Power Load Forecasting Based on Particle Swarm Optimization Algorithm
In response to the problem of non adaptation to nonlinear relationships in traditional power load forecasting,an improved particle swarm optimization algorithm based on Levy flight strategy is proposed.Firstly,the original dataset is optimized using a discretization approach,and three key parameters are identified through data mining.Then,by introducing the Levy flight strategy,the algorithm adjusts particle positions more flexibly during the optimization process,effectively improving the accuracy and global search performance of power load forecasting.The superiority of the LPSO algorithm has been confirmed through experiments,providing a more reliable prediction tool for power system operation.
distribution networkbig datadata analysisload forecasting
NETL
NSTL
万方数据
