天然气与石油2025，Vol.43Issue(5)：28-35,8.DOI:10.3969/j.issn.1006-5539.2025.05.004
面向新能源制氢的短期功率预测方法
Short-term power prediction method for new-energy-based hydrogen production
摘要
Abstract
In the context of low-carbon energy,producing hydrogen from wind and solar renewable energy has become an inevitable trend.However,the fluctuation nature of new energy often leads to the curtailment of wind and solar power in the grid.To address this issue,improve the accuracy of new energy power forecasting,and enable efficient hydrogen production under wide power fluctuations,this study proposes a short-term power prediction method for new-energy-based hydrogen production using a Long Short-Term Memory(LSTM)neural network.First,based on the numerical weather prediction data,including wind speed,wind direction,air temperature,relative humidity and air pressure,the correlation coefficient between the new energy power output and meteorological factors are calculated to support the dimensionality reduction of multi-dimensional weather data.Then,considering the fluctuation and trend of new energy output,the 90%confidence interval is used to characterize the fluctuation of new energy output,serving as a preliminary screening processs for the training data to ensure the prediction accuracy.Finally,the LSTM neural network prediction model is used to train the selected numerical data and establish a mapping relationship between weather parameters and new energy power generation output.Using measured photovoltaic power output data as a case study,the proposed method demonstrates high prediction accuracy.When applied to hydrogen production via proton exchange membrane(PEM)electrolyzers,the results can provide a reference for the optimal control and operation of new-energy-based hydrogen production system.关键词
新能源功率预测/制氢/LSTM神经网络/数值天气预报/置信区间Key words
New energy power prediction/Hydrogen production/LSTM neural network/Numerical weather prediction/Confidence interval引用本文复制引用
余苏兴,徐育斌,陈石义,吴筱熳,廖勇..面向新能源制氢的短期功率预测方法[J].天然气与石油,2025,43(5):28-35,8.基金项目
国家自然科学基金"高比例新能源场景下电网暂态支撑能力评估理论与提升方法"(52177112) （52177112）
浙江能源天然气集团有限公司支撑课题"天然气管道掺氢、输送、分离应用技术研究及浙能先导示范项目"(ZNKJ-2021-108) （ZNKJ-2021-108）
