Voltage Source Converters (VSC) are increasingly used due to the growing demand for renewable energy resources (RES) and distributed energy resources (DES). Among the various control strategies, the virtual synchronous generator (VSG) has emerged as a popular choice, which makes converters to emulate the behaviour of real synchronous generators (SG). However, the conventional VSG faces several challenges, such as difficulty including current limits and instability when connected to the grid with a high short circuit ratio. To overcome the drawbacks, this thesis proposes a novel current source interfaced VSG that emulates the dynamics of an SG while operating as a current source interface. Before designing the current source interfaced VSG, a control method to make the converter act as a high-bandwidth and high-precision current source is required and is proposed in this thesis. The novel hysteresis current controller using acceleration slope utilizes the multiple voltage steps available with the modular multilevel converter (MMC) to adjust the rate of change of current depending on whether it deviates significantly from the target current. Both the Electromagnetic Transients (EMT) simulation and hardware-in-loop (HIL) experiment validate the successful operation of the proposed method. Using the proposed hysteresis current controller, a current source interfaced VSG named synchronous machine emulation VSG is introduced then. This approach can easily implement inherent current limiting by constraining the current reference magnitude. It also allows one to represent the VSG with the differential equations of an actual SG with as much detail as desired, such as the number of d- and q-axis windings, etc. Both small signal analysis and EMT simulation results show that the VSG remains stable not only in weak systems but also in ultra-stiff systems, which was identified as a challenge for earlier conventional VSG implementations. The thesis also investigates the effect of damper windings through small signal analysis. Moreover, the proposed VSG parameters are not restricted to physical machine ranges, which enables the assignment of arbitrary parameter values. The genetic algorithm (GA) is used to optimize the parameters to obtain better performance.