Abstract: A distribution network optimization method based on improved particle swarm optimization algorithm is proposed for the optimization problem of source grid load interaction. Firstly, a mathematical model was constructed that comprehensively considers the interaction between power generation, distribution network, and load to describe the dynamic coupling relationship between the three. Secondly, a dynamic reconstruction method for the distribution network was proposed, which adjusts the topology structure of the grid by controlling switch devices to improve system stability and reliability. Models were established for power balance constraints, voltage constraints, and switch state constraints. In order to improve the solution accuracy and optimization efficiency, this paper improves the traditional particle swarm optimization algorithm and proposes improvement strategies such as adaptive inertia weight, local search mechanism, and mutation operation to enhance the global search ability and avoid getting stuck in local optimal solutions. The experimental results show that the algorithm proposed in this paper can find the optimal solution in a relatively short period of time, adapting to the needs of real-time scheduling and dynamic optimization. In summary, this article provides an efficient and reliable solution for optimizing the distribution network.