开放源对环境空气质量影响的评估技术与实例

开放源排放的颗粒物已经成为城市环境大气颗粒物的主要来源之一,介绍了其对环境空气质量影响的评估技术,采用开放源的动力学经验公式测算S市粉煤灰场、原煤堆场、土堆、沙石料堆4类开放源不同粒径颗粒物的起动风速及扩散距离,并利用箱模型(A值)和源解析(化学质量平衡法,CMB)模型测算开放源的区域年均起尘量及其对环境空气中颗粒物的贡献值.结果表明:开放源排放的颗粒物易升腾而且影响面积很大;S市区开放源类排放的小于100 μm的颗粒物约22.2×104 t/a,小于10 μm的颗粒物约15.8×104 t/a;开放源对环境空气中TSP的贡献值约370 μg/m3,质量浓度分担率达60%,对PM₁₀的贡献值约263 μg/m3,分担率达64%.      

上海崇明地区大气分形态汞污染特征

2014年3月~2015年2月对上海崇明东滩湿地公园的气态零价汞(GEM)、活性气态汞(RGM)和颗粒态汞(PBM)分别进行了为期1a的连续监测.GEM、RGM和PBM的年平均浓度分别为(2.75±1.13)ng·m~(-3)、(13.39±15.95)pg·m~(-3)和(21.89±40.42)pg·m~(-3),明显高于对应北半球背景值浓度.GEM浓度在夏季最高(3.65 ng·m~(-3)),受自然源排放影响较大,秋冬季较低,受人为源排放影响较大;RGM浓度在春季最高,冬季最低,主要受风速风向的影响;PBM浓度在秋冬季节明显高于其他季节,受秋冬季节较多的细颗粒物重污染过程的影响.GEM和PBM浓度均夜间较高,白天较低,主要受空气气团混合作用影响.RGM浓度在下午较高,主要是由于GEM在下午的光氧化作用加强,利于RGM的生成.GEM和PBM浓度在偏西风向上浓度较高,受上海、江苏等地人为源排放影响较大.RGM浓度在东南风向上浓度明显高于其他方向,这是因为RGM主要来源为人为排放,其浓度受风速影响较大,东南风向上平均风速较小,持续的弱风及停滞的空气不利于RGM的扩散.     

基于生命周期评价的风力发电机碳足迹分析

本文以我国市场占用率最高的2 MW双馈式风力发电机为研究对象,采用生命周期评价(LCA)方法,核算其全生命周期过程的碳足迹和总能量需求,分析风力发电机不同生命周期阶段的环境影响,识别其减碳潜力.研究结果表明,风力发电机生产阶段、运输阶段、运行阶段和废弃处理处置阶段的碳足迹(以CO2-eq计,下同)分别为1701 t、61 t、255 t和-325 t;各生命周期阶段的总能量需求分别为10413 GJ、701 GJ、1561.95 GJ和-1081 GJ.风力发电机的碳足迹和总能量需求主要来源于生产阶段,废弃处理处置阶段材料的回收利用有效的降低了生命周期的碳足迹和总能量需求.生产阶段的碳足迹和总能量需求分别占全生命周期碳足迹和总能量需求的101%和90%;废弃处置阶段对碳足迹和总能量需求的贡献为-19%和-10%.每1k Wh风力发电的碳足迹和总能量需求分别为20.7 g和0.14 MJ,风力发电机的能量回收期为0.79年.敏感性分析表明,风力发电机的质量和废弃处置阶段的金属回收率都是风力发电机总能量需求和碳足迹的影响因素.     

环境风对高层建筑楼梯井内火灾烟气运动特性的影响

环境风会影响高层建筑楼梯井内火灾烟气的运动特性.以广州市某地真实高层建筑楼梯井为原型,采用理论分析和数值模拟相结合的方法,利用火灾动力学仿真软件FDS建立该16层高层建筑楼梯井全尺寸FDS数值模型,对环境风作用下高层建筑楼梯井内火灾烟气运动规律展开数值模拟研究,分析不同窗户开合状态、不同风向和不同风速条件下环境风对高层...     

中国风电的时空分布特征和发展趋势

利用1990-2005年中国和英国风电发展数据,对两国风电的时空分布特征和发展趋势进行了比较分析。据英国风电发展的阶段性,把中国风电发展划分为试验性发展、规模发展、过渡发展3个阶段,并预测到2007年步入大规模发展阶段。因此,未来几年,中国风电场数目和规模将会快速增长,并且由集中走向高密度集中分布。据对影响风电场省级时空分布的自然、市场和政策共8个选择因子的主成分分析和系统聚类分析结果,将中国风电场按省级划分为3个区域和8个亚区域,对聚类结果进行逐步判别回判,结果表明准确率达92.6%。     

街道峡谷内汽车排放污染物浓度分布的观测与数值模拟

在上海某典型街道峡谷内按一定的空间布点,在一定时段内同时对各布点进行采样并做一氧化碳浓度分析,同时记录车辆种类、车流量、气象条件等,分析街道峡谷内污染物浓度的分布.运用风向频率加权(WDFW)方法,结合大气流动和污染物扩散的CFD模型进行数值模拟计算.结果表明,数值模拟结果和现场观测结果较吻合,建筑物低的一侧污染物浓度远高于建筑物高的一侧污染物浓度,两侧的污染物浓度随着高度的增加而降低.     

