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A long-term capacity expansion planning model for an electric power system integrating large-size renewable energy technologies

Authors
Min, DaikiRyu, Jong-hyunChoi, Dong Gu
Issue Date
Aug-2018
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Keywords
Electricity; Capacity expansion planning; System reliability; Renewable energy technology; Stochastic programming
Citation
COMPUTERS & OPERATIONS RESEARCH, v.96, pp.244 - 255
Journal Title
COMPUTERS & OPERATIONS RESEARCH
Volume
96
Start Page
244
End Page
255
URI
https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/3361
DOI
10.1016/j.cor.2017.10.006
ISSN
0305-0548
Abstract
The recent interest in reducing greenhouse gas emissions and the recent technical evolution of energy networks to smart grids have facilitated the integration of renewable energy technologies (RETs) into the electricity sector around the world. Although renewable energy provides substantial benefits for the climate and the economy, the large-size deployment of RETs could possibly hurt the level of power system reliability because of the RETs' technical limitations, intermittency, and non-dispatchability. Many power system planners and operators consider this a critical problem. This paper proposes a possible solution to this problem by designing a new stochastic optimization model for the long-term capacity expansion planning of a power system explicitly incorporating the uncertainty associated with RETs, and develops its solution by using the sample average approximation method. A numerical analysis then shows the effects of the large-scale integration of RETs on not only the power system's reliability level but also, and consequentially, its long-term capacity expansion planning. From the results of the numerical analysis, we show that our proposed model can develop a long-term capacity expansion plan that is more robust with respect to uncertain RETs and quantify the capacity the system requires to be reliable. (C) 2017 Elsevier Ltd. All rights reserved.
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