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• W2967769938 abstract "Frequency control represents a critically significant issue for the enhancement of the dynamic performance of isolated micro grids. The micro grid system studied here was a wind–diesel system. A new and robust optimization technique called the mine blast algorithm (MBA) was designed for tuning the PID (proportional–integral–differential) gains of the blade pitch controller of the wind turbine side and the gains of the superconducting magnetic energy storage (SMES) controller. SMES was implemented to release and absorb active power quickly in order to achieve a balance between generation and load power, and thereby control system frequency. The minimization of frequency and output wind power deviations were considered as objective functions for the PID controller of the wind turbine, and the diesel frequency and power deviations were used as objective functions for optimizing the SMES controller gains. Different case studies were considered by applying disturbances in input wind, load power, and wind gust, and sensitivity analysis was conducted by applying harsh conditions with varying fluid coupling parameter of the wind–diesel hybrid system. The proposed MBA–SMES was compared with MBA (tuned PID pitch controller) and classical PI control systems in the Matlab environment. Simulation results showed that the MBA–SMES scheme damped the oscillations in the system output responses and improved the system performance by reducing the overshoot by 75% and 36% from classical and MBA-based systems, respectively, reduced the settling time by 45% compared to other systems, and set the final steady-state error of the frequency deviation to zero compared to other systems. The proposed scheme was extremely robust to disturbances and parameter variations." @default.
• W2967769938 created "2019-08-22" @default.
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• W2967769938 date "2019-08-13" @default.
• W2967769938 modified "2023-09-26" @default.
• W2967769938 title "Performance Enhancement of Micro Grid System with SMES Storage System Based on Mine Blast Optimization Algorithm" @default.
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• W2967769938 doi "https://doi.org/10.3390/en12163110" @default.
• W2967769938 hasPublicationYear "2019" @default.
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