Abstract: For the location optimization of the peak load cutting and valley filling of the BIPV building,considering network loss and voltage deviation after connecting to the distribution network, an optimization model of the BIPV building double-layer energy system is proposed in this paper.Considering the DG cost and the environment cost,the lower layer of the model uses energy storage to cut the peak load and fill the valley load,while the upper layer of the model optimizes the location scheme of the BIPV and energy storage under the premise of considering distribution network loss and voltage deviation. An improved multi-objective quantum particle swarm optimization algorithm is designed using the quantum behavior and probability expression characteristics of quantum theory when solving the double-layer model. A dynamic ε infeasibility constraint dominating function is introduced to deal with the solution. Finally,taking the IEEE30 bus system as a reference system,the optimization results show that the load peak-valley difference of the BIPV building,the distribution network loss and the voltage deviation are effectively reduced,which proves that the proposed configuration optimization strategy is feasible.At the same time, the results also show that the global optimization ability and population diversity of the proposed algorithm are significantly improved.