Details

Autor(en) / Beteiligte

• Gong, J.W.
• Li, Y.P.
• Lv, J.
• Huang, G.H.
• Suo, C.
• Gao, P.P.

Titel

Development of an integrated bi-level model for China’s multi-regional energy system planning under uncertainty

Ist Teil von

• Applied energy, 2022-02, Vol.308, Article 118299

Ort / Verlag

Elsevier Ltd

Erscheinungsjahr

2022

Link zum Volltext

Quelle

Elsevier ScienceDirect Journals Complete

Beschreibungen/Notizen

• [Display omitted] •A bi-level joint-probabilistic programming approach is developed.•It can handle leader–follower issues and joint-probabilistic constraints.•The proposed approach is applied to China’s multi-regional energy system model.•The optimal schemes during 2021–2050 under three mitigation scenarios are obtained.•Results are helpful to achieve low-carbon goals in multi-regional energy system. Climate change mitigation and renewable resources utilization are becoming particularly urgent for energy system management. In this study, a bi-level joint-probabilistic programming (BJPP) method is developed for planning multi-regional energy system under different mitigation policies and uncertainties. BJPP can handle leader–follower issues in decision-making process as well as examine the risk of violating joint-probabilistic constraints. Based on the BJPP method, a China’s multi-regional energy system (named as BJPP_CMES) model is formulated to provide optimal scheme for energy system planning of China over a long-term horizon (2021–2050) by synergistically minimizing carbon dioxide (CO2) emission and system cost. A series of scenarios associated with different carbon capture and storage (CCS) levels and violation risks of energy-demand constraints are examined. Results reveal that: (i) the share of non-fossil energy in China’s energy supply would keep increasing in 2021–2050, and the highest growth of the renewable supply would occur in Ningxia (rising 47.7%); (ii) Sichuan, Inner Mongolia, and Gansu would be the top three suppliers of renewable electricity; (iii) the CO2 emission of China would reach a peak of [44.3, 54.8] billion tonnes during the period of 2026–2030; Shandong, Inner Mongolia, and Shanxi would be main contributors of CO2 emission in the future; (iv) compared with the single-level model, the CO2 emission from the BJPP_CMES model would reduce by [2.7, 5.7]%; (v) among developed regions, the individual probability level of Jiangsu-Zhejiang-Shanghai is the most significant parameter for both CO2 emission and system cost. The findings are helpful for decision makers to optimize multi-regional energy system (MES) with a low-carbon and cost-effective manner, as well as to provide useful information for renewable energy utilization and regional sustainable development.