Journal of Modern Power Systems and Clean Energy

ISSN 2196-5625 CN 32-1884/TK

Economic Scheduling of Gaseous-liquid Hydrogen Generation and Storage Plants Considering Complementarity of Multiple Products
Author:
Affiliation:

1.College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
2.Hunan Key Laboratory of Intelligent Information Analysis Integrated Optimization for Energy Internet, Hunan University, Changsha 410082, China
3.Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
4.Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
5.College of electrical Engineering, Guangxi University, Nanning 530004, China

Fund Project:

This work was supported by the National Natural Science Foundation of China (No. 51877117) and the Key Project of National Natural Science Foundation of China (No. 61733010).

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    Abstract:

    The accessible and convenient hydrogen supply is the foundation of successful materialization for hydrogen-powered vehicles (HVs). This paper proposes a novel optimal scheduling model for gaseous-liquid hydrogen generation and storage plants powered by renewable energy to enhance the economic feasibility of investment. The gaseous-liquid hydrogen generation and storage plant can be regarded as an energy hub to supply concurrent service to both the transportation sector and ancillary market. In the proposed model, the power to multi-state hydrogen (P2MH) process is analyzed in detail to model the branched hydrogen flow constraints and the corresponding energy conversion relationship during hydrogen generation, processing, and storage. To model the coupling and interaction of diverse modules in the system, the multi-energy coupling matrix is developed, which can exhibit the mapping of power from the input to the output. Based on this, a multi-product optimal scheduling (MPOS) algorithm considering complementarity of different hydrogen products is further formulated to optimize dispatch factors of the energy hub system to maximize the profit within limited resources. The demand response signals are incorporated in the algorithm to further enhance the operation revenue and the scenario-based method is deployed to consider the uncertainty. The proposed methodology has been fully tested and the results demonstrate that the proposed MPOS can lead to a higher rate of return for the gaseous-liquid hydrogen generation and storage plant.

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History
  • Received:April 25,2021
  • Revised:July 27,2021
  • Adopted:
  • Online: January 28,2023
  • Published: