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Integration of distributed generations into distribution networks has become one of the important features of new power systems. The integration of distributed generation and the uncertainty of power generation make the power flow in distribution networks complex and variable, which poses higher technical requirements for rapid fault location in distribution networks. However, existing intelligent optimization algorithms may encounter problems such as slow convergence speed and susceptibility to local optimization when solving the problem of fault section location in distribution networks. To address these challenges and problems, a rapid fault section location technology based on quantum ant colony algorithm (QACA) is proposed. First, a location mathematical model is constructed based on the state approximation idea and the minimum fault set theory. Then, an information self-correction method is proposed for the missing information uploaded by feeder terminal unit, and a hierarchical location model is proposed to shorten the location time. Afterwards, three improvement techniques are proposed to improve the QACA. The update mechanism of the quantum rotary gate is improved, the rotation angle is dynamically adjusted in the form of function control, and the elite strategy is introduced to accelerate the convergence speed of the algorithm. Finally, after the key parameters are determined, the effectiveness of the improved technique, the information self-correction method, and the hierarchical positioning model is verified. A comparison with 7 different algorithms indicates that the improved QACA can effectively locate the fault section, and has a fast convergence speed, great accuracy, and fault tolerance.