Abstract: In response to the typical optimization problem of economic load dispatch（ELD） in power systems, this paper proposes a combination of adaptive weight updating strategy and differential evolution random mutation strategy in the whale optimization algorithm（ADWOA）. Firstly, an adaptive weight is introduced into the WOA algorithm to enhance its capturing ability, allowing the algorithm to perform fine-grained global search in the early stages and precise local search in the later stages, thus accelerating the iteration of the optimization algorithm. Simultaneously, due to the random mutation strategy, positions are updated again. Then, the best position is selected from the updated results to expedite the convergence of the population. Finally, multiple bio-inspired algorithms are compared for solving the ELD problem. The results validate that the ADWOA algorithm can better solve the ELD problem, quickly find the optimal solution, and achieve low-cost load allocation.