In order to deal with the large day-ahead dispatch deviation of microgrid caused by the uncertainty of wind and solar output

the random fuzzy theory is introduced into the optimization operation of AC/DC hybrid microgrid. Based on the uncertainty theory

the wind speed is defined as a random fuzzy variable

and the membership functions of the Weibull distribution parameters are extracted by the maximum likelihood method

so that a random fuzzy chance constrained optimization model to minimizing the day-ahead dispatch cost is established. The random fuzzy simulation

neural network and chaotic particle swarm optimization algorithm are combined to solve the dual-uncertainty optimization model. By setting three scenarios: deterministic

stochastic and random fuzziness

the day-ahead dispatch schedule and the intra-day unbalanced power adjustment program of the three scenarios are analyzed. The correctness and feasibility of the random fuzzy dual-uncertainty model in the optimal operation of AC/DC hybrid microgrid are verified.