内蒙古农业大学学报（自然科学版）2026，Vol.47Issue(5)：79-88,10.DOI:10.16853/j.cnki.1009-3575.2026.05.009
区块链架构下风光储电站超短期功率预测方法
Fusion Method for Blockchain-based Cyber-physical System of Wind-solar-storage Power Stations and Ultra-short-term Power Prediction
摘要
Abstract
The power prediction of wind-solar-storage power stations is fundamental to both the dispatch of the stations themselves and the dispatch of the larger power grid.To ensure the prediction process,the cyber-physical system(CPS)that underpins this pro-cess requires stronger security.Power forecasts to meet dispatch requirements need to ensure high accuracy,high-frequency up-dates,short time scales,and multiple time scales.In this paper,a blockchain-based ultra-short-term power prediction method for wind-solar-storage power stations is proposed.The blockchain-based two-layer architecture of wind-solar-storage power station cyber-physical system can weaken the dependence on the physical topology of the storage power station and eliminate the vulnerability when responding to attacks.The improved spatiotemporal graph convolutional network algorithm can increase parameter scale flexi-bility and inter-parameter correlation to improve prediction accuracy.Combining these two in a blockchain smart contract,forming a blockchain-based ultra-short-term power prediction method for wind-solar-storage power stations,ensures the security of the predic-tion process and the prediction results.At the end,the proposed method is validated through case studies,demonstrating its effec-tiveness.The average error in electricity load forecasting is reduced by at least 1.22%,the average error in heat load forecasting is reduced by at least 4.70%,the average error in cooling load forecasting is reduced by at least 1.60%,and the average absolute error in renewable energy output forecasting is reduced by at least 2.17%.关键词
区块链/智能合约/风光储电站/信息物理系统/超短期功率预测/时空图卷积算法Key words
Blockchain/Smart contract/Wind-solar-storage power station/Cyber-physical system/Ultra-short-term power prediction/Spatiotemporal graph convolutional algorithm分类
信息技术与安全科学引用本文复制引用
傅思敏,孙华忠,孙跃,龚钢军..区块链架构下风光储电站超短期功率预测方法[J].内蒙古农业大学学报（自然科学版）,2026,47(5):79-88,10.基金项目
国网山东省电力公司科技项目(2024A-027) （2024A-027）
