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考虑平抑风光波动的ALK-PEM电解制氢系统容量优化模型

杨胜 樊艳芳 侯俊杰 白雪岩

电力系统保护与控制2024,Vol.52Issue(1):85-96,12.
电力系统保护与控制2024,Vol.52Issue(1):85-96,12.DOI:10.19783/j.cnki.pspc.230500

考虑平抑风光波动的ALK-PEM电解制氢系统容量优化模型

Capacity optimization model for an ALK-PEM electrolytic hydrogen production system considering the stabilization of wind and PV fluctuations

杨胜 1樊艳芳 1侯俊杰 1白雪岩1

作者信息

  • 1. 新疆大学电气工程学院,新疆 乌鲁木齐 830047
  • 折叠

摘要

Abstract

To enhance wind power and photovoltaic utilization,electrolytic hydrogen production has gained attention.However,hydrogen energy is vulnerable to the fluctuations of these resources during production.Therefore,this paper proposes an alkaline-proton exchange membrane(ALK-PEM)capacity optimization model for hydrogen electrolysis to mitigate these fluctuations.First,the EMD algorithm is used to analyze the transient fluctuation characteristics of raw wind and PV.Supercapacitors are employed to smooth these fluctuations,ensuring safe and stable operation of the hydrogen production system.An EMD-based SC capacity allocation model is constructed for this purpose.Second,a capacity optimization model is proposed for the ALK-PEM electrolytic hydrogen production system.By combining proton exchange membrane(PEM)and Alkaline(ALK)electrolyzers,it replaces the single-type electrolyzer system.This approach considers different electrolyzer operational characteristics,thereby improving economic efficiency.Finally,the system's capacity planning is simulated using data from a wind farm and a photovoltaic power plant.This validates the proposed model's effectiveness in smoothing fluctuations,enhancing renewable energy utilization,and improving the system's overall economy.

关键词

氢能/ALK-PEM电解/经验模态分解/风光波动性/容量配置

Key words

hydrogen/ALK-PEM electrolysis/EMD/wind and PV fluctuations/capacity configuration

引用本文复制引用

杨胜,樊艳芳,侯俊杰,白雪岩..考虑平抑风光波动的ALK-PEM电解制氢系统容量优化模型[J].电力系统保护与控制,2024,52(1):85-96,12.

基金项目

新疆维吾尔自治区自然科学基金项目资助(2022D01C365,2022D01C662) (2022D01C365,2022D01C662)

2022 天山英才培养计划项目资助(2022TSYCLJ0019) This work is supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region(No.2022D01C365 and No.2022D01C662). (2022TSYCLJ0019)

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