使用广义线性模型对Eskom燃煤发电站的二氧化氮排放进行建模

IF 0.6 4区 工程技术 Q4 ENERGY & FUELS
Delson Chikobvu, Mpendulo Mamba
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引用次数: 0

摘要

本文的目的是确定广义线性模型(GLM)是否比传统的简单线性回归模型更好,当适用于Eskom的13个燃煤发电站在发电过程中排放到大气中的二氧化氮(NO2)时。通过正向和反向选择模型变量,拟合了NO2排放数据的GLM。采用回归分析拟合了一个类似的模型进行比较。结果表明,GLM可以用来预测和解释南非燃煤发电站的NO2排放。通过包括在残差中显示改进的方差行为的图在内的诊断措施,发现对数正态模型是更好的模型。各种变量,如发送的电量(以千瓦时为单位),发电站的年龄(以年为单位),使用的发电站,以及相互作用的术语,如电力和站,年龄和站,可以用来描述/预测Eskom燃煤发电站的二氧化氮排放量(以吨为单位)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modelling NO2 emissions from Eskom’s coal fired power stations using Generalised Linear Models
The aim of this paper is to determine if a Generalised Linear Model (GLM) is a better model over the traditional simple linear regression when fitted to nitrogen dioxide (NO2) emitted into the atmosphere during the production of electricity from 13 Eskom’s coal fuelled power stations. A GLM was fitted to the NO2 emission data using forward and backward selection of variables for the models. A similar model using regression analysis was fitted for comparison. The results show that a GLM can be used to predict and explain NO2 emissions from coal fired electricity stations in South Africa. The Lognormal model was found to be the better model by diagnostic measures including plots that showed improved variance behaviour in the residuals. Various variables such as amount of electricity sent out (in GWhs), age of power station (in years), power station used, and interaction terms such as electricity and station, Age and station can be used in describing/ predicting NO2 emissions (in tons) from Eskom’s coal fuelled power stations.
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来源期刊
CiteScore
3.00
自引率
0.00%
发文量
16
审稿时长
6 months
期刊介绍: The journal has a regional focus on southern Africa. Manuscripts that are accepted for consideration to publish in the journal must address energy issues in southern Africa or have a clear component relevant to southern Africa, including research that was set-up or designed in the region. The southern African region is considered to be constituted by the following fifteen (15) countries: Angola, Botswana, Democratic Republic of Congo, Lesotho, Malawi, Madagascar, Mauritius, Mozambique, Namibia, Seychelles, South Africa, Swaziland, Tanzania, Zambia and Zimbabwe. Within this broad field of energy research, topics of particular interest include energy efficiency, modelling, renewable energy, poverty, sustainable development, climate change mitigation, energy security, energy policy, energy governance, markets, technology and innovation.
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