{'fraction_non_alphanumeric': 0.02308265078183172, 'fraction_numerical': 0.0029784065524944155, 'mean_word_length': 5.556097560975609, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A useful identification method to build low‐order transfer function models based on frequency response for small‐signal stability analysis

This paper presents a scheme of small‐signal stability analysis for very large radial power systems. Generally, a radial power system can be easily classified as one main system and some external systems. Therefore, if accurate low‐order model of the external systems could be identified, the analysis effort for small‐signal stability can be reduced. Some dynamic reduction methods are proposed. Especially, the frequency‐domain least‐squares approximation methods, which are powerful and have high numerical reliability. This paper proposes a modal rebuild logic to improve the result obtained by the frequency‐domain least‐squares approximation methods. The proposed method provides high accuracy and a practical low‐order transfer function model. This paper introduces the usefulness of the proposed method with some numerical examples. In addition, merging sophisticated data handling and advanced applications in order to reduce human efforts is also discussed. This paper mentions the importance of automated node ID handling in order to realize the classification of system data into some partial data sets. © 2006 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.