Discrete Fourier Transform and Correlation Analysis on Highly Penetrated Variable Renewable Energy System to Achieve Frequency Stability

Renewable energy has been emerging due to global needs. However, the renewable energy power plant’s active power fluctuation will affect the frequency deviation signal. This paper presents a method to reduce frequency fluctuation using Discrete Fourier Transform and Correlation analysis. From the initial simulation, the frequency deviation signal exceeds the limit $(\pm 0.2$ Hz) obtained by conducting the quasi-dynamic analysis due to the fluctuation of solar plant and wind turbine generators. The quasi-dynamic analysis is also compared to the RMS analysis in terms of better time efficiency while simulating the frequency deviation of the system due to the fluctuation of the intermittent power plants. This paper uses a mathematical analysis approach by transforming the time domain signal to the frequency domain signal using Discrete Fourier Transform. The Discrete Fourier Transform transforms the time domain signal of the solar irradiation, wind speed, and frequency deviation signals in a day into the frequency domain signal. The filtered solar irradiation and the wind speed signals by Discrete Fourier Transform then become new inputs and will yield a new frequency deviation signal with less fluctuation and does not exceed the limit. On the other hand, correlation analysis provides the variable renewable energy plants with the most intermittent than others and yield fluctuating frequency deviation violating the limit at the end of the day. The battery energy storage system will compensate for the power fluctuation because of the intermittent power plants to achieve frequency stability.