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Development of an inexact optimization model for coupled coal and power management in North China

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  • Liu, Y.
  • Huang, G.H.
  • Cai, Y.P.
  • Cheng, G.H.
  • Niu, Y.T.
  • An, K.

Abstract

In this study, an inexact coupled coal and power management (ICCPM) model was developed for planning coupled coal and power management systems through integrating chance-constrained programming (CCP), interval linear programming (ILP) and mixed integer linear programming (MILP) techniques. The ICCPM model can effectively handle uncertainties presented in terms of probability density functions and intervals. It can also facilitate dynamic analysis of capacity expansions, facility installation and coal inventory planning within a multi-period and multi-option context. Complexities in coupled coal and power management systems can be systematically reflected in this model, thus applicability of the modeling process would be highly enhanced. The developed ICCPM model was applied to a case of long-term coupled coal and power management systems planning in north China. Interval solutions associated with different risk levels of constraint violations have been obtained, which can be used for generating decision alternatives and helping identify desired policies. The generated results can also provide desired solutions for coal and power generation, capacity initiation and expansion, and coal blending with a minimized system cost, a maximized system reliability and a maximized coal transportation security. Tradeoffs between system costs and constraint-violation risks can also be tackled.

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  • Liu, Y. & Huang, G.H. & Cai, Y.P. & Cheng, G.H. & Niu, Y.T. & An, K., 2009. "Development of an inexact optimization model for coupled coal and power management in North China," Energy Policy, Elsevier, vol. 37(11), pages 4345-4363, November.
    • Handle: RePEc:eee:enepol:v:37:y:2009:i:11:p:4345-4363
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    5. Dong, C. & Huang, G.H. & Cai, Y.P. & Liu, Y., 2012. "An inexact optimization modeling approach for supporting energy systems planning and air pollution mitigation in Beijing city," Energy, Elsevier, vol. 37(1), pages 673-688.
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