Battery energy storage (BES) can provide many grid services, such as power flow management to reduce distribution grid overloading. It is desirable to minimise BES storage capacities to reduce investment costs. However, it is not always clear how battery sizing is affected by battery siting and power flow simultaneity (PFS). This paper describes a method to compare the battery capacity required to provide grid services for different battery siting configurations and variable PFSs. The method was implemented by modelling a standard test grid with artificial power flow patterns and different battery siting configurations. The storage capacity of each configuration was minimised to determine how these variables affect the minimum storage capacity required to maintain power flows below a given threshold. In this case, a battery located at the transformer required 10–20% more capacity than a battery located centrally on the grid, or several batteries distributed throughout the grid, depending on PFS. The differences in capacity requirements were largely attributed to the ability of a BES configuration to mitigate network losses. The method presented in this paper can be used to compare BES capacity requirements for different battery siting configurations, power flow patterns, grid services, and grid characteristics.
The ever-increasing electrification of society has been a cause of utility grid issues in many regions around the world. With the increased adoption of electric vehicles (EVs) in the Netherlands, many new charge points (CPs) are required. A common installation practice of CPs is to group multiple CPs together on a single grid connection, the so-called charging hub. To further ensure EVs are adequately charged, various control strategies can be employed, or a stationary battery can be connected to this network. A pilot project in Amsterdam was used as a case study to validate the Python model developed in this study using the measured data. This paper presents an optimisation of the battery energy storage capacity and the grid connection capacity for such a P&R-based charging hub with various load profiles and various battery system costs. A variety of battery control strategies were simulated using both the optimal system sizing and the case study sizing. A recommendation for a control strategy is proposed.
Electrification of residential areas is increasingly common. Major areas of development include rooftop solar panels, electric vehicles and heat pumps. However, existing grid components may have insufficient network capacity to accommodate the resulting electricity flows. Battery energy storage (BES) can be used to prevent transformer overloading resulting from electrification. Ideally, BES should be sized and placed such that it can prevent overloading with a minimum amount of storage capacity, but it is unclear how load characteristics affect BES capacity requirements. This study investigated how load simultaneity affects the minimum BES capacity required to prevent transformer overloading, comparing a central with a distributed BES layout. It was found that as simultaneity increases, distributed storage requires relatively less capacity than central storage. This is likely due to the reduced ability of central BES to share capacity between connections as simultaneity increases, and the ability of distributed BES to better reduce transportation losses.
