The invention relates to an NSGA-II and approximate dynamic programming-based multi-objective dynamic optimal power flow solving method and belongs to the power system day-ahead scheduling programming research field. The method includes the following steps that: relevant data of a system in the next scheduling period are obtained; with minimum power generation consumption, pollutant emission quantity and network loss adopted as objectives, and node secure voltage and reactive power out as constraints, a multi-objective dynamic optimal power flow model is established; the NSGA-II is adopted to solve a Pareto solution set at each single time section, and a single-time section continuous decision space is discretized, the fuzzy satisfaction degree of a non-dominated solution is adopted as a value function, and the model is transformed to a multi-time section dynamic plan problem based on dynamic constraints of time section coupling; and a policy iteration dynamic programming method is adopted to solve the model, so that a path with maximum cumulative satisfaction degree, namely, the optimal solution of multi-objective dynamic optimal power flow, can be obtained. According to the NSGA-II and approximate dynamic programming-based multi-objective dynamic optimal power flow solving method of the invention, the NSGA-II and the dynamic approximate programming method are combined to solve problems in multi-objective optimal power, and a multi-objective optimization problem containing continuous variables and a problem of curse of dimensionality of traditional dynamic programming can be solved comprehensively.