Energy Storage Capacity Allocation and Economic Evaluation for Improving PV Short-term Forecast Accuracy

Photovoltaic(PV) short-term forecast accuracy is not high and it is difficult to meet the scheduling requirements. Energy storage devices can improve the PV forecast accuracy, but there is a contradiction among improving forecast accuracy, energy storage capacity allocation and economics. In this paper, the probability density estimation method is used to analyze the distribution characteristics of PV prediction errors. A calculation model for energy storage allocation is established taking into account the relationship between economy, prediction accuracy and capacity. An optimal control strategy for energy storage charge and discharge with a better tracking prediction value is constructed by using the principle of “replenishment of the shortage”. The tracking-economic factor is introduced to obtain the economic evaluation method of energy storage device. The simulation analysis shows that the PV prediction error has a normal distribution characteristic, and the established control strategy is effective and practicable. The method proposed prevents the energy storage device from being fast and complete Charging and discharging process while improving the accuracy of PV short-term output prediction. Therefore, the economic utilization level of the energy storage device is improved.