A novel model based on CEEMDAN, IWOA, and LSTM for ultra-short-term wind power forecasting
Shaomei Yang, Aijia Yuan, Zhengqin Yu
Topics & Concepts
ResidualWind powerWind power forecastingTerm (time)Computer scienceHilbert–Huang transformPartial autocorrelation functionNoise (video)RandomnessAutocorrelationPower (physics)Mode (computer interface)OverfittingAlgorithmElectric power systemMeteorologyWhite noiseArtificial intelligenceTime seriesMathematicsStatisticsMachine learningEngineeringArtificial neural networkAutoregressive integrated moving averageTelecommunicationsImage (mathematics)Electrical engineeringQuantum mechanicsOperating systemPhysicsEnergy Load and Power ForecastingElectric Power System OptimizationWind Energy Research and Development