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Research Papers: Energy Systems Analysis

A Novel Inexact Two-Stage Stochastic Robust-Compensation Model for Electric Supply Environmental Management Under Uncertainty

[+] Author and Article Information
W. Li

Professor
China-Canada Energy and
Environmental Research Center,
North China Electric Power University,
Beijing 102206, China
e-mail: weili1027@gmail.com

S. X. Liu

China-Canada Energy and
Environmental Research Center,
North China Electric Power University,
Beijing 102206, China
e-mail: sanxing1113@163.com

Z. H. Fu

China-Canada Energy and
Environmental Research Center,
North China Electric Power University,
Beijing 102206, China
e-mail: fzhncepu@gmail.com

H. D. Shi

China Academy of Environmental Science,
Beijing 100012, China
e-mail: shihd@craes.org.cn

Y. L. Xie

China-Canada Energy and
Environmental Research Center,
North China Electric Power University,
Beijing 102206, China
e-mail: xieyulei850228@gmail.com

1Corresponding author.

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received July 10, 2014; final manuscript received June 10, 2015; published online June 30, 2015. Assoc. Editor: Kau-Fui Wong.

J. Energy Resour. Technol 137(6), 062001 (Jun 30, 2015) (10 pages) Paper No: JERT-14-1210; doi: 10.1115/1.4030844 History: Received July 10, 2014

In this study, a novel inexact two-stage stochastic robust-compensation programming (ITSP-RC) model is developed for CO2 emission reduction management under uncertainties. This model is attempted to integrate ITSP and stochastic RC programming into a general framework and apply the ITSP-RC for power management and CO2 emission reduction management, such that the developed model can tackle uncertainties described in terms of interval values and probability distributions over a two-stage context. Moreover, it can reflect dynamic and randomness of the energy systems during the planning horizon. The developed method has been applied to a case to solve CO2 emission management problem in electric supply environmental management. A number of scenarios corresponding to different adoption rate levels of carbon capture, utilization, and storage technology are examined. With the RC programming, regional energy systems would have a stable financial budget. The result suggests that the methodology is applicable for reflecting complexities of large-scale energy management systems and addressing CO2 emissions reduction issue with the planning period.

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Figures

Grahic Jump Location
Fig. 1

Framework of ITSP-RC model

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Fig. 2

Optimized power generation amount without considering carbon treatment: (a) low demand level, (b) medium demand level, and (c) high demand level. (“T,” “H,” “W,” and “S” denote “thermal power,” “hydropower,” “wind power,” and “solar power,” respectively.)

Grahic Jump Location
Fig. 3

Amount of optimal power generation under 20% carbon treatment: (a) low demand level, (b) medium demand level, and (c) high demand level

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Fig. 4

Solutions of power generation under different scenarios in September

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Fig. 5

Optimal amount of CO2 emission under different scenarios

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Fig. 6

Total costs under different scenarios

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