Data-Driven Optimization Framework for Voltage Regulation in Distribution Systems
Tianqi Hong, Yichen Zhang
Abstract
This letter proposes a data-driven optimization framework for voltage regulation problems to address the challenge of model inaccuracy and parameter varying. To achieve online voltage optimization, the recursive kernel regression and interior point methods are integrated. The IEEE 123-Bus system and EPRI Ckt5 feeder are selected to validate the effectiveness of the proposed data-driven optimization framework. The proposed method is also compared with a linear function based method.
Topics & Concepts
VoltageOptimization problemComputer scienceKernel (algebra)Function (biology)System optimizationData modelingLinear programmingVoltage regulatorPoint (geometry)Mathematical optimizationControl theory (sociology)EngineeringElectronic engineeringAlgorithmMathematicsElectrical engineeringCombinatoricsArtificial intelligenceBiologyEvolutionary biologyControl (management)DatabaseGeometryOptimal Power Flow DistributionElectric Power System OptimizationSmart Grid Energy Management