电网企业废铅蓄电池回收模式与趋势分析

基于电网企业的废铅蓄电池产生和处置现状,结合我国废铅蓄电池回收工作进展,以华北地区为重点研究区域,提出委托回收、联合回收和自主回收3种废铅蓄电池回收利用模式.对于具有废铅蓄电池资质单位较多的地区,优先考虑全部委托回收模式,有助于降低法律风险,并节约人力、物力.对于环保管理相对创新和管理理念先进的地区,考虑依托地市公司建设收集网点,由省公司统一管理和转移,并联合有资质的回收企业开展回收.对于以营利为目的,期望扩大回收业务的地区,建议考虑自主回收模式.无论采用何种模式,国家电网及其电网企业应建立和完善废铅蓄电池的信息化系统,将电池采购、维护及产废信息、台账记录、管理计划、转移联单等信息纳入系统进行管理,并实现与政府部门危险废物信息系统的数据对接.     

1000MW近零排放燃煤机组重金属排放及分布特征

采用EPA 29方法对国华寿光电厂2号1000MW超超临界燃煤机组污染物控制单元进行采样,开展了重金属污染物(As、Pb、Se、Cd)全流程监测.建立了包括气体/固体/液体中重金属的燃煤过程中质量平衡,并考察了重金属在机组中的富集与分布特征.结果表明:该机组烟气排放的重金属含量相对较低,100%负荷时As、Se、Pb、Cd排放浓度分别为1.11,0.59,0.33和0.01 μg/m³,45%负荷时相关重金属排放和100%负荷接近.给出了不同负荷下各种重金属在燃煤机组的分布,燃烧后Pb、Se、Cd主要富集到飞灰中,但低负荷时底渣中Se和Cd的比例明显升高.APCDs中,ESP对烟气中As、Pb、Se、Cd四种元素的脱除率均达到了97%以上,不同负荷下WFGD和WESP对这些重金属具有深度脱除的效果.     

双碳目标下电力系统转型对产业部门影响评估——以粤港澳大湾区为例

通过细化机组级燃煤发电财务状况建模,测算了提前退役、灵活性调整、限制和停止新增等情景下煤电搁浅资产风险,明确了不同情景下导致搁浅资产规模及时空分布情况.结果表明:存量煤电机组是引起搁浅资产的主体,控制新增煤电有助于降低搁浅资产风险,提前退役、灵活性调整情景下中国现存和新增煤电搁浅资产总规模分别为1.90万亿和3.98万亿元;不同转型情景导致煤电搁浅资产的年际分布差异明显,提前退役搁浅压力主要集中于2030~2040年间,灵活性调整情景下则集中于2021~2035年间;煤电搁浅资产空间分布极不均衡,山东、内蒙古、江苏等10个煤电大省搁浅资产规模占全国的67%和70%.因此,煤电低碳转型需审慎决策,重视提前退役造成的煤电资产搁浅,更要防范和控制灵活性调整导致的煤电资产减值,重点关注山东、内蒙古、新疆、江苏等重点省份,制定因地制宜的煤电转型策略,帮助电力相关企业及政府等进行减排政策选择.     

A火电厂氨站喷淋系统改造

液氨在储存和使用过程中存在较大的安全风险,极易燃,且有毒,对人体伤害较大,而且氨一旦产生大量泄漏,会对环境构成严重危害。通过安全评价的手段,查找出A火电厂氨站喷淋装置设置不合理,存在的安全隐患。针对此隐患,A火电厂有关部门按照相关设计标准,提出了对氨站喷淋装置的改、扩建方案,并于改造完成后对氨站喷淋装置试运行,改造后的喷淋装置能够达到要求,但是还存在一些不足,需要进一步改进。     

排污许可审计式合规核查研析——以火电企业为例

针对排污单位证后守法情况,以火电企业为例,设计了三阶段的“审计式”合规核查机制,主管部门可以依次对执行报告及其支撑材料、自行监测和台账记录等内容进行完整性、规范性、逻辑性核查,以识别企业在按证守法方面存在的问题,发现企业存在的未按期提交执行报告、未按技术规范要求计算排放量、台账数据不合逻辑等潜在的线索,为下一步进行现场检查及现场执法提供指引。     

Energy consumption analysis of ABS plastic parts injected in a hybrid injection moulding machine

The energy analysis of injection moulding processes is influenced by complex interactions amongst the moulded part, its material, the injection machine, the process parameters and the environmental conditions. The availability of energy usage analyses that comprehend information on specific materials and machine kind is limited. This paper reports a study that estimates and analyses the power usage profile (PUP), the specific energy consumption (SEC), and the energy distribution at an operation level of two different injected parts made of acrylonitrile-butadiene-styrene and produced in a hybrid injection moulding machine. The methodology followed by the authors incorporates an experiment carried out in an industrial facility. A large sample size, and data-acquisition and data post-processing processes to obtain an accurate PUP and SEC are used. A breakdown of the energy consumed by the injection moulding process of the parts studied at an operation level using Sankey diagrams is discussed. The study results are used to identify strategies to reduce the energy consumed by the processes. The methodology employed, and the strategies reported could be used with other plastic parts regardless of the material and machine used. The results reported are new experimental data useful input for theoretical models.     

