基于机器学习的风光功率预测系统研究

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中图分类号：TP181 文献标志码：A 文章编号：2095-2945（2025）13-0113-05

Abstract：Withtherapiddevelopmentofrenewableenergytechnologies，addressingtheinherentstochasticity，fluctuations， andintermitencyofwindandsolarpowergenerationthroughadvancedartificialinteligencehasbecomecriticalforindustry advanceent.Thisstudyproposesasmaitintegrated，andonestopforecastingsystemarchitecturecomprisingtwocoreodules： amachinelearningalgorithmmanagementplatformformodeldevelopmentandoptimization，andaforecastingsupportservice platformforoperationaldecision-making.Thesystemprovidesend-to-endtechnicalsupportspanningmodeltraining，algorithm selection，scenario-specificservices，energytradingassistance，andbenefitalocationmechanisms.Byenablingnationwidesharing ofdataresources，optimizedalgorithms，andcloudplatforms，thisframeworkofersanovelsolutiontoenhanceprediction accuracy，timeliness，and grid integration efficiency for hybrid renewable energy systems.

Keywords： machine learning; wind power; solar power; power forecasting; system

近年来，随着全球气候变化的日益严峻，人们对减少二氧化碳排放的需求不断增长，截至2024年底，我国以风电、太阳能发电为主的新能源发电装机规模达到 ，首次超过火电装机规模。（剩余6281字）