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Risk analysis for Shanghai's electric power system under multiple uncertainties

Author

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  • Piao, M.J.
  • Li, Y.P.
  • Huang, G.H.
  • Nie, S.

Abstract

In this study, a RIFP (robust interval-fuzzy programming) approach is developed for risk analysis of EPS (electric power systems) in association with multiple uncertainties expressed as fuzzy-boundary intervals and probability distributions. RIFP can provide an effective linkage between the pre-regulated policies and the associated corrective actions against any infeasibility arising from random outcomes. A RIFP-MEP (RIFP-based municipal-scale electric-power-system planning) model is formulated for the City of Shanghai, China. Various robustness levels and feasibility degrees are incorporated within the modeling formulation for enhancing the RIFP-MEP model capability. Solutions have been generated and are useful for supporting the Shanghai's energy supply, electricity generation, capacity expansion, and air-pollution control. Results can help decision makers to address the challenge generated in the processes of electric power production (such as imbalance between electricity supply and demand, the contradiction between air pollution emission and environmental protection); this allows an increased robustness in controlling system risk in the optimization process, which permits in-depth analyses of various conditions that are associated with different robustness levels of economic penalties when the promised policy targets are violated, and thus help the decision makers to identify desired electricity-generation schemes.

Suggested Citation

  • Piao, M.J. & Li, Y.P. & Huang, G.H. & Nie, S., 2015. "Risk analysis for Shanghai's electric power system under multiple uncertainties," Energy, Elsevier, vol. 87(C), pages 104-119.
  • Handle: RePEc:eee:energy:v:87:y:2015:i:c:p:104-119
    DOI: 10.1016/j.energy.2015.04.059
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    as
    1. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    2. Iniyan, S & Sumathy, K, 2000. "An optimal renewable energy model for various end-uses," Energy, Elsevier, vol. 25(6), pages 563-575.
    3. Grubb, Michael & Butler, Lucy & Twomey, Paul, 2006. "Diversity and security in UK electricity generation: The influence of low-carbon objectives," Energy Policy, Elsevier, vol. 34(18), pages 4050-4062, December.
    4. Huang, G. H. & Baetz, B. W. & Patry, G. G., 1995. "Grey fuzzy integer programming: An application to regional waste management planning under uncertainty," Socio-Economic Planning Sciences, Elsevier, vol. 29(1), pages 17-38, March.
    5. Zhu, Y. & Huang, G.H. & Li, Y.P. & He, L. & Zhang, X.X., 2011. "An interval full-infinite mixed-integer programming method for planning municipal energy systems - A case study of Beijing," Applied Energy, Elsevier, vol. 88(8), pages 2846-2862, August.
    6. Chen, W.T. & Li, Y.P. & Huang, G.H. & Chen, X. & Li, Y.F., 2010. "A two-stage inexact-stochastic programming model for planning carbon dioxide emission trading under uncertainty," Applied Energy, Elsevier, vol. 87(3), pages 1033-1047, March.
    7. Iniyan, S & Suganthi, L & Jagadeesan, T.R & Samuel, Anand A, 2000. "Reliability based socio economic optimal renewable energy model for India," Renewable Energy, Elsevier, vol. 19(1), pages 291-297.
    8. Collins, Julie, 2007. "Climate Change and Emissions Trading (Power Point)," 2007 Seminar, August 24, 2007, Wellington, New Zealand 97617, New Zealand Agricultural and Resource Economics Society.
    9. Li, M.W. & Li, Y.P. & Huang, G.H., 2011. "An interval-fuzzy two-stage stochastic programming model for planning carbon dioxide trading under uncertainty," Energy, Elsevier, vol. 36(9), pages 5677-5689.
    10. Yu, Chian-Son & Li, Han-Lin, 2000. "A robust optimization model for stochastic logistic problems," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 385-397, March.
    11. Li, Y.P. & Huang, G.H. & Chen, X., 2011. "Planning regional energy system in association with greenhouse gas mitigation under uncertainty," Applied Energy, Elsevier, vol. 88(3), pages 599-611, March.
    12. Li, Y.F. & Huang, G.H. & Li, Y.P. & Xu, Y. & Chen, W.T., 2010. "Regional-scale electric power system planning under uncertainty--A multistage interval-stochastic integer linear programming approach," Energy Policy, Elsevier, vol. 38(1), pages 475-490, January.
    13. Jimenez, Mariano & Arenas, Mar & Bilbao, Amelia & Rodri'guez, M. Victoria, 2007. "Linear programming with fuzzy parameters: An interactive method resolution," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1599-1609, March.
    14. Chen, C. & Li, Y.P. & Huang, G.H., 2013. "An inexact robust optimization method for supporting carbon dioxide emissions management in regional electric-power systems," Energy Economics, Elsevier, vol. 40(C), pages 441-456.
    15. Cai, Y.P. & Huang, G.H. & Yang, Z.F. & Tan, Q., 2009. "Identification of optimal strategies for energy management systems planning under multiple uncertainties," Applied Energy, Elsevier, vol. 86(4), pages 480-495, April.
    16. Huang, Guo H. & Baetz, Brian W. & Patry, Gilles G., 1995. "Grey integer programming: An application to waste management planning under uncertainty," European Journal of Operational Research, Elsevier, vol. 83(3), pages 594-620, June.
    17. Cormio, C. & Dicorato, M. & Minoia, A. & Trovato, M., 2003. "A regional energy planning methodology including renewable energy sources and environmental constraints," Renewable and Sustainable Energy Reviews, Elsevier, vol. 7(2), pages 99-130, April.
    18. Zhu, Y. & Li, Y.P. & Huang, G.H. & Fu, D.Z., 2013. "Modeling for planning municipal electric power systems associated with air pollution control – A case study of Beijing," Energy, Elsevier, vol. 60(C), pages 168-186.
    19. Chen, C. & Li, Y.P. & Huang, G.H. & Zhu, Y., 2012. "An inexact robust nonlinear optimization method for energy systems planning under uncertainty," Renewable Energy, Elsevier, vol. 47(C), pages 55-66.
    20. John M. Mulvey & Robert J. Vanderbei & Stavros A. Zenios, 1995. "Robust Optimization of Large-Scale Systems," Operations Research, INFORMS, vol. 43(2), pages 264-281, April.
    21. 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.
    22. Li, Y.F. & Li, Y.P. & Huang, G.H. & Chen, X., 2010. "Energy and environmental systems planning under uncertainty--An inexact fuzzy-stochastic programming approach," Applied Energy, Elsevier, vol. 87(10), pages 3189-3211, October.
    23. Lehtila, A & Pirila, P, 1996. "Reducing energy related emissions : Using an energy systems optimization model to support policy planning in Finland," Energy Policy, Elsevier, vol. 24(9), pages 805-819, September.
    24. Dawei Bai & Tamra Carpenter & John Mulvey, 1997. "Making a Case for Robust Optimization Models," Management Science, INFORMS, vol. 43(7), pages 895-907, July.
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