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A Multi-Objective Energy and Environmental Systems Planning Model: Management of Uncertainties and Risks for Shanxi Province, China

Author

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  • Changyu Zhou

    (School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China)

  • Guohe Huang

    (Institute for Energy, Environment and Sustainability Research, UR-NCEPU, North China Electric Power University, Beijing 102206, China)

  • Jiapei Chen

    (Institute for Energy, Environment and Sustainable Communities, UR-BNU, 3737 Wascana Parkway, Regina, SK S4S 0A2, Canada)

Abstract

In this study, a fuzzy chance-constrained fractional programming (FCFP) approach is developed to help tackle various uncertainties involved in electric power systems (EPSs) management. The FCFP approach is capable of solving ratio optimization decision problems in power systems associated with random and fuzzy information by chance-constrained programming (CCP) method, fuzzy measure programming, fractional programming (FP) into a general framework. It can tackle inexact information expressed as fuzzy set and probability distributions, comprehensively reflect the decision maker’s pessimistic and optimistic preferences, and balance dual objectives of system economy and sustainability. To demonstrate its applicability, FCFP approach is then applied to a case study of Shanxi Province, a typical coal-heavy electricity region in China. The results indicate that the FCFP approach reveals uncertain interactions among the decision maker’s preferences and various random variables. Reasonable solutions have been generated for Shanxi EPS management practices, which can provide strategies in mitigating pollutant emissions, reducing system costs, and promoting coalbed methane as an alternative energy source for coal-fired and plays an essential role in Shanxi’s municipal planning. The solutions will help decision makers generate alternatives in the event of the reducing coal-fired power generation and could be applicable in other coal-heavy electricity regions.

Suggested Citation

  • Changyu Zhou & Guohe Huang & Jiapei Chen, 2018. "A Multi-Objective Energy and Environmental Systems Planning Model: Management of Uncertainties and Risks for Shanxi Province, China," Energies, MDPI, vol. 11(10), pages 1-21, October.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:10:p:2723-:d:175026
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    1. Zhu, H. & Huang, W.W. & Huang, G.H., 2014. "Planning of regional energy systems: An inexact mixed-integer fractional programming model," Applied Energy, Elsevier, vol. 113(C), pages 500-514.
    2. Zhang, Y.M. & Huang, G.H. & Lin, Q.G. & Lu, H.W., 2012. "Integer fuzzy credibility constrained programming for power system management," Energy, Elsevier, vol. 38(1), pages 398-405.
    3. 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.
    4. Xiaogang Guo & Zhejing Bao & Zhijie Li & Wenjun Yan, 2018. "Adaptively Constrained Stochastic Model Predictive Control for the Optimal Dispatch of Microgrid," Energies, MDPI, vol. 11(1), pages 1-17, January.
    5. Wang, S. & Huang, G.H., 2015. "A multi-level Taguchi-factorial two-stage stochastic programming approach for characterization of parameter uncertainties and their interactions: An application to water resources management," European Journal of Operational Research, Elsevier, vol. 240(2), pages 572-581.
    6. 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.
    7. Kangji Li & Lei Pan & Wenping Xue & Hui Jiang & Hanping Mao, 2017. "Multi-Objective Optimization for Energy Performance Improvement of Residential Buildings: A Comparative Study," Energies, MDPI, vol. 10(2), pages 1-23, February.
    8. Zhou, Y. & Li, Y.P. & Huang, G.H., 2015. "Planning sustainable electric-power system with carbon emission abatement through CDM under uncertainty," Applied Energy, Elsevier, vol. 140(C), pages 350-364.
    9. Sarkar, Biswajit & Ganguly, Baishakhi & Sarkar, Mitali & Pareek, Sarla, 2016. "Effect of variable transportation and carbon emission in a three-echelon supply chain model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 112-128.
    10. Song, Han & Dotzauer, Erik & Thorin, Eva & Guziana, Bozena & Huopana, Tuomas & Yan, Jinyue, 2012. "A dynamic model to optimize a regional energy system with waste and crops as energy resources for greenhouse gases mitigation," Energy, Elsevier, vol. 46(1), pages 522-532.
    11. Mula, Josefa & Peidro, David & Poler, Raul, 2010. "The effectiveness of a fuzzy mathematical programming approach for supply chain production planning with fuzzy demand," International Journal of Production Economics, Elsevier, vol. 128(1), pages 136-143, November.
    12. 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.
    13. Rekik, Mouna & Abdelkafi, Achraf & Krichen, Lotfi, 2015. "A micro-grid ensuring multi-objective control strategy of a power electrical system for quality improvement," Energy, Elsevier, vol. 88(C), pages 351-363.
    14. Huang, G. H., 1998. "A hybrid inexact-stochastic water management model," European Journal of Operational Research, Elsevier, vol. 107(1), pages 137-158, May.
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