基于大数据的调峰火力发电机组化学性能预测方法

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中图分类号：TM611 文献标志码：A 文章编号：2095-2945（2025）34-0090-04

Abstract：Asthermalpowergeneratingunitsgraduallymovetowardsintellgentandeficientoperation，monitoringand predictingchemicalpropertiesofunitshavebecomeanimportantmeans toensurestableoperationandextendequipmentservice life.Chemicalreactionssuchascorosion，scalingandsaltacumulationhaveaprofoundimpactonthesafetyandeconomyof theunit.Thispaperanalyzestheimpactofchemicalcompositiononthermalpowerunits，studiesamulti-dimensionalprediction methodbasedonbigdata，andproposesamulti-factoranalysismodelcombiningsupportvectormachinealgorithmtoimprove the prediction accuracy of chemical properties of unit operation.

Keywords：bigdata;peak shaving thermalpowerunit;chemical performanceprediction;corosionprocess;vectormachine

火力发电机组是电力系统中重要的调峰设备，其运行安全与设备的化学性能密切相关。（剩余5700字）