摘要
全球低碳化进程方兴未艾,低碳电力的发展模式与技术方案层出不穷,亟须对其生产运营效率进行准确评价。文中提出一种以低碳电力效率指数为核心的低碳电力生产效率评估新思路。在超效率数据包络分析(DEA)的基础上,充分考虑模型非径向松弛变量带来的非期望产出误差以及低碳评价指标间的信息交叠,利用主成分分析法对超效率DEA模型进行改进,并引入低碳投入偏好因子与低碳投入主成分,重构DEA优化模型目标函数以提高模型精度。最后通过具体算例完成不同省(市)间低碳电力生产效率水平测算、综合评价、模型对比及参数灵敏度分析,从而验证了评估模型的有效性和准确性。
With the global low-carbon revolution growing rapidly,the development patterns and technical plans of low-carbon electricity emerge in an endless stream.It is imperative to make precise evaluation of the production efficiency of low-carbon electricity.A new line of thought for low-carbon electricity benefits evaluation with the low-carbon index as the core is proposed.Based on the data envelopment analysis(DEA),the super efficiency DEA model is improved by principal component analysis,with the unexpected error caused by non-radial relaxation variables and the information overlap existing in low-carbon evaluation indices considered.The low-carbon input preference factor and low-carbon input principal component are also introduced while the objective function of optimization model is modified to improve model accuracy.Finally an example is given to prove the validity and correctness of the model with low-carbon electricity production efficiency calculation, comprehensive evaluation,model comparison and parameter sensitivity analysis of the low-carbon power systems in different provinces (cities).
出处
《电力系统自动化》
EI
CSCD
北大核心
2014年第17期170-176,共7页
Automation of Electric Power Systems
基金
国家自然科学基金资助项目(51377103)
南方电网公司重点科技项目(K-GD2011-420)~~
关键词
低碳电力
生产效率
数据包络分析
主成分分析
低碳投入因子
低碳投入成分
low-carbon electricity
production efficiency
data envelopment analysis(DEA)
principal component analysis
low-carbon input preference factor
low-carbon input principal component
