IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i8p2108-d163565.html
   My bibliography  Save this article

A Stochastic Inexact Robust Model for Regional Energy System Management and Emission Reduction Potential Analysis—A Case Study of Zibo City, China

Author

Listed:
  • Yulei Xie

    (School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China)

  • Linrui Wang

    (The Vehicle Pollution Prevention and Control Center of Jinan, Jinan Environmental Protection Bureau, Jinan 250099, Shandong, China)

  • Guohe Huang

    (Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, SK S4S 0A2, Canada)

  • Dehong Xia

    (School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China)

  • Ling Ji

    (School of Economics and Management, Beijing University of Technology, Beijing 100124, China)

Abstract

In this study, in order to improve regional energy system adjustment, a multistage stochastic inexact robust programming (MSIRP) is proposed for electric-power generation planning and structure adjustment management under uncertainty. Scenario-based inexact multistage stochastic programming and stochastic robust optimization were integrated into general programming to reflect uncertainties that were expressed as interval values and probability distributions in the objective function and constraints. An MSIRP-based energy system optimization model is proposed for electric-power structure management of Zibo City in Shandong Province, China. Three power demand scenarios associated with electric-power structure adjustment, imported electricity, and emission reduction were designed to obtain multiple decision schemes for supporting regional sustainable energy system development. The power generation schemes, imported electricity, and emissions of CO 2 and air pollutants were analyzed. The results indicated that the model can effectively not only provide a more stable energy supply strategies and electric-power structure adjustment schemes, but also improve the balanced development between conventional and new clear power generation technologies under uncertainty.

