In response to the impact of the randomness of wind and solar power generation and the high penetration rate of DG ( Distributed Generation ) on the grid, the IGAN ( Improved Generative Adversarial Network) and the IChOA( Improved Chimpanzee Optimization Algorithm) are integrated to construct a source-storage two-layer optimal configuration model for active distribution networks. Firstly, IGAN is used to generate typical wind and solar power generation scenarios to represent their uncertainty. Then, a source-storage two-layer optimization architecture containing voltage quality indicators is constructed. The upper layer uses IChOA to optimize the capacity and location configuration schemes of ESS(Energy Storage Systems) and DG, and the lower layer uses SOCP ( Second-Order Cone Programming) to solve the optimal daily dispatch strategy of energy

storage. Finally, the IEEE 33-node system verification shows that this collaborative strategy can significantly reduce the annualized cost and network loss of the system, improve the voltage level, and effectively avoid voltage limit violations and DG power fluctuations.

active distribution network, generative adversarial networks, improved chimpanzee optimization algorithm, distributed generation(DG), energy storage system(ESS)