Modeling of hydrogen production system for photovoltaic power generation and capacity optimization of energy storage system

Wei, Daohong and Li, Huawei and Ren, Yan and Yao, Xianhe and Wang, Long and Jin, Kunyong (2022) Modeling of hydrogen production system for photovoltaic power generation and capacity optimization of energy storage system. Frontiers in Energy Research, 10. ISSN 2296-598X

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Abstract

Hydrogen production using solar energy is an important way to obtain hydrogen energy. However, the inherent intermittent and random characteristics of solar energy reduce the efficiency of hydrogen production. Therefore, it is necessary to add an energy storage system to the photovoltaic power hydrogen production system. This paper establishes a model of a photovoltaic power generation hydrogen system and optimizes the capacity configuration. Firstly, the mathematical model is modeled and analyzed, and the system is modeled using Matlab/Simulink; secondly, the principle of optimal configuration of energy storage capacity is analyzed to determine the optimization strategy, we propose the storage capacity configuration algorithm based on the low-pass filtering principle, and optimal time constant selection; finally, a case study is conducted, whose photovoltaic installed capacity of 30 MW, verifying the effectiveness of the proposed algorithm, analyzing the relationship between energy storage capacity and smoothing effect. The results show that as the cut-off frequency decreases, the energy storage capacity increases and the smoothing effect is more obvious. The proposed algorithm can effectively reduce the 1 h maximum power variation of PV power generation. In which the maximum power variation of PV generation 1 h before smoothing is 4.31 MW. We set four different sets of time constants, the maximum power variation of PV generation 1 h after smoothing is reduced to 0.751, 0.389, 0.078, and 0.04 MW, respectively.

Item Type: Article
Subjects: Impact Archive > Energy
Depositing User: Managing Editor
Date Deposited: 08 May 2023 04:20
Last Modified: 15 Jan 2024 03:56
URI: http://research.sdpublishers.net/id/eprint/2219

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