Renewable energy sources (wind turbine and photovoltaic system) are connected to the smart grid to promote the grid power, but the output of these sources is changed due to the sunlight and wind speed variations. Power storage system has the ability to reduce variations in a power system. Battery energy storage system (BESS) and superconducting magnetic energy storage system (SMES) are good solutions for this problem. The storage unit is connected to a power system at the point of common coupling and is able to absorb/store both active and reactive powers from this system and inject them into the power system in the peak demand periods. A control strategy based on proportional-integrative-derivative (PID) and model predictive controller (MPC) are used to control (SMES/BESS) to enhance the transient performance of a smart grid. The proposed algorithm has been tested on standard IEEE 5-bus system connected to wind turbine distributed generator, non-linear loads, and storage device (BESS/SMES) to verify the superiority of the presented method. The simulation results show that the performance of SMES with PID is more efficient than BESS with PID, but they have nearly the same output when MPC control strategy is used. 2 Types of energy storage devices The increasing focus on large-scale integration of renewable energy sources (wind turbine and photovoltaic system) introduces

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Recently, the offshore wind farms (OWFs) have excellent potential in global power networks. So, the demand for high power and high‐quality transmission system is becoming more pressing with the fast growth of OWFs. A promising solution is provided by the voltage source converter‐high voltage direct current (VSC‐HVDC) system. This paper proposes a control method for controlling the VSC‐HVDC system to integrate OWFs into power grids based on model predictive control (MPC). To minimise the distortion and filtering of the harmonics injected into the utility grid, the receiving end converter of the VSC‐HVDC system is connected with LCL filter. The proposed control strategy maintains active/reactive power‐sharing with efficient regulation of AC voltage among the different OWFs operation conditions. The detailed system components modelling and simulation are executed in the MATLAB/Simulink environment, which is used to perform both dynamics and transient evaluation of the suggested control strategy. The acquired simulation results emphasize the capability of the proposed control strategy to maintain system stability under different operation conditions compared to the synchronous reference frame‐based current limiting droop control method (SRF‐based CLD).

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