In order to solve the problem of low accuracy of industrial structure optimization of digital economy in Active Distribution Network (ADN), the research on industrial structure optimization and development model of digital economy based on data driven was proposed. This paper analyzes the components of the total operating cost of ADN, and takes the minimum total operating cost of ADN as the objective function, comprehensively considers various constraints, and establishes an economic optimal scheduling model of ADN based on the Elite Strategy Cuckoo Search (ESCS). The Cuckoo Search (CS) algorithm is improved by using the dynamic setting of bird egg detection probability and elite strategy to improve the optimization performance of the algorithm. The IEEE33 bus distribution system is used for simulation analysis. The experimental results show that: in terms of the number of convergence iterations, the number of iterations of the ESCS algorithm is 52, which is far less than the other three optimization algorithms. From the perspective of the optimal solution, the solution accuracy of the ESCS algorithm is also higher than the other three optimization algorithms. It can be seen that the ESCS algorithm can effectively reduce the number of iterations and improve the calculation accuracy.