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

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

Energy, 2023, vol. 278, issue PA

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.

Keywords: Chance-constrained programming; Energy system; Optimization; Decarbonization (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:278:y:2023:i:pa:s0360544223012070

DOI: 10.1016/j.energy.2023.127813

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