EconPapers    
Economics at your fingertips  
 

Optimal configuration of hybrid energy systems considering power to hydrogen and electricity-price prediction: A two-stage multi-objective bi-level framework

Jingyi Shang, Jinfeng Gao, Xin Jiang, Mingguang Liu and Dunnan Liu

Energy, 2023, vol. 263, issue PF

Abstract: This paper develops a two-stage multi-objective bi-level framework to optimize the sizing of a grid-connected electricity-hydrogen system. Firstly, a multi-objective bi-level capacity configuration optimization model considering the different functional orientations of hydrogen energy and electricity-price prediction is established. Then, to solve the above multi-objective bi-level model, a two-stage solution algorithm is proposed. In stage one, the CPLEX solver and non-dominated sorting genetic algorithm II are employed to obtain the solutions of the developed optimization model. In stage two, an entropy method is applied to get the importance of the three objectives of the outer model, whereas a cumulative prospect theory is used to rank the best Pareto solution. Finally, an industrial park in Aksai Kazak Autonomous County is chosen for case study, the results show: (1) the best capacity configuration alternative, which includes 22 wind turbines, 210 photovoltaic panels, 2 gas turbines, 2 fuel cells, 1 electrolyzer, and 3 hydrogen tanks, owns the NPB of 161,503 CNY, the ACE of 93,111 kg, and the LOEC of 603,874 kWh. (2) the ACE with the weight of 0.527 is the most important objective. (3) Sensitivity analysis on electricity price fluctuations of ±5% and ±10% presents that the proposed approach is robust.

Keywords: Configuration optimization; Bi-level programming; Electricity-price prediction; NSGA-II; Cumulative prospect theory (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544222029097
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:263:y:2023:i:pf:s0360544222029097

DOI: 10.1016/j.energy.2022.126023

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:energy:v:263:y:2023:i:pf:s0360544222029097