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Planning regional-scale electric power systems under uncertainty: A case study of Jing-Jin-Ji region, China

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  • Yu, L.
  • Li, Y.P.
  • Huang, G.H.
  • Fan, Y.R.
  • Yin, S.

Abstract

In this study, a copula-based stochastic fuzzy-credibility programming (CSFP) method is developed for planning regional-scale electric power systems (REPS). CSFP cannot only deal with multiple uncertainties presented as random variables, fuzzy sets, interval values as well as their combinations, but also reflect uncertain interactions among multiple random variables owning different probability distributions and having previously unknown correlations. Then, a CSFP-REPS model is formulated for planning the electric power systems (EPS) of the Jing-Jin-Ji region, where multiple scenarios with different joint and individual probabilities as well as different credibility levels are examined. Results reveal that electricity shortage would offset [4.8, 5.2]% and system cost would reduce [3.2, 3.3]% under synergistic effect scheme. Results also disclose that the study region’s future electricity-supply pattern would tend to the transition to renewable energies and the share of renewable energies would increase approximately 10% over the planning horizon. Compared to the conventional stochastic programming, the developed CSFP method can more effectively analyze individual and interactive effects of multiple random variables, so that the loss of uncertain information can be mitigated and the robustness of solution can be enhanced. Moreover, based on the main effect analysis and regression analysis, CSFP-REPS can provide multiple joint planning strategies in a cost- and computation-effective way. Findings are useful for reflecting interactions among multiple random variables and disclosing their joint effects on modeling outputs of REPS planning problems.

Suggested Citation

  • Yu, L. & Li, Y.P. & Huang, G.H. & Fan, Y.R. & Yin, S., 2018. "Planning regional-scale electric power systems under uncertainty: A case study of Jing-Jin-Ji region, China," Applied Energy, Elsevier, vol. 212(C), pages 834-849.
    • Handle: RePEc:eee:appene:v:212:y:2018:i:c:p:834-849
    DOI: 10.1016/j.apenergy.2017.12.089
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    as
    1. Motalleb, Mahdi & Ghorbani, Reza, 2017. "Non-cooperative game-theoretic model of demand response aggregator competition for selling stored energy in storage devices," Applied Energy, Elsevier, vol. 202(C), pages 581-596.
    2. Herbes, Carsten & Brummer, Vasco & Rognli, Judith & Blazejewski, Susanne & Gericke, Naomi, 2017. "Responding to policy change: New business models for renewable energy cooperatives – Barriers perceived by cooperatives’ members," Energy Policy, Elsevier, vol. 109(C), pages 82-95.
    3. 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.
    4. Narayan, Apurva & Ponnambalam, Kumaraswamy, 2017. "Risk-averse stochastic programming approach for microgrid planning under uncertainty," Renewable Energy, Elsevier, vol. 101(C), pages 399-408.
    5. Sun, Xudong & Li, Jiashuo & Qiao, Han & Zhang, Bo, 2017. "Energy implications of China's regional development: New insights from multi-regional input-output analysis," Applied Energy, Elsevier, vol. 196(C), pages 118-131.
    6. Yu, L. & Li, Y.P. & Huang, G.H., 2016. "A fuzzy-stochastic simulation-optimization model for planning electric power systems with considering peak-electricity demand: A case study of Qingdao, China," Energy, Elsevier, vol. 98(C), pages 190-203.
    7. 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.
    8. Huang, Yun-Hsun & Wu, Jung-Hua & Hsu, Yu-Ju, 2016. "Two-stage stochastic programming model for the regional-scale electricity planning under demand uncertainty," Energy, Elsevier, vol. 116(P1), pages 1145-1157.
    9. Perera, A.T.D. & Nik, Vahid M. & Mauree, Dasaraden & Scartezzini, Jean-Louis, 2017. "Electrical hubs: An effective way to integrate non-dispatchable renewable energy sources with minimum impact to the grid," Applied Energy, Elsevier, vol. 190(C), pages 232-248.
    10. Kshirsagar, Charudatta M. & Anand, Ramanathan, 2017. "Artificial neural network applied forecast on a parametric study of Calophyllum inophyllum methyl ester-diesel engine out responses," Applied Energy, Elsevier, vol. 189(C), pages 555-567.
    11. Rong, Aiying & Lahdelma, Risto, 2008. "Fuzzy chance constrained linear programming model for optimizing the scrap charge in steel production," European Journal of Operational Research, Elsevier, vol. 186(3), pages 953-964, May.
    12. Yu, L. & Li, Y.P. & Huang, G.H. & Fan, Y.R. & Nie, S., 2018. "A copula-based flexible-stochastic programming method for planning regional energy system under multiple uncertainties: A case study of the urban agglomeration of Beijing and Tianjin," Applied Energy, Elsevier, vol. 210(C), pages 60-74.
    13. Lin, Boqiang & Wu, Wei, 2017. "Cost of long distance electricity transmission in China," Energy Policy, Elsevier, vol. 109(C), pages 132-140.
    14. Mirjat, Nayyar Hussain & Uqaili, Mohammad Aslam & Harijan, Khanji & Valasai, Gordhan Das & Shaikh, Faheemullah & Waris, M., 2017. "A review of energy and power planning and policies of Pakistan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 110-127.
    15. Devlin, Ger & Talbot, Bruce, 2014. "Deriving cooperative biomass resource transport supply strategies in meeting co-firing energy regulations: A case for peat and wood fibre in Ireland," Applied Energy, Elsevier, vol. 113(C), pages 1700-1709.
    16. 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.
    17. A. Charnes & W. W. Cooper, 1983. "Response to "Decision Problems Under Risk and Chance Constrained Programming: Dilemmas in the Transition"," Management Science, INFORMS, vol. 29(6), pages 750-753, June.
    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. Prebeg, Pero & Gasparovic, Goran & Krajacic, Goran & Duic, Neven, 2016. "Long-term energy planning of Croatian power system using multi-objective optimization with focus on renewable energy and integration of electric vehicles," Applied Energy, Elsevier, vol. 184(C), pages 1493-1507.
    20. Shen, Jianjian & Cheng, Chuntian & Wu, Xinyu & Cheng, Xiong & Li, Weidong & Lu, Jianyu, 2014. "Optimization of peak loads among multiple provincial power grids under a central dispatching authority," Energy, Elsevier, vol. 74(C), pages 494-505.
    21. Park, Heejung & Baldick, Ross, 2016. "Multi-year stochastic generation capacity expansion planning under environmental energy policy," Applied Energy, Elsevier, vol. 183(C), pages 737-745.
    22. Zhou, Xiong & Huang, Guohe & Zhu, Hua & Chen, Jiapei & Xu, Jinliang, 2015. "Chance-constrained two-stage fractional optimization for planning regional energy systems in British Columbia, Canada," Applied Energy, Elsevier, vol. 154(C), pages 663-677.
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