Abstract
Wide-area measurement systems in the smart grid are how to reply securely and consistently to several disturbances in the smart grid applications. The enthusiasm for that type of application arises from the fact that with the support of communication, synchronized measurements from various remote substations in a grid network can greatly enhance the accuracy and timeliness of detecting the source of uncertainties. Therefore, proper signal processing using the right window function can mitigate such uncertainties. Hence, this paper provides an overview of window functions and then presents and compares the window functions to scrutinize the best window function in designing the right FIR filter, so that measurement and fault detection as well as protection can be ensured by the WAMS in smart grid Internet of Things systems. FIR filter is the ideal filter when using windows methods, which is designed to have an exact linear phase and is great in shaping their magnitude response. Three types of windows are discussed in the window function’s project, that is, Hanning window (HNNW), HMMW, and Blackman window (BW). Matlab simulation used to generate the frequency and time domain for the magnitude of three windows with N is set to 4, 8, 16, 32, 64, and 1028. The Hanning, Hamming, and Blackman windows used the same source code but have different general numerical equations. For the HNNW, the peak of the bell-shaped waveform in the time domain getting closer to 1 and the number of lobes per cycle increase as the number of samples, N, increase. Hamming window shows a similar characteristic wave as HNNW, but the starting and ending points do not touch the 0 or are known as the origin. For BW’s general numerical equation, an extra cosine is included which helps to reduce the side lobe. The time-domain graph of the Blackman signal touches the 0-axis, HNNW signal slightly touches the 0-axis, and Hamming signal does not touch the 0-axis at all. Hamming has a discontinuity in the signal and thus better in canceling the nearest side lobe. The frequency-domain graph of Blackman window has the widest main lobe width, has the lowest side lobe with approximately -60dB, lesser side lobe, and the largest side lobe roll-off rate compared to Hamming and Hanning. HNNW is useful for analyzing transients longer than the time duration of the window and for general-purpose applications. HNNW is suitable to be used in most engineering cases due to good frequency resolution and reduced spectral leakage, which is satisfactory in 95% of cases. Blackman window is applicable for single-tone measurement because it has a low maximum side lobe level and a high side lobe roll-off rate.
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Hasan, M.K., Ahmed, M.M., Islam, S., Memon, I., Shaikh, R.A., Shaikh, H. (2022). Window Functions for Phasor Signal Processing of Wide-Area Measurement in Smart Grid Internet of Things Communications. In: Rani, S., Sai, V., Maheswar, R. (eds) IoT and WSN based Smart Cities: A Machine Learning Perspective. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-84182-9_4
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