In this paper, the uncertainty of the source and load of the microgrid is considered to be studied. Aiming at the uncertainty of load side fluctuation caused by electric vehicles connected to microgrid charging, the orderly charge-discharge strategy is proposed for peak clipping and valley filling and a multi-objective programming model is constructed. Information Gap Decision Theory (IGDT) is introduced to simulate and analyze the uncertainty of generating capacity of new energy units. Firstly, a multi-objective programming function is constructed, then processed by fuzzy normalization. Secondly, the Improved Chaotic Mapping Particle Swarm Optimization algorithm is introduced to obtain the optimal value of the comprehensive operation cost and load demand fluctuation of microgrid. Finally, the multi-objective model optimized by IGDT is simulated and analyzed. The results of the example verify that the optimized model plays a better role in peak-cutting and valley filling for the load fluctuation caused by electric vehicles entering the network. Compared with other optimization methods, the proposed IGDT optimization model can better adapt to the severe Knightian uncertainty scenario and coordinate the contradictory relationship between robustness and economy.