面向统一能源系统的中长期氢负荷预测

doi:10.11930/j.issn.1004-9649.202007205

中国电力 ›› 2022, Vol. 55 ›› Issue (1): 84-90.DOI: 10.11930/j.issn.1004-9649.202007205

• 面向统一能源系统的氢综合利用技术专栏 • 上一篇下一篇

面向统一能源系统的中长期氢负荷预测

彭生江^1,2, 孙传帅³, 妥建军¹, 袁铁江³

1. 甘肃省电力公司经济技术研究院, 甘肃兰州 730000;
2. 华北电力大学经济与管理学院, 北京 102206;
3. 大连理工大学电气工程学院, 辽宁大连 116024

收稿日期:2020-07-25 修回日期:2021-09-28 出版日期:2022-01-28 发布日期:2022-01-20
作者简介:彭生江(1975-),男,博士研究生,高级工程师(教授级),从事电力系统规划设计与建设管理研究,E-mail:pshj@sina.com;孙传帅(1994-),男,通信作者,硕士,从事新能源并网研究,E-mail:1925397839@qq.com
基金资助:
国家自然科学基金资助项目（氢储能耦合分散式风电消纳研究，51577163）；国网甘肃省电力公司经济技术研究院科学技术项目（大规模风光互补制氢关键技术研究，52273018000 G）。

Medium and Long-Term Hydrogen Load Forecast for Unified Energy System

PENG Shengjiang^1,2, SUN Chuanshuai³, TUO Jianjun¹, YUAN Tiejiang³

1. Economic and Technical Research Institute of Gansu Electric Power Company, Lanzhou 730000, China;
2. School of Economics and Management, North China Electric Power University, Beijing 102206, China;
3. School of Electrical Engineering, Dalian University of Technology, Dalian 116024, China

Received:2020-07-25 Revised:2021-09-28 Online:2022-01-28 Published:2022-01-20
Supported by:
This work is supported by National Natural Science Foundation of China (Research on Hydrogen Energy Storage Coupled Distributed Wind Power Dissipation, No.51577163), Science and Technology Project of State Grid Gansu Provincial Electric Power Company Institute of Economics and Technology (Research on Key Technologies of Large-Scale Scenery-Complementary Hydrogen Production, No.52273018000 G）

摘要/Abstract

摘要： 未来能源社会中氢气将在电力、工业、供热、交通等领域发挥巨大作用，氢能将作为统一能源系统的关键要素，实现各能源相互转化。针对未来社会中氢能在工业、供热、交通等领域的需求，提出一种氢负荷预测的方法。获取工业领域的氢负荷样本数据，算出负荷数据的特征，采用支持向量机回归（SVR）算法，得到工业领域氢负荷预测模型；然后，以供热、交通领域需氢数据建立模型，采用改进灰色GM(1，1)模型与新陈代谢模型结合，得到供热、交通领域氢负荷预测模型；最后，叠加3种氢负荷预测，完成数学模型构建。从结果可以看出SVRT预测方法十分准确、改进灰色GM(1，1)模型与新陈代谢的组合模型组预测精度较高，该方法可用于中长期氢负荷预测。

关键词: 统一能源系统, 氢负荷, 支持向量机, 灰色模型, 预测

Abstract: In the future energy society, hydrogen will play a huge role in power system, industrial application, heating supply, transportation and other fields. Hydrogen energy will be used as the key element of the unified energy system to achieve the energy conversion between various energy sources. In this paper, a method of hydrogen load forecast is proposed for the future demand of hydrogen energy. Firstly, on the basis of the hydrogen load sample data from the industrial field, the characteristics of the load data are calculated and the support vector machine regression (SVR) algorithm is applied to set up the hydrogen load forecast model accordingly. Secondly, a model based on the hydrogen demand data in the heating supply and transportation fields are built as well, and the improved gray GM (1,1) model is utilized in combination with the metabolic model to obtain a hydrogen load forecast model in the heating supply and transportation fields. Finally, all above three hydrogen load forecast are superimposed together to complete the construction of the mathematical model. From the results, not only the SVRT prediction method is proved to be very accurate, but also the combined model group based on the improved gray GM (1,1) model and metabolism have demonstrated high forecast precision. This method is feasible for medium and long-term hydrogen load prediction.

Key words: unified energy system, hydrogen load, support vector machine, gray model, prediction

彭生江, 孙传帅, 妥建军, 袁铁江. 面向统一能源系统的中长期氢负荷预测[J]. 中国电力, 2022, 55(1): 84-90.

PENG Shengjiang, SUN Chuanshuai, TUO Jianjun, YUAN Tiejiang. Medium and Long-Term Hydrogen Load Forecast for Unified Energy System[J]. Electric Power, 2022, 55(1): 84-90.

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面向统一能源系统的中长期氢负荷预测

Medium and Long-Term Hydrogen Load Forecast for Unified Energy System

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面向统一能源系统的中长期氢负荷预测

Medium and Long-Term Hydrogen Load Forecast for Unified Energy System

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