Based on the spot market trading mechanism of source network and load storage revenue allocation, a planning model of the joint optical storage system is constructed, which realizes the effective planning for both internal and external layers of the system under multiple constraints. The enhanced multi-objective particle swarm optimization algorithm involves a dispersal mechanism and conducts a global search of the best configuration of the integrated source-grid-load-storage system by adjusting the positions of particles, enhancing their diversity, and other similar operations. A series of experiments is conducted to test the effectiveness of such coordinated planning strategy in the context of the integrated source-grid-load-storage structure. The IMOPSO algorithm presented in this work can be well applied to models of different dimensionality and computational complexity. The findings on three planned scenarios show that in the framework of coordinated source-grid-load-storage planning, the optimal scheduling scheme and the energy cost at the operational level impact the value of the objective function and the configuration of the power generation machinery at the planning level, whereas the optimized planning-level configuration further influences the combination of unit outputs in operation. They are interrelated.
