{'fraction_non_alphanumeric': 0.010126582278481013, 'fraction_numerical': 0.0, 'mean_word_length': 5.1796875, '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}}
Detection of voltage sag by artificial neural network and mitigation using DSTATCOM

An important task in power system operation is to decide whether the system, at a given point of time, operates safely, critically and optimally while the system operates safely. So uninterrupted supply of high quality power to customers in a secure and economic environment is the goal of power system engineers. In this paper the voltage sag is detected by artificial neural network then trained data and neural network output simulated in neural network block set, then it will be mitigated using DSTATCOM with neural network control block. Here different aspects or power line status were considered and simulated using artificial neural network to get the response under changed operating conditions.