An optimization model design for energy systems planning and management under considering air pollution control in Tangshan City, China. (November 2016)
- Record Type:
- Journal Article
- Title:
- An optimization model design for energy systems planning and management under considering air pollution control in Tangshan City, China. (November 2016)
- Main Title:
- An optimization model design for energy systems planning and management under considering air pollution control in Tangshan City, China
- Authors:
- Zhen, Jiliang
Huang, GuoHe
Li, Wei
Wu, ChuanBao
Liu, Zhengping - Abstract:
- Highlights: An interval fuzzy mixed integer programming (IFMIP) model is designed. Uncertainties are presented as both interval values and fuzzy distributions. Air pollution control with various emission-mitigation scenarios is considered. Results could support the sustainable development of society and environment. Abstract: In this study, an interval-parameter fuzzy programming mixed integer programming method (IFMIP) is designed for supporting the planning of energy systems management (ESM) and air pollution mitigation control under multiple uncertainties. The IFMIP-ESM model is based on an integration of interval-parameter programming (IPP), fuzzy programming (FP), and mixed-integer programming (MIP), which can reflect multiple uncertainties presented as both interval values and fuzzy distributions numbers. Moreover, it can successfully identify dynamics of capacity expansion schemes, reflect dual dynamics in terms of interval membership function, and analyze various emission-mitigation scenarios through incorporating energy and environmental policies. The designed model is applied to a case of energy systems management in Tangshan City, China, and the results indicate that reasonable solutions obtained from the model would be helpful for decision makers to effectively (a) adjust the allocation patterns of energy resources and transform the patterns of energy consumption and economic development, (b) facilitate the implement of air pollution control action plan, and (c)Highlights: An interval fuzzy mixed integer programming (IFMIP) model is designed. Uncertainties are presented as both interval values and fuzzy distributions. Air pollution control with various emission-mitigation scenarios is considered. Results could support the sustainable development of society and environment. Abstract: In this study, an interval-parameter fuzzy programming mixed integer programming method (IFMIP) is designed for supporting the planning of energy systems management (ESM) and air pollution mitigation control under multiple uncertainties. The IFMIP-ESM model is based on an integration of interval-parameter programming (IPP), fuzzy programming (FP), and mixed-integer programming (MIP), which can reflect multiple uncertainties presented as both interval values and fuzzy distributions numbers. Moreover, it can successfully identify dynamics of capacity expansion schemes, reflect dual dynamics in terms of interval membership function, and analyze various emission-mitigation scenarios through incorporating energy and environmental policies. The designed model is applied to a case of energy systems management in Tangshan City, China, and the results indicate that reasonable solutions obtained from the model would be helpful for decision makers to effectively (a) adjust the allocation patterns of energy resources and transform the patterns of energy consumption and economic development, (b) facilitate the implement of air pollution control action plan, and (c) analysis dynamic interactions among system cost, energy-supply security, and environmental requirement. … (more)
- Is Part Of:
- Journal of process control. Volume 47(2016:Nov.)
- Journal:
- Journal of process control
- Issue:
- Volume 47(2016:Nov.)
- Issue Display:
- Volume 47 (2016)
- Year:
- 2016
- Volume:
- 47
- Issue Sort Value:
- 2016-0047-0000-0000
- Page Start:
- 58
- Page End:
- 77
- Publication Date:
- 2016-11
- Subjects:
- Energy systems management -- Air pollution control -- Renewable energy -- Fuzzy distributions -- Multiple scenarios analysis -- Uncertainty
Process control -- Periodicals
Fabrication -- Contrôle -- Périodiques
Process control
Periodicals
Electronic journals
660.281 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09591524 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jprocont.2016.08.011 ↗
- Languages:
- English
- ISSNs:
- 0959-1524
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5042.645000
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British Library HMNTS - ELD Digital store - Ingest File:
- 285.xml