Journal
JOURNAL OF PROCESS CONTROL
Volume 47, Issue -, Pages 58-77Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jprocont.2016.08.011
Keywords
Energy systems management; Air pollution control; Renewable energy; Fuzzy distributions; Multiple scenarios analysis; Uncertainty
Funding
- Fundamental Research Funds for the Central Universities [2015XS95]
- Program for Innovative Research Team in University [IRT1127]
- 111 Project [B14008]
- Natural Science and Engineering Research Council of Canada
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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. (C) 2016 Elsevier Ltd. All rights reserved.
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