Big Data Feature Mining Method for Energy Storage System of Photovoltaic Power Station in Typical Scenarios

The energy storage system can effectively solve the challenges brought by the high proportion of renewable energy access to the power grid. In this paper, a big data feature mining method based on double-layer intelligent optimization algorithm is proposed. Considering the differences in operating conditions of energy storage systems in photovoltaic power stations caused by different seasonal scenarios and different weather scenarios, the improved bird swarm algorithm is proposed to mine the big data features of energy storage systems in photovoltaic power stations under typical weather scenarios. The inherent operation law of the energy storage system in the actual photovoltaic power station is revealed, and the charging and discharging characteristics of the actual energy storage system are reflected.