Distributionally robust energy-transportation coordination in coal mine integrated energy systems

Hongxu Huang, Zhengmao Li, Hoay Beng Gooi, Haifeng Qiu, Xiaotong Zhang, Chaoxian Lv, Rui Liang*, Dunwei Gong

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

25 Citations (Scopus)

Abstract

In this paper, a coordinated operation approach is proposed for scheduling the energy-transportation coupled coal mine integrated energy system (CMIES) under diverse uncertainties. As the coupling equipment in the coal transportation network (CTN) and the CMIES, the belt conveyors are able to coordinate the coal delivery scheduling and energy management. However, lacking the CTN modelling remains an unsolved challenge. Firstly, this paper proposed a novel energy-transportation coordinated model, consisting of the radial CTN and second-order cone programming (SOCP) relaxed CMIES. To address uncertainties from renewable energy generation output and raw coal production, the distributionally robust optimization (DRO) method is applied under the two-time scale operation framework to overcome the drawbacks of robust optimization and stochastic programming. The first timescale, i.e., the day-ahead scheduling, is focused on energy dispatching at long time intervals while the second scale i.e., the intra-day. scheduling, deals with uncertainties at short time intervals. Specifically, an event-wise Wasserstein ambiguity set is devised to handle the issue of probability distribution function information requirement, which is hard to obtain in practice. Finally, a real case of CMIES is simulated to validate the effectiveness of our proposed model and method. The results reveal that our method can effectively enhance the operational economy, realize decarbonization, and fulfill the coal transportation continuity compared to conventional methods.

Original languageEnglish
Article number120577
JournalApplied Energy
Volume333
DOIs
Publication statusPublished - 1 Mar 2023
MoE publication typeA1 Journal article-refereed

Funding

This work was financially supported by the National Natural Science Foundation of China NO. 62133015, NO. 52077215, National Key R&D Program of China with grant No. 2021YFE0199000 and conducted in cooperation with Taiyuan Coal Gasification Longquan Energy Development Co. Ltd. Shanxi Province, China.

Keywords

  • Coal mine integrated energy system (CMIES)
  • Distributionally robust optimization
  • Energy-transportation
  • Multiple uncertainties
  • Virtual energy storage (VES)

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