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来源类型Conference or Workshop Item
规范类型其他
Applying Load Factors to the Mean-Variance Analysis for Fuel Diversification.
Ruangpattana, Suriya; Gotham, Douglas J; Muthuraman, Kumar; Preckel, Paul V; Rardin, Ronald L
发表日期2008-05
出版年2008
语种英语
摘要Fuel diversification implies the selection of a mix of generation technologies for long-term electricity generation. The goal is to strike a good balance between reduced costs and reduced risk. The method of analysis that has been advocated and adopted for such studies is the mean-variance portfolio analysis pioneered by Markowitz (1952). However the standard meanvariance methodology, does not account for the ability of various fuels/technologies to adapt to varying loads. Such analysis often provides results that are easily dismissed by regulators and practitioners as unacceptable, since load cycles play critical roles in fuel selection. To account for such issues and still retain the convenience and elegance of the mean-variance approach, we propose a variant of the mean-variance analysis using the decomposition of the load into various types and utilizing the load factors of each load type. We also present examples using real data for the state of Indiana and demonstrate the ability of the model in providing useful insights.
特色分类HG4900 By region or country$QA0299 Analysis. Including analytical methods connected with physical problems$T0057.6 Operations research. Systems analysis$TA0168 Systems engineering$TK1001 Production of electric energy or power. Powerplants. Central stations
关键词Indiana fuel diversification fuel selection long-term electricity generation mean-variance portfolio analysis electricity supply industry fuel economy power generation economics risk management
URLhttp://sro.sussex.ac.uk/id/eprint/39807/
来源智库Science Policy Research Unit (United Kingdom)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/467458
推荐引用方式
GB/T 7714
Ruangpattana, Suriya,Gotham, Douglas J,Muthuraman, Kumar,et al. Applying Load Factors to the Mean-Variance Analysis for Fuel Diversification.. 2008.
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