可再生能源制氢系统多目标优化调度
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TM715

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河北省科技支撑计划资助项目(19210108D,19214501D,20314501D,F2021202022)


Research on Multi-objective Optimal Scheduling of Renewable Energy Hydrogen Production System
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    摘要:

    随着双碳政策的推行,氢能在能源去碳化进程中扮演着重要的地位。利用可再生能源制氢可以进一步实现能源低碳化。针对可再生能源系统稳定性较弱的缺点,本文将系统收益和环境成本这一对相互矛盾的目标进行折中考虑,提出使用多目标金鹰算法(MOGEO)对可再生能源制氢系统运行优化求解帕累托最优解集。为验证该方法的可行性,以冬奥场馆所在地的典型日为例,分别与商业求解器CPLEX及传统的多目标粒子群算法(MOPSO)进行对比,证明本文所提方法可以取得更好的优化结果。

    Abstract:

    With the implementation of the Double carbon policy, hydrogen plays an important role in the process of decarbonization of energy, the use of renewable energy to produce hydrogen can further decarbonize energy. In response to the weakness of the stability of renewable energy systems, In this paper, the conflicting objectives of system benefits and environmental costs are considered as a simultaneously consideration,the multi-objective Golden Eagle algorithm (MOGEO) is used to run and optimize the Pareto optimal solution set for the renewable energy hydrogen production system. In order to verify the feasibility of the proposed method, four typical days at the location of Winter Olympic as an example, and compared with the commercial solver CPLEX and the traditional multi-objective particle swarm optimization (MOPSO) algorithm, it is proved that the proposed method can achieve better optimization results.

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梁涛,孙博峰,刘伟,等. 可再生能源制氢系统多目标优化调度[J]. 科学技术与工程, 2023, 23(1): 226-235.
Liang Tao, Sun Bofeng, Liu Wei, et al. Research on Multi-objective Optimal Scheduling of Renewable Energy Hydrogen Production System[J]. Science Technology and Engineering,2023,23(1):226-235.

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历史
  • 收稿日期:2022-04-18
  • 最后修改日期:2023-01-05
  • 录用日期:2022-09-18
  • 在线发布日期: 2023-01-18
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