted to reduce rebound. Controlling residential energy use could also be effective in reducing rebound, this has particular implication to economies in which residential energy consumption are far from saturation.