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A chance-constrained programming approach to optimal planning of low-carbon transition of a regional energy system

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  • Zhang, Jiaqi
  • Tian, Guang
  • Chen, Xiangyu
  • Liu, Pei
  • Li, Zheng

Abstract

Low-carbon transition of energy systems is an inevitable trend to address climate change challenges. For developing regions, proper planning is essential for reducing transition costs during low-carbon transition of their energy systems, featuring a higher proportion of intermittent renewable power connected to power grids. Impact of uncertainty must be considered for more feasible planning of peak-shaving and energy storage units. In this study, a chance-constrained programming approach to optimal planning of low-carbon transition of a regional energy system is presented. This approach considers uncertainties of wind power, photovolatic (PV) power and load to ensure power supply reliability. A developing region in central China is taken as a case study. Results show that considering uncertainty, an additional 4.79% of power generation capacity needs to be installed per year on average, with a 3.02% increase in the transition cost. Finally, sensitivity analysis results are provided, showing that a rapid increase in transition costs occurs when the confidence level exceeds 99%. The results in this study provide references for decision-makers to plan the low-carbon transition of energy systems as well as weighing transition costs against energy supply stability.

Suggested Citation

  • Zhang, Jiaqi & Tian, Guang & Chen, Xiangyu & Liu, Pei & Li, Zheng, 2023. "A chance-constrained programming approach to optimal planning of low-carbon transition of a regional energy system," Energy, Elsevier, vol. 278(PA).
    • Handle: RePEc:eee:energy:v:278:y:2023:i:pa:s0360544223012070
    DOI: 10.1016/j.energy.2023.127813
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