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Physics-informed Gaussian process regression for states estimation and forecasting in power grids

Alexandre M. Tartakovsky, Tong Ma, David A. Barajas‐Solano, Ramakrishna Tipireddy

2022International Journal of Forecasting22 citationsDOIOpen Access PDF

Topics & Concepts

KrigingKalman filterEnsemble Kalman filterComputer scienceGridGaussianGaussian processStochastic differential equationMonte Carlo methodData assimilationGround-penetrating radarMathematical optimizationApplied mathematicsAlgorithmMathematicsStatisticsMeteorologyExtended Kalman filterArtificial intelligenceMachine learningPhysicsRadarTelecommunicationsQuantum mechanicsGeometryEnergy Load and Power ForecastingReservoir Engineering and Simulation MethodsMeteorological Phenomena and Simulations
Physics-informed Gaussian process regression for states estimation and forecasting in power grids | Litcius