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.     

Economic dispatch of power system containing wind power and photovoltaic considering carbon trading and spare capacity variation

The drying up of the fossil energy sources and the damage from unchecked carbon emissions demand the development of low carbon economy, which promotes the development of new energy sources, such as wind power and photovoltaic. However, the direct connections of wind/photovoltaic power into power grid bring great impacts on power systems, thus affecting the security and stability of power system operations, which challenges the power system dispatching. In despite of many methods for power system dispatch, lack of the models, for power system containing wind power and photovoltaic considering carbon trading and spare capacity variation (PSCWPCCTSCV), restricts the further optimal operations of power systems. This paper studies the economic dispatch modeling problem of power system containing wind power and photovoltaic, establishes the model of economic dispatch of PSCWPCCTSCV. On this basis, adaptive immune genetic algorithm is applied to conduct the economic operation optimization, which can provide the optimal carbon trading price and the optimal power distribution coefficient. Finally, simulations based on the newly proposed models are made to illustrate the economic dispatch of PSCWPCCTSCV. The results show that optimization with the proposed model can not only weaken the volatility of the new energy effectively, but also reduce carbon emissions and reduce power generation costs.     

Coalition of injustice? Bodies,business, and the biosphere in struggles against unwanted land uses

Scholars of environmental injustice have pushed to see beyond the spatial distribution of environmental harms in studies of unwanted land uses. Building upon this work, this article examines how the complex geographies of environmental injustice play out in a coalition to prevent the construction of a coal-fired power plant in Surry County, Virginia. While spatially dispersed coalitions of negatively affected actors can strengthen efforts to prevent the construction of an unwanted land use, they can also perpetuate the environmental injustices surrounding it. To make this argument, particular attention is paid to the diverse reasons and ways differentially situated actors oppose an unwanted land use. It is demonstrated how the disparate concerns and differential tactics deployed by actors in coalitions against unwanted land uses are often embedded in and potentially contribute to longer histories of social injustice.     

利用卫星遥感评估广西壮族自治区SO_2减排成效

基于2005—2012年OMI卫星遥感PBL SO2柱浓度数据分析了广西壮族自治区SO2污染的时空格局和变化特征,并结合燃煤火电厂SO2排放模型估算与工业经济增长数据,在时间、空间尺度上分析了自治区内不同区域的SO2污染对火电厂烟气脱硫政策的响应以及所呈现出的减排成效。结果表明,广西因火电厂脱硫政策驱动的SO2污染改善具有显著的空间异质性,自治区内高污染区的SO2浓度在2011—2012年出现了显著下降,而低污染区的SO2浓度则在8年中持续增长;排放模型估算结果显示,烟气脱硫驱动的火电厂SO2减排贡献将在2008年后持续下降,而遥感观测结果显示,广西全区SO2半年浓度均值总体呈现波动上升趋势,2005—2012年浓度增加了8.6%、年均增长约0.9%;综合工业经济增长数据发现,近年来其他工业源的增量排放已给广西SO2减排带了新挑战,而这一变化仍未得到相关决策部门关注,存在明显缺陷的SO2统计排放量数据尚未得到修正。针对上述污染变化新特征,政府相关部门应引起足够重视,尽快更新完善污染源信息并启动针对其他污染源的限排措施,以确保环境持续改善。     

燃煤电厂大气污染物排放考核时间间隔的建议

新的《火电厂大气污染物排放标准》和新《环境保护法》实施后,燃煤火电企业的依法治企自觉性不断提高,但由于不同的环保管理文件对超标处罚依据和处罚手段不同,造成政府对企业处罚的自由裁量权加大,对企业造成一定的压力与困惑。结合企业实际运行情况对燃煤电厂大气污染物排放考核时间间隔提出建议。     

燃煤电厂烟尘超低排放技术措施研究

针对越来越严格的环保要求,介绍了原有的除尘技术,并对除尘器新技术改造方案进行了说明,其中重点对电袋复合代替静电除尘技术、在静电除尘器中增置旋转电极、更改工频电源为高频电源、在电除尘器前加装低温换热器、脱硫后增加湿式电除尘器技术等方案进行比较分析。为了达到超低排放要求,对不同的烟尘超低排放实践工艺进行了说明,并结合东部沿海地区可再生能源发展空间有限的实际情况,提出加快推广超低排放技术在现有燃煤电厂的应用,实现传统煤电产业和环保产业的转型升级。     

基于分布型电力系统的 PSO 优化设计

优化了传统粒子群算法,运用了混沌算法对粒子做初始化,优化了传统粒子群算法的收敛特性,并在算法的优化过程中,增加了混沌干扰元素对整体最优化极值做混沌干扰,将符合杂交几率的优化粒子做杂交处理,提高了粒子群的种类,增强了粒子群算法的搜寻水平。并通过IEEE33节点的分布型电力系统做无功优化仿真验证,通过比较,验证了优化算法的优越性与准确性。     

宁夏地区光伏发电环境效益分析及建模

在阐述了宁夏地区光伏发电发展的优势及发展现状的基础上,分析了光伏发电开发利用对宁夏生态环境产生的积极和消极的影响,并为降低消极影响提出了相应的对策;为了定量直观的评估光伏发电积极影响和消极影响所产生的环境效益,分别建立了节能减排、防风固沙和土地增值、景观效应、植被恢复费用、噪声污染超标罚款、光污染费用等价值模型及光伏发电总的生态环境效益价值模型;最后以中电投宁夏能源铝中卫香山光伏电站为例进行计算验证,结果表明模型的合理性和准确性,同时光伏电站的节能减排效益显著。相对于传统的火力发电,表现了优越的环境效益。     

甘肃省风力发电现状及发展对策

介绍了甘肃省的风力资源及风力发电的发展现状,重点阐述了白银地区、玉门地区、酒泉瓜州、金昌地区、敦煌地区和武威地区等几个具有代表性地区的风能资源优势及风电建设情况,指出了甘肃省风力发电在技术和政策等方面目前还存在的主要问题,分析了产生这些问题的原因,提出了促进甘肃省风力发电事业发展的对策。     

燃机电厂噪声模拟时SoundPLAN声源模型的简化

燃机电厂一般靠近用电负荷或城镇建设,为了有效地控制噪声,在燃机电厂项目的设计、环评等阶段对其噪声影响进行合理的模拟从而提出相应的降噪方案是非常必要的。结合国家标准,对燃机电厂的敏感目标和主要噪声的声源特性进行了总结。通过对比声源类型、中心频率的设置对模拟结果产生的影响,探讨了在应用SoundP-LAN软件对燃机电厂的噪声模拟时如何简化设置声源模型的问题,为今后的噪声模拟评估工作提供参考。