Two-stage stochastic programming model for the regional-scale electricity planning under demand uncertainty

研究成果: Article同行評審

15 引文 斯高帕斯(Scopus)

摘要

Traditional electricity supply planning models regard the electricity demand as a deterministic parameter and require the total power output to satisfy the aggregate electricity demand. But in today's world, the electric system planners are facing tremendously complex environments full of uncertainties, where electricity demand is a key source of uncertainty. In addition, electricity demand patterns are considerably different for different regions. This paper developed a multi-region optimization model based on two-stage stochastic programming framework to incorporate the demand uncertainty. Furthermore, the decision tree method and Monte Carlo simulation approach are integrated into the model to simplify electricity demands in the form of nodes and determine the values and probabilities. The proposed model was successfully applied to a real case study (i.e. Taiwan's electricity sector) to show its applicability. Detail simulation results were presented and compared with those generated by a deterministic model. Finally, the long-term electricity development roadmap at a regional level could be provided on the basis of our simulation results.

原文English
頁(從 - 到)1145-1157
頁數13
期刊Energy
116
DOIs
出版狀態Published - 2016 十二月 1

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Building and Construction
  • Pollution
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

指紋 深入研究「Two-stage stochastic programming model for the regional-scale electricity planning under demand uncertainty」主題。共同形成了獨特的指紋。

引用此