A grey-forecasting interval-parameter mixed-integer programming approach for integrated electric-environmental management–A case study of Beijing

Xingwei Wang, Yanpeng Cai, Jiajun Chen and Chao Dai

Energy, 2013, vol. 63, issue C, 334-344

Abstract: In this study, a GFIPMIP (grey-forecasting interval-parameter mixed-integer programming) approach was developed for supporting IEEM (integrated electric-environmental management) in Beijing. It was an attempt to incorporate an energy-forecasting model within a general modeling framework at the municipal level. The developed GFIPMIP model can not only forecast electric demands, but also reflect dynamic, interactive, and uncertain characteristics of the IEEM system in Beijing. Moreover, it can address issues regarding power supply, and emission reduction of atmospheric pollutants and GHG (greenhouse gas). Optimal solutions were obtained related to power generation patterns and facility capacity expansion schemes under a series of system constraints. Two scenarios were analyzed based on multiple environmental policies. The results were useful for helping decision makers identify desired management strategies to guarantee the city's power supply and mitigate emissions of GHG and atmospheric pollutants. The results also suggested that the developed GFIPMIP model be applicable to similar engineering problems.

Keywords: Interval-parameter programming; Mixed-integer programming; Grey-forecasting model; Integrated electric-environmental management; Beijing; Uncertainties (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:63:y:2013:i:c:p:334-344

DOI: 10.1016/j.energy.2013.10.054

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