Suggested Citation

  • Yulei Xie & Linrui Wang & Guohe Huang & Dehong Xia & Ling Ji, 2018. "A Stochastic Inexact Robust Model for Regional Energy System Management and Emission Reduction Potential Analysis—A Case Study of Zibo City, China," Energies, MDPI, vol. 11(8), pages 1-24, August.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:8:p:2108-:d:163565
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/8/2108/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/8/2108/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mackay, R. M. & Probert, S. D., 1995. "Energy and environmental policies of the developed and developing countries within the evolving Oceania and South-East Asia trading bloc," Applied Energy, Elsevier, vol. 51(4), pages 369-400.
    2. Cai, Y.P. & Huang, G.H. & Yang, Z.F. & Lin, Q.G. & Tan, Q., 2009. "Community-scale renewable energy systems planning under uncertainty--An interval chance-constrained programming approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(4), pages 721-735, May.
    3. Dubreuil, Aurelie & Assoumou, Edi & Bouckaert, Stephanie & Selosse, Sandrine & Maı¨zi, Nadia, 2013. "Water modeling in an energy optimization framework – The water-scarce middle east context," Applied Energy, Elsevier, vol. 101(C), pages 268-279.
    4. 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.
    5. Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
    6. Xie, Y.L. & Huang, G.H. & Li, W. & Ji, L., 2014. "Carbon and air pollutants constrained energy planning for clean power generation with a robust optimization model—A case study of Jining City, China," Applied Energy, Elsevier, vol. 136(C), pages 150-167.
    7. Ushnik Mukherjee & Azadeh Maroufmashat & Apurva Narayan & Ali Elkamel & Michael Fowler, 2017. "A Stochastic Programming Approach for the Planning and Operation of a Power to Gas Energy Hub with Multiple Energy Recovery Pathways," Energies, MDPI, vol. 10(7), pages 1-27, June.
    8. Pouria Sheikhahmadi & Ramyar Mafakheri & Salah Bahramara & Maziar Yazdani Damavandi & João P. S. Catalão, 2018. "Risk-Based Two-Stage Stochastic Optimization Problem of Micro-Grid Operation with Renewables and Incentive-Based Demand Response Programs," Energies, MDPI, vol. 11(3), pages 1-17, March.
    9. Wu, C.B. & Huang, G.H. & Li, W. & Xie, Y.L. & Xu, Y., 2015. "Multistage stochastic inexact chance-constraint programming for an integrated biomass-municipal solid waste power supply management under uncertainty," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1244-1254.
    10. Xie, Y.L. & Li, Y.P. & Huang, G.H. & Li, Y.F., 2010. "An interval fixed-mix stochastic programming method for greenhouse gas mitigation in energy systems under uncertainty," Energy, Elsevier, vol. 35(12), pages 4627-4644.
    11. 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.
    12. Zhang-Chun Tang & Yanjun Xia & Qi Xue & Jie Liu, 2018. "A Non-Probabilistic Solution for Uncertainty and Sensitivity Analysis on Techno-Economic Assessments of Biodiesel Production with Interval Uncertainties," Energies, MDPI, vol. 11(3), pages 1-17, March.
    13. Price, T. J. & Probert, S. D., 1995. "Taiwan's energy and environmental policies: Past, present and future," Applied Energy, Elsevier, vol. 50(1), pages 41-68.
    14. Luhandjula, M.K., 2006. "Fuzzy stochastic linear programming: Survey and future research directions," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1353-1367, November.
    15. Leung, Stephen C.H. & Tsang, Sally O.S. & Ng, W.L. & Wu, Yue, 2007. "A robust optimization model for multi-site production planning problem in an uncertain environment," European Journal of Operational Research, Elsevier, vol. 181(1), pages 224-238, August.
    16. 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.
    17. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yang Zhang & Zhenghui Fu & Yulei Xie & Qing Hu & Zheng Li & Huaicheng Guo, 2020. "A Comprehensive Forecasting–Optimization Analysis Framework for Environmental-Oriented Power System Management—A Case Study of Harbin City, China," Sustainability, MDPI, vol. 12(10), pages 1-26, May.
    2. Xiao Zhao & Xuhui Xia & Guodong Yu, 2019. "Primal-Dual Learning Based Risk-Averse Optimal Integrated Allocation of Hybrid Energy Generation Plants under Uncertainty," Energies, MDPI, vol. 12(12), pages 1-15, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xie, Y.L. & Huang, G.H. & Li, W. & Ji, L., 2014. "Carbon and air pollutants constrained energy planning for clean power generation with a robust optimization model—A case study of Jining City, China," Applied Energy, Elsevier, vol. 136(C), pages 150-167.
    2. Guan, Panbo & Huang, Guohe & Wu, Chuanbao & Wang, Linrui & Li, Chaoci & Wang, Yuanyi, 2019. "Analysis of emission taxes levying on regional electric power structure adjustment with an inexact optimization model - A case study of Zibo, China," Energy Economics, Elsevier, vol. 84(C).
    3. 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.
    4. Wang, Xingwei & Cai, Yanpeng & Chen, Jiajun & Dai, Chao, 2013. "A grey-forecasting interval-parameter mixed-integer programming approach for integrated electric-environmental management–A case study of Beijing," Energy, Elsevier, vol. 63(C), pages 334-344.
    5. 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.
    6. 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.
    7. Xie, Y.L. & Xia, D.H. & Ji, L. & Zhou, W.N. & Huang, G.H., 2017. "An inexact cost-risk balanced model for regional energy structure adjustment management and resources environmental effect analysis-a case study of Shandong province, China," Energy, Elsevier, vol. 126(C), pages 374-391.
    8. Ratanakuakangwan, Sudlop & Morita, Hiroshi, 2021. "Hybrid stochastic robust optimization and robust optimization for energy planning – A social impact-constrained case study," Applied Energy, Elsevier, vol. 298(C).
    9. Yin, J.N. & Huang, G.H. & Xie, Y.L. & An, Y.K., 2021. "Carbon-subsidized inter-regional electric power system planning under cost-risk tradeoff and uncertainty: A case study of Inner Mongolia, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    10. Koo, Jamin & Han, Kyusang & Yoon, En Sup, 2011. "Integration of CCS, emissions trading and volatilities of fuel prices into sustainable energy planning, and its robust optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 665-672, January.
    11. Chen, F. & Huang, G.H. & Fan, Y.R. & Chen, J.P., 2017. "A copula-based fuzzy chance-constrained programming model and its application to electric power generation systems planning," Applied Energy, Elsevier, vol. 187(C), pages 291-309.
    12. Wu, Zhibin & Xu, Jiuping, 2013. "Predicting and optimization of energy consumption using system dynamics-fuzzy multiple objective programming in world heritage areas," Energy, Elsevier, vol. 49(C), pages 19-31.
    13. Baños, R. & Manzano-Agugliaro, F. & Montoya, F.G. & Gil, C. & Alcayde, A. & Gómez, J., 2011. "Optimization methods applied to renewable and sustainable energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(4), pages 1753-1766, May.
    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. Zhengping Liu & Wang Zhang & Hongxian Liu & Guohe Huang & Jiliang Zhen & Xin Qi, 2019. "Characterization of Renewable Energy Utilization Mode for Air-Environmental Quality Improvement through an Inexact Factorial Optimization Approach," Sustainability, MDPI, vol. 11(8), pages 1-19, April.
    16. Xu, Y. & Huang, G.H. & Qin, X.S. & Cao, M.F., 2009. "SRCCP: A stochastic robust chance-constrained programming model for municipal solid waste management under uncertainty," Resources, Conservation & Recycling, Elsevier, vol. 53(6), pages 352-363.
    17. Song, Tangnyu & Huang, Guohe & Zhou, Xiong & Wang, Xiuquan, 2018. "An inexact two-stage fractional energy systems planning model," Energy, Elsevier, vol. 160(C), pages 275-289.
    18. Aalaei, Amin & Davoudpour, Hamid, 2017. "A robust optimization model for cellular manufacturing system into supply chain management," International Journal of Production Economics, Elsevier, vol. 183(PC), pages 667-679.
    19. Masoud Hekmatfar & M. R. M. Aliha & Mir Saman Pishvaee & Tomasz Sadowski, 2023. "A Robust Flexible Optimization Model for 3D-Layout of Interior Equipment in a Multi-Floor Satellite," Mathematics, MDPI, vol. 11(24), pages 1-41, December.
    20. Pereira, Sérgio & Ferreira, Paula & Vaz, A.I.F., 2016. "Optimization modeling to support renewables integration in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 316-325.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:11:y:2018:i:8:p:2108-:d:163565. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.