Energy-water-carbon nexus system planning: A case study of Yangtze River Delta urban agglomeration, China

M.S. Liang, G.H. Huang, J.P. Chen and Y.P. Li

Applied Energy, 2022, vol. 308, issue C, No S0306261921014203

Abstract: In this study, a chance-constrained fractional programming model is developed for energy-water-carbon nexus systems in Yangtze River Delta urban agglomeration, China. The developed model can tackle the ratio objectives and multiple uncertainties expressed as interval numbers and probability distributions, and provide desired decision alternatives under different constraint-violation levels. Then, the developed model is applied to the strategic planning of the energy-water-carbon nexus system in Yangtze River Delta urban agglomeration for addressing issues of energy-related water resource shortage and carbon emission reduction. Two different development patterns are designed in this strategic planning. One is to maximize the renewable electricity generation per unit of system cost corresponding to the system efficiency-oriented development pattern, while the other is to minimize the total system cost with respect to the economic benefit-oriented development pattern. The obtained comparative results show that the energy-water-carbon nexus system under the system efficiency-oriented development pattern would increase 21.71% of renewable electricity generation and 16.29% of system efficiency, save 8.95% of water resource, reduce 14.61% of carbon emission, but increase 4.07% of imported electricity and 7.85% of system cost over the planning horizon. These findings can provide profound solutions and insights for decision makers considering different policy implications. The application to Yangtze River Delta urban agglomeration energy-water-carbon nexus system shows the practicability of the extension to other regions under severe situations of energy supply limitation, water resource shortage and carbon emission reduction.

Keywords: Energy-water-carbon nexus; Multiple uncertainties; Chance-constrained fractional programming; Renewable energy penetration; Dual objectives (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (10)

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DOI: 10.1016/j.apenergy.2021.118144

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