孙一凡,王林,金潇
SUN Yifan,WANG Lin,JIN Xiao

• 1:国网浙江省电力有限公司嘉兴供电公司

摘要(Abstract)：

新能源发电的波动性会加速电转气场站内电解水设备的老化，现有优化模型无法有效计及宽功率波动对电解水设备寿命及电转气场站容量配置的影响。在此背景下，提出了考虑电解水设备寿命的电转气场站容量分布鲁棒优化配置模型。首先，提出一种考虑功率波动影响的电解水设备寿命折损评估模型，进而建立了含电转气场站的电-气综合能源系统优化规划模型，对电转气场站内电解水、甲烷化和储氢罐的容量进行优化配置。其次，基于1-范数约束和∞-范数约束构建源荷场景的概率分布模糊集，将规划模型改写为“min-max-min”形式的分布鲁棒优化模型，并利用列与约束生成算法进行求解。最后，利用测试算例对所提模型和算法进行验证。结果表明，所提模型能够更准确地计算电转气场站的经济效益，延长电解水设备预期使用寿命。
The volatility of renewable energy generation accelerates the aging of water distributionally robust optimization within Power-to-Gas(P2G) stations. Existing optimization models fail to effectively account for the impact of wide power fluctuations on the service life of water electrolysis equipment and the capacity configuration of P2G stations. In this context, this paper proposes a distributionally robust optimization model for the capacity configuration in P2G stations, taking into consideration the service life of electrolysis equipment. Firstly, a model for assessing the degradation of water electrolysis equipment service life is introduced, considering the influence of power fluctuations. Subsequently, an optimization and planning model for an integrated electricity and natural gas system(IENGS) that includes P2G stations is established. This model optimizes the capacity configuration of electrolysis, methanation, and hydrogen storage tanks within the P2G station. Secondly, a fuzzy set of probability distribution for source-load scenarios is constructed based on l1-norm constraints and l∞-norm constraints. The planning model is reformulated as a min-max-min distributionally robust optimization(DRO) model and solve it using a column-andconstraint generation algorithm. Finally, the proposed model and algorithm are validated using test cases. Results demonstrate that the proposed model can more accurately calculate the economic benefits of P2G stations and extend the expected service life of electrolysis equipment.

关键词(KeyWords)： 电转气;电解水;寿命折损评估;优化规划;分布鲁棒优化
P2G;water electrolysis;life degradation assessment;optimal planning;DRO

Abstract:

Keywords:

基金项目(Foundation): 国网浙江省电力有限公司科技项目（B311JX220002）

作者(Author): 孙一凡,王林,金潇
SUN Yifan,WANG Lin,JIN Xiao

DOI: 10.19585/j.zjdl.202405003

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