How to achieve energy storage by distributed energy storage on the low voltage side

Why should energy storage systems be strategically located?

An appropriately dimensioned and strategically located energy storage system has the potential to effectively address peak energy demand, optimize the addition of renewable and distributed energy sources, assist in managing the power quality and reduce the expenses associated with expanding distribution networks.

Can energy storage systems improve PV accommodation capacity?

The use of only flexible interconnections between distribution areas with a high proportion of PVs may not achieve complete PV accommodation. Furthermore, some scholars have demonstrated that the accommodation capacity of PV can be improved by configuring energy storage systems (ESSs) [18-20].

Can flexible interconnections and energy storage systems improve accommodation capacity?

To address these problems, we propose a coordinated planning method for flexible interconnections and energy storage systems (ESSs) to improve the accommodation capacity of DPVs. First, the power-transfer characteristics of flexible interconnection and ESSs are analyzed.

How does load level affect the charging/discharging process?

The load level has an impact on the charging/discharging process. The state of ESSs is contingent upon the daily energy consumption. Consequently, during periods of insufficient energy supply, particularly when the demand is at its peak, ESSs operate as generators, redistributing the load among themselves.

Can lvdn improve PV accommodation capacity?

Finally, at night, the ESS discharged power, and VSC2 utilized the power complementarity to alleviate the overload problem of the distribution transformer in area 2. Overall, the effectiveness of the proposed planning method was validated through an actual LVDN scenario, which verified its advantages in enhancing the PV accommodation capacity.

How can dandelion optimize ESSs in a distribution network?

This study proposes an efficient approach utilizing the Dandelion Optimizer (DO) to find the optimal placement and sizing of ESSs in a distribution network. The goal is to reduce the overall annual cost of the system, which includes expenses related to power losses, voltage deviation, and peak load damand.