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IEEE Transactions on Sustainable Energy
Article . 2022 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
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Coordinated Planning of HVDCs and Power-to-Hydrogen Supply Chains for Interregional Renewable Energy Utilization

Authors: Jiarong Li; Jin Lin; Yonghua Song; Jinyu Xiao; Feng Liu; Yuxuan Zhao; Sen Zhan;

Coordinated Planning of HVDCs and Power-to-Hydrogen Supply Chains for Interregional Renewable Energy Utilization

Abstract

With the urgent requirement of the utilization of renewable energy (RE) for the decarbonization of energy systems, power transmission via high-voltage direct current (HVDC) lines shows limits in the face of fluctuations of RE generation. This paper addresses the coordinated planning of HVDCs and power-to-hydrogen supply chains (P2HSCs) for RE utilization. First, the lumped cluster model of the large-scale power-to-hydrogen is established based on the derivation of the maximum production points. On this basis, P2HSC is modeled as a constrained power load. Then, a multi-objective multi-stage stochastic planning model of HVDCs and P2HSCs is proposed to fully consider RE fluctuation and uncertainty characteristics. Furthermore, a decomposition algorithm based on the dynamic programming method is designed to solve this problem. Finally, the proposed model and algorithm are applied in real Inner Mongolia-Shandong case studies. The effectiveness and robustness of the proposed model are quantitatively verified. Furthermore, the investment interplay of HVDCs and P2HSCs on the planning timeline and the operational interplay of the two sectors as complementary power loads are verified to create the maximum social benefit in renewable energy systems.

Country
Netherlands
Keywords

dynamic programming, P2HSC, Load modeling, HVDC, Production, HVDC transmission, Renewable energy sources, Planning, multi-objective multi-stage stochastic planning, SDG 7 - Affordable and Clean Energy, SDG 7 – Betaalbare en schone energie, Hydrogen, Supply chains

  • BIP!
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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    6
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
hybrid