The effective identification of multi-load switching behavior provides a powerful support for understanding the user"s electricity behavior, making energy-saving plans and achieving intelligent power consumption. Firstly, an improved binary particle swarm optimization (IBPSO) algorithm is proposed in order to solve the identification problem of simultaneous switching of multiple loads. And the distance measure method is introduced as the fitness function of the IBPSO algorithm. In view of the fact that the accuracy of the identification of single load characteristic is not ideal at present, the current harmonics and active power are considered as the characteristics of load switching behavior. Finally, a large number of simulation tests are carried out on the current and power information extracted from multi-load switching. Simulation results show that the proposed algorithm improves the convergence speed and accuracy of the identification of multi-load switching behavior.