A convective wind resource model for Solar Vortex power generation

ABSTRACT

Climate change has increased the need for clean, nonpolluting energy sources to decrease dependence on fossil fuels. Alternative energy sources, mainly solar and horizontal wind, have been the primary focus for producing clean energy. New technologies are being developed, such as the Solar Vortex (SoV), which was developed at the Georgia Institute of Technology, and relies on a vertical wind resource to generate power. The National Renewable Energy Lab (NREL) has resource models representing solar and horizontal wind resources across the 48 United States. This research developed a vertical wind resource model that is comparable in resolution to NREL’s solar and horizontal wind resource models and uses the model for estimating power output for the SoV. This model complements NREL’s existing resource models and supports the deployment of an additional clean energy generation technology. The model was applied to Mesa, Arizona to find feasible sites for a small-scale vertical wind farm.     

Short-term wind speed forecasting based on random forest model combining ensemble empirical mode decomposition and improved harmony search algorithm

ABSTRACT

Wind speed forecasting plays an important role in power grid dispatching management. This article proposes a short-term wind speed forecasting method based on random forest model combining ensemble empirical modal decomposition and improved harmony search algorithm. First, the initial wind speed data set is decomposed into several ensemble empirical mode functions by EEMD, then feature extraction of each sub-modal IMF is performed using fast Fourier transform to solve the cycle of each sub-modal IMF. Next, combining the high-performance parameter optimization ability of the improved harmony search algorithm, two optimal parameters of random forest model, number of decision trees, and number of split features are determined. Finally, the random forest model is used to forecast the processing results of each submodal IMF. The proposed model is applied to the simulation analysis of historical wind data of Chaoyang District, Liaoning Province from April 27, 2015 to May 22, 2015. To illustrate the suitability and superiority of the EEMD-RF-IHS model, three types of models are used for comparison: single models including ANN, SVM, RF; EMD combination models including EMD-ANN, EMD-SVM, EMD-RF; EEMD combination models including EEMD-ANN, EEMD-SVM, EEMD-RF. The analysis results of evaluation indicators show that the proposed model can effectively forecast short-term wind data with high stability and precision, providing a reference for forecasting application in other industry fields.     

Multi-objective-based optimal transmission switching and demand response for managing congestion in hybrid power systems

ABSTRACT

This paper proposes a novel congestion management (CM) approach by using the optimal transmission switching (OTS) and demand response (DR) for a system with conventional thermal generators and renewable energy sources (RESs). In this paper, wind and solar PV units are considered as the RESs. The stochastic behavior of wind and solar PV powers are modeled by using the appropriate probability density functions (PDFs). The proposed CM methodology simultaneously optimizes the generation dispatch, demand response, and also the network topology of the power system. The OTS identifies the branches that should be taken out of service by significantly reducing the operating cost of the system while respecting the system security. Here, the total operating cost minimization/social welfare maximization and system losses minimization are considered as the objectives to be optimized. The proposed CM problem is solved using the multi-objective Jaya algorithm and it is used to determine a set of Pareto-optimal solutions. The Jaya algorithm is simple and it does not have any algorithmic-specific parameters to be tuned. This aspect reduces the designer’s effort in tuning the parameters to arrive at the optimum objective function value. A fuzzy logic-based approach is used to identify the best compromise solution. The effectiveness of the proposed CM approach is examined on modified IEEE 30 and practical Indian 75 bus test systems. The obtained simulation results are analyzed and they show the effectiveness of the proposed approach.     

Investigation of sustainable energy alternatives for powering remote communities in northern Ontario

ABSTRACT

Remote communities in the North of Ontario survive in isolation as their proximity to the southern industrial sector of the province limits their accessibility to the major grid. The lack of grid connection has led to antiquated methods of power generation which pollute the environment and deplete the planet of its natural resources. Aside from the primary means of electricity generation being by diesel generators, generation infrastructure is deteriorating due to age and the stagnation of the power supply has led to communities facing load restrictions. These challenges may be resolved by introducing clean energy alternatives and providing a fuel blend option. The primary energy sources investigated in this research are solar, wind, and hydrogen. To assess the viability of these energy production methods in Northern communities, an exergy analysis is employed as it utilizes both the first and second law of thermodynamics to determine systems’ efficiency and performance in the surroundings. Local weather patterns were used to determine the viability of using wind turbines, solar panels and/or hydrogen fuel cells in a remote community. Through analysis of the resources available at the community, it was determined that the hydrogen fuel cell was best suited to provide clean energy to the community. Wind resulted in low efficiency in the range of 2–3% while solar efficiencies resulted in ranges of 18 – 19%, as the seasonal variations between the three years is not very great. Due to the higher operating efficiencies observed of the PV panels it would also be an attractive alternative to diesel generators however, the lack of consistent operation above 30% efficiency throughout the year, resulted in hydrogen fuel cells being a better alternative.