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Intervene in advance or passively? Analysis and application on congestion control of smart grid

Author

Listed:
  • Yue Liu

    (School of Finance and Economics, Jiangsu University)

  • Jijian Zhang

    (School of Finance and Economics, Jiangsu University)

  • Xuhui Ding

    (School of Finance and Economics, Jiangsu University)

  • Xiling Zhang

    (School of Finance and Economics, Jiangsu University)

Abstract

This paper models a frequently encountered problem regarding optimal control and queuing. When the arriving and leaving of queuer are predicted, congestion is forecasted, the timing of intervene and control can really improve the effectiveness. A practical case of its application in industry is for the congestion management of smart grid, designed for which, modeling and solving the relevant optimal stopping problem refine the management to be even smarter, especially for the decision of whether intervene in advance or until the congestion happens, towards an ultimate reduction of congestion time. This model has no assumption expect letting the arriving time with a period time follows a uniform distribution, and has no parameters expect the congestion threshold. This conciseness makes this study applicable for very general cases and even for similar situations in other topics, and the findings illustrate deep wisdom of management especially for queueing control.

Suggested Citation

  • Yue Liu & Jijian Zhang & Xuhui Ding & Xiling Zhang, 2023. "Intervene in advance or passively? Analysis and application on congestion control of smart grid," Annals of Operations Research, Springer, vol. 320(2), pages 887-899, January.
    • Handle: RePEc:spr:annopr:v:320:y:2023:i:2:d:10.1007_s10479-021-04389-2
    DOI: 10.1007/s10479-021-04389-2
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    1. Thierry Bréchet & Carmen Camacho & Vladimir Veliov, 2014. "Model predictive control, the economy, and the issue of global warming," Annals of Operations Research, Springer, vol. 220(1), pages 25-48, September.
    2. Galus, Matthias D. & Zima, Marek & Andersson, Göran, 2010. "On integration of plug-in hybrid electric vehicles into existing power system structures," Energy Policy, Elsevier, vol. 38(11), pages 6736-6745, November.
    3. Sneha Dhyani Bhatt & Sachin Jayaswal & Ankur Sinha & Navneet Vidyarthi, 2021. "Alternate second order conic program reformulations for hub location under stochastic demand and congestion," Annals of Operations Research, Springer, vol. 304(1), pages 481-527, September.
    4. Yuan, Zhao & Hesamzadeh, Mohammad Reza, 2017. "Hierarchical coordination of TSO-DSO economic dispatch considering large-scale integration of distributed energy resources," Applied Energy, Elsevier, vol. 195(C), pages 600-615.
    5. Hadush, Samson Yemane & Meeus, Leonardo, 2018. "DSO-TSO cooperation issues and solutions for distribution grid congestion management," Energy Policy, Elsevier, vol. 120(C), pages 610-621.
    6. Yue Liu & Nicolas Privault, 2018. "A Recursive Algorithm for Selling at the Ultimate Maximum in Regime-Switching Models," Methodology and Computing in Applied Probability, Springer, vol. 20(1), pages 369-384, March.
    7. Debjit Roy & Ananth Krishnamurthy & Sunderesh Heragu & Charles Malmborg, 2015. "Stochastic models for unit-load operations in warehouse systems with autonomous vehicles," Annals of Operations Research, Springer, vol. 231(1), pages 129-155, August.
    8. Hemmati, Reza & Saboori, Hedayat & Jirdehi, Mehdi Ahmadi, 2017. "Stochastic planning and scheduling of energy storage systems for congestion management in electric power systems including renewable energy resources," Energy, Elsevier, vol. 133(C), pages 380-387.
    9. Yue Liu & Aijun Yang & Jijian Zhang & Jingjing Yao, 2020. "An Optimal Stopping Problem of Detecting Entry Points for Trading Modeled by Geometric Brownian Motion," Computational Economics, Springer;Society for Computational Economics, vol. 55(3), pages 827-843, March.
    10. Bjørndal, Endre & Bjørndal, Mette & Midthun, Kjetil & Zakeri, Golbon, 2016. "Congestion Management in a Stochastic Dispatch Model for Electricity Markets," Discussion Papers 2016/12, Norwegian School of Economics, Department of Business and Management Science.
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