江西水利电力大学学报2026，Vol.45Issue(1)：66-72,7.
基于XGBoost的江西省能源需求预测与储能发展路径研究
Energy demand prediction and energy storage technology paths based on XGBoost
摘要
Abstract
Driven by the"dual carbon"goals,green and low-carbon development has become a distinctive feature of China's energy structure.However,significant disparities exist among provinces in terms of energy resource endowments,economic development models and industrial structures.Consequently,the importance of provincial energy development planning and energy storage path research has become increasingly prominent.First,we develop an energy demand prediction model based on the Extreme Gradient Boosting algorithm to analyze energy demand under different economic growth scenarios.Second,we quantitatively assess suitable energy storage technology path for Jiangxi Province from such dimensions as technical advanta-ges,environmental benefits,and economic performance.Finally,we take Hongping Pumped Storage Power Station and Yans-han Advanced Compressed Air Energy Storage Plant as examples,analysing their comprehensive benefits.The results indi-cate that pumped storage technology is mature and highly beneficial,yet its deployment is constrained by geographical condi-tions and presents significant layout challenges.In contrast,compressed air energy storage offers greater flexibility,though its conversion efficiency requires further improvement.Although electrochemical storage and hydrogen energy storage still face challenges related to higher costs and technical bottlenecks,they play crucial roles in the new power system.Electrochemical storage provides flexible and rapid configuration,whereas hydrogen storage offers the advantages of long-duration energy stor-age and cross-sector applications.While vigorously developing pumped storage,Jiangxi Province should also actively promote the development of diversified storage methods,including compressed air,electrochemical and hydrogen storage,to meet en-ergy storage demands across various scenarios.关键词
能源需求/经济增长/能源转型/抽水蓄能/储能技术Key words
energy demand/economic growth/energy transition/pumped hydro storage/energy storage technology分类
资源环境引用本文复制引用
宋泽宁,周挺,毛清祥,胡卓,彭钰璋,谢明祥..基于XGBoost的江西省能源需求预测与储能发展路径研究[J].江西水利电力大学学报,2026,45(1):66-72,7.基金项目
国家自然科学基金项目(51969017) （51969017）
江西水利电力大学研究生创新计划项目(YJSCX202415) （YJSCX202415）
