Research on Capacity Optimization Allocation Strategy of Photovoltaic Multi-Component Energy Storage System in Random Scenario

The configuration of hybrid energy storage system for photovoltaic (PV) power generation is an effective way to deal with intermittent and random output of PV system. To satisfy the demands of PV multi-component energy storage system on stability and economy, this paper presents a capacity optimization allocation method for PV integrated multi-component energy storage system in random scenarios. In this paper, five energy storage methods, namely lithium iron phosphate, all-vanadium flow, lithium-ion capacitor, hydrogen fuel cell and flywheel, are selected to construct a hybrid energy storage system. Then, with the system power loss rate as the inner objective, the lowest life cycle cost as the outer objective function, and the capacity, power and energy storage SOC limits as constraints, the two-layer capacity optimization configuration model is constructed. Meanwhile, k-means clustering algorithm is used in the model to realize the typical daily PV output data selection, and the daily power allocation is realized on the basis of variational mode decomposition (VMD) algorithm. Finally, VMD-NSGA-II algorithm is applied to resolve the capacity optimization configuration model, and the results of VMD-PSO and traditional NSGA-II algorithm are compared. In the case of similar power loss rate, the whole life cycle cost are 678.32, 841.83 and 872.24 million yuan, respectively. The results showed that the selected method had significant advantages. Under the optimal configuration scheme, the life cycle cost of the hybrid energy storage system is 678.32 million yuan, which corresponds to a typical daily power loss rate of -0.74%.