The invention discloses a hybrid learning-based adaptive real-time energy management method for a more-electric aircraft. The method comprises the steps of S1, establishing a more-electric aircraft energy management model; s2, in an off-line stage, acquiring load configuration data of the more-electric aircraft and inputting the load configuration data into a commercial solver in batches to obtain a solving result of the model, and forming a data set; s3, establishing an integrated deep neural network model; s4, training an integrated deep neural network model based on the data set; and S5, in an online stage, inputting real-time operation scene data into the trained model to obtain an integer solution, judging the feasibility of the integer solution, solving other continuous variables of the more-electric aircraft energy management model by adopting a commercial solver when the integer solution is feasible, otherwise, abandoning the integer solution, and obtaining all variables of the more-electric aircraft energy management model by adopting the commercial solver. The method can adapt to the dynamic operation scene of the more-electric aircraft, reduces the occupation of computing resources, reduces the solving time, improves the energy scheduling rate, and has the real-time performance, the self-adaption performance and the optimality.