An Energy Storage Optimization Control Method to Compensate Photovoltaic Prediction error

The demand for renewable energy drives the integration of more and more distributed generation equipment into distribution grid, such as photovoltaics (PV), which are highly random and volatile. PV is considered to be one of the renewable energy sources with the greatest potential for installation at the user side. PV is installed quickly and convenient for site selection, and installed capacity of PV on the distribution network side is growing rapidly. PV output is highly volatile, so power must be forecasted to provide reference for dispatching. Limited by current forecasting technology, it is impossible to eliminate prediction error, so there is still an unstable factor in the power system. In this paper, a hybrid energy storage system (HESS) control strategy is proposed. Under the premise of meeting the system operation requirements, the adjustment potential of the energy storage equipment installed on the supporting installation is mobilized, and operating cost of the energy storage equipment is considered. The error caused by the prediction is compensated with a small cost, which is conducive to the equipment running according to the scheduling curve. Finally, the predicted value and actual value of a PV station are selected to verify the effectiveness of proposed strategy.