Support vector machine based prediction of photovoltaic module and power station parameters

ABSTRACT

The uncertainty in the output power of the photovoltaic (PV) power generation station due to variation in meteorological parameters is of serious concern. An accurate output power prediction of a PV system helps in better design and planning. The present study is carried out for the prediction of output power of PV generating station by using Support Vector Machines. Two cases are considered in the present study for prediction. Case-I deals with the prediction of PV module parameters such as V_oc, I_sh, R_s, R_sh, I_max, V_max, P_max, and case-II deals with the prediction of power generation parameters such as P_DC, P_AC, and system efficiency. Historical data of PV power station with an installed capacity of 10 MW and weather information are used as input to develop four different seasons-based SVM models for all parameters. The performance results of the models are presented in terms of Mean Relative Error (MRE) and Root Mean Square Error (RMSE). Additionally, the performance results obtained with polynomial and Radial Based Function kernel are also compared to show that which kernel has better prediction accuracy, and practicability. The result shows that the minimum average RMSE and MRE for case-I with Radial Based Function kernel are 0.034%, 0.055%, 0.002%, 1.726%, 0.044%, 0.047%, 2.342%, and 0.005%, 0.014%, 0.079%, 0.885%, 0.005%, 0.007%, 0.013%, and for case-II with poly kernel are 0.014%, 0.016%, 0.149% and 0.011%, 0.0175, 1.03%, respectively. The present study will be helpful to provide technical guidance to the prediction of the PV power System.     

An interval type-2 fuzzy stochastic approach for regional-scale electric power system under parameter uncertainty

In this study, an interval type-2 fuzzy stochastic linear programming method (IT2FSLP) is developed to support regional-scale electric power system (REM) planning. The IT2FSLP-REM model is based on an integration of interval type-2 fuzzy sets boundary programming and stochastic linear programming techniques enable it to have robust abilities to the deal with uncertainties expressed as type-2 fuzzy intervals and probabilistic distributions within a general optimization framework. Moreover, it can reflect dynamic decisions for energy supply and energy conversion processes, as well as provide capacity expansion options with multiple periods. The developed model is applied to a case of planning regional-scale energy and environmental systems to demonstrate its applicability. Based on a two-step solution algorithm, reasonable solutions have been obtained, which reflect tradeoffs among economic cost, environmental requirements, and energy-supply security. Thus, the lower and upper solutions of IT2FSLP-REM would then help energy authorities adjust or justify allocation patterns of regional energy resources and services.     

污泥协同处置技术及应用分析

对我国火电厂、水泥窑在污泥协同处置方面的基本情况进行了简要介绍和分析,并对气化炉、烧结窑炉和冶金高炉等炉窑在污泥协同处置方面的应用技术进行了简要介绍。指出我国火电厂和水泥窑协同处置能力较强,但由于经济效益问题,企业协同处置污泥的积极性不高,致使行业实际处理量远小于其处理能力。同时指出气化炉、烧结窑炉和冶金高炉等其他炉窑在协同处置工业污泥方面具有适用范围广、就地处置成本低等优势,需要对其进行扩展性、挖潜性研发。     

不同驯化方式对以苯酚为基质的微生物燃料电池产电性能的影响

以厌氧污泥作为初始接种体,构建了单室微生物燃料电池（MFCs）,考察了梯度驯化、直接驯化和间接驯化3种不同驯化方式对MFC降解苯酚及产电性能的影响。结果表明,MFC在闭路状态下对苯酚的降解速率比MFC在开路状态下的苯酚降解速率加快10%～20%,说明MFC在产电的同时,可加速苯酚的降解。当以600 mg/L的苯酚溶液为单一燃料,反应68 h后,3种驯化方式下的MFC对苯酚降解率都达到90%以上。相对于其他2种驯化方式,梯度驯化条件最有利于MFC产电性能的提高及苯酚的降解,其最大输出功率为31.3 mW/m2,降解速率提高了7%～20%。