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Two-layer optimal scheduling of integrated electric-hydrogen energy system with seasonal energy storage

Liu, Xinghua, Zu, Longyu, Wei, Zhongbao, Wang, Yubo, Pan, Zhongmei, Xiao, Gaoxi and Jenkins, Nicholas ORCID: https://orcid.org/0000-0003-3082-6260 2024. Two-layer optimal scheduling of integrated electric-hydrogen energy system with seasonal energy storage. International Journal of Hydrogen Energy 82 , pp. 1131-1145. 10.1016/j.ijhydene.2024.07.415
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Abstract

Hydrogen is characterized by zero carbon emissions and high energy density, which can effectively support the consumption of a high proportion of intermittent new energy. Considering the seasonal nature of renewable energy sources, a seasonal hydrogen storage model is incorporated in an electric-hydrogen integrated energy system (EH-IES). In this paper, a two-layer optimization method is proposed for EH-IES with seasonal hydrogen storage. The problem of co-optimizing the equipment capacity and configuration in the proposed system is coordinated by establishing a two-layer optimization framework. Specifically, the system is optimized to minimize cost and carbon emissions at the upper layer using the multi-objective stochastic paint optimizer (MOSPO) algorithm, with the capacity configuration results being transmitted to the lower layer. The lower layer, aiming to reduce the total system cost, utilizes a commercial solver to obtain the optimal economic scheduling results for a typical day. The final analysis of the four scenarios shows that the increase in renewable energy reduces the purchasing cost of electricity by 1.89%, while in contrast, the total cost increases by 4.4% in the system with a lower proportion of renewable energy. In the case of higher heating and cooling loads, the increase in renewables reduces the purchase cost of natural gas by 9.10%. The results demonstrate that the proposed method can leverage the seasonal complementary benefits to drive new energy consumption, enhance system operation efficiency, and effectively reduce EH-IES’s total operation cost and carbon emission.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: Elsevier
ISSN: 0360-3199
Date of First Compliant Deposit: 2 September 2024
Date of Acceptance: 27 July 2024
Last Modified: 02 Sep 2024 23:45
URI: https://orca.cardiff.ac.uk/id/eprint/171552

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