K-Nearest Neighbor Algorithm Applied to Accelerate Security Constrained Unit Commitment Problem
With the expansion of power grid scale and the higher requirements of security,the difficulty in solving the security constrained unit commitment(SCUC)is increasing.Aiming at the characteristics of constraints of active power over transmission lines and 0-1 on/off integer variables in the SCUC,two prediction methods are constructed based on improved K-nearest neighbor algorithm,which are used to identify the active transmission power constraints and determine the values of partial integer variables respectively.At the same time,considering the influence of load parameters on the values of integer variables,the action interval of the integer variables is limited to improve the prediction accuracy.Before solving the problem,two forecasting methods can quickly predict the active transmission power constraints and the values of partial integer variables.Using this information,a simplified SCUC model can be built,and then the optimization solver can be used to solve the model directly,shortening the solution time of the SCUC.Finally,the correctness and effectiveness of the proposed method are verified by the standard test system and an actual provincial grid data.
security constrained unit commitmenttransmission power constraintsmixed-integer linear programmingK-nearest neighbor algorithm
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