2023 AIChE Annual Meeting
(438c) Multi-Period Joint Capacity Expansion Planning of Renewable Electricity and Hydrogen Production: An Application to South Korea
Authors
One study proposed a linear continuous truck routing model for hydrogen transportation within a joint planning framework [3], where a robust optimization was employed to address uncertainties. Another study investigated various technologies associated with the generation and storage of both electricity and hydrogen [4]. Specifically, hydrogen production through electrolysis was compared against that from steam methane reforming with or without carbon capture and storage. However, these studies did not account for the long-term dynamics of the hybrid system or the lifetimes of different facilities, which have significant implications for long-term planning. On the other hand, there exist several works which addressed long-term, multi-period planning for the hydrogen and renewable power production by considering facilities with varying lifetime [5, 6]. However, in these studies, the focus was on the planning of either hydrogen production or renewable power generation, while the other was assumed to have a fixed infrastructure, i.e., joint planning was not explicitly considered.
To this end, in this talk, a multi-period joint capacity expansion planning framework is proposed for renewable electricity and hydrogen production to meet the long-term future demands. The proposed framework determines the optimal size and location of production, storage, transmission/transportation, and operation of the hybrid supply chain network by solving a cost minimization mathematical programming problem. This problem is a multi-time scale decision making problem, where detailed operational decision constraints at an hourly level are combined with investment planning decisions over a few decades. The effectiveness and advantages of the proposed framework will be illustrated by a comprehensive case study for the hydrogen economy of South Korea, taking into account a range of policy and technology scenarios.
[1] Riera, J. A., Lima, R. M., & Knio, O. M. (2023). A review of hydrogen production and supply chain modeling and optimization. International Journal of Hydrogen Energy.
[2] Farrokhifar, M., Nie, Y., & Pozo, D. (2020). Energy systems planning: A survey on models for integrated power and natural gas networks coordination. Applied Energy, 262, 114567.
[3] Wang, S., & Bo, R. (2021). Joint planning of electricity transmission and hydrogen transportation networks. IEEE Transactions on Industry Applications, 58(2), 2887-2897.
[4] Bødal, E. F., Mallapragada, D., Botterud, A., & Korpås, M. (2020). Decarbonization synergies from joint planning of electricity and hydrogen production: a Texas case study. international journal of hydrogen energy, 45(58), 32899-32915.
[5] Li, C., Conejo, A. J., Liu, P., Omell, B. P., Siirola, J. D., & Grossmann, I. E. (2022). Mixed-integer linear programming models and algorithms for generation and transmission expansion planning of power systems. European Journal of Operational Research, 297(3), 1071-1082.
[6] Yoon, H. J., Seo, S. K., & Lee, C. J. (2022). Multi-period optimization of hydrogen supply chain utilizing natural gas pipelines and byproduct hydrogen. Renewable and Sustainable Energy Reviews, 157, 112083.