Back to Search Start Over

Balancing the water-energy dilemma in nexus system planning with bi-level and multi-uncertainty.

Authors :
Huang, Shanshan
Suo, Cai
Guo, Junhong
Lv, Jing
Jing, Rui
Yu, Lei
Fan, Yurui
Ding, Yanming
Source :
Energy. Sep2023, Vol. 278, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

The complicated interrelationship between water and energy makes the water-energy dilemma a complex challenge to be tackled, especially considering the tradeoffs among decision-makers at different hierarchical levels and multiple uncertainties derived from climate change, socio-economic development, technical improvement and decision-making preferences. Thus, a water-energy nexus planning framework would be established in this paper to assist optimal decision-making with bi-level programming and multi-uncertainty. By integrating the regional climate model, multiple linear regression, and bi-level interval flexible programming, an integrated prediction optimization model would be developed as the core of the water-energy nexus planning framework. Then it is applied to planning Zhengzhou City over fifteen years. Multiple scenarios based on electricity demand-supply and carbon dioxide emission satisfaction degrees are analyzed leading to the results of (1) compared to the conventional single-level optimization method, the developed model can achieve the hierarchical goals of water saving and economic suitability; (2) renewable energy will be largely developed and its ratio to electricity generation will reach [26.30, 27.51] % under the limited water availability. Overall, the proposed water-energy nexus planning framework can achieve a balanced water-energy dilemma considering bi-level decision-making preferences and multi-uncertainties, which can be applied to planning water-energy nexus systems at a similar scale. • Regional climate model is used for predicting future electricity demands. • The proposed model addresses bi-level and multi-uncertainty. • Water-energy dilemma towards two different hierarchical levels is assessed. • Optimal solutions provide insights for managing similar scale studies. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03605442
Volume :
278
Database :
Academic Search Index
Journal :
Energy
Publication Type :
Academic Journal
Accession number :
164379721
Full Text :
https://doi.org/10.1016/j.energy.2023.127720