{'fraction_non_alphanumeric': 0.01611459265890779, 'fraction_numerical': 0.0017905102954341987, 'mean_word_length': 5.817073170731708, '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}}
Visualization of time-sequential simulation for large power distribution systems

Many graphical alternatives are useful to demonstrate critical characteristics of distribution systems such as voltage regulation or power flow. The visualization of electrical variables can also be an effective approach to analyze, compare and evaluate large-scale systems. However, visual analysis of large power distribution systems is increasing in complexity for operational and research purposes. In this paper, we show a proposed approach to take advantage of the statistical inference to visualize complex behaviors in time-sequential simulations. This method provides a meaningful representation to millions of simulation results that can be used for analysis and validation of smart grid strategies and devices. The visual examples show a fast identification of electrical phenomena obtained from the OpenDSS simulation of the EPRI Ckt24 test circuit. This approach can be applied to the volt-var control, topological reconfiguration, distributed generