## 1 Introduction
### Literature Review  
The voltage control in the distribution system utilizing BESS has been studied by researchers in the past decade. The work in [20], for instance, proposes a mitigation strategy for voltage rise or drop in LV distribution networks with the installation of solar PV using battery storage. The authors assume that each of the rooftop PV systems is equipped with a battery. For the battery operation protocol, an iterative method is employed for dispatching the battery charging/discharging, which is based on local information. Two practical LV-distribution feeders located in Western Sydney, New South Wales, Australia, have been studied in connection with rooftop residential PV systems with rated capacities of 2-4 kW. The authors conclude that a proper selection of the charging/discharging rate is required for the effective daily utilization of the battery storage devices. In [21], the authors use the Fourier series description based on a day-ahead energy forecast for the optimal daily charging/discharging of batteries to minimize battery losses, cyclic battery cost, and the network voltage profile. A total of 26 batteries are randomly placed along three phases of the LV distribution feeder. In this study, the management of batteries is accomplished by the data management system using hierarchical bi-directional communication infrastructures. The analysis reveals that the size and charging/discharging rates are significantly impacted by BESS locations and the number of controlled BESS. While [21] considered only an LV network, the same strategy is applied in [16] for the optimal siting of BESS in MV and LV distribution networks. The MV distribution network, the IEEE 33-test system, has a two wind distributed generation (DG) with a rate of 1 MW and seven PV DG; three of the PV have a rate of 400 kVA and four have a rate of 500 kVA. In this study, the optimal placement of BESS is based on centralized batteries in both MV and LV networks. Results reflect that the tradeoffs between desired services, including voltage regulation, loss reduction, and battery parameters, are greatly influenced by the battery storage location. The optimal siting, sizing, and operation of BESS in distribution grids with renewable integration have a crucial impact on their overall efficiency and performance. Furthermore,the distributed BESS brings about better benefits to distribution networks if allocated in a distributed manner than in centralized ones [9]. Many studies have been conducted to tackle the ideal allocation and capacity of BESS. Reference [22], for instance, discusses the optimal allocation and sizing problem of 25 BESS in a distribution system. The goal of this study is to minimize voltage deviation and network losses while also addressing the capital and operation lifetime of BESS. The objective function is tackled by a genetic algorithm (GA) based on multilayer objective optimization. For battery operation, linear programming (LP) is utilized to minimize the daily non-coincident peak demand. Their study reveals a distinct relation between the BESS capacity and location decisions and voltage improvement. Furthermore, the researchers in [23] propose a controlling strategy to identify the optimal location, capacity, and operational characteristics of different BESS in a distribution system with PV generation. The latter objectives are achieved by maximizing the total net present value (NPV). In this study, the GA is utilized to maximize the NPV, while the battery charging/discharging strategy was managed by an iterative and analytical approach using the load following method. By determining the optimal location, size, and operation of BESS, results demonstrate that several economic benefits can be obtained, including energy arbitrage, peaking power generation, energy loss reduction, system upgrade deferral, a reduction in CO2 emissions, and reactive power support. The study assumed that PV units are placed at all system busses to represent rooftop solar PV with a total annual PV generation of 28.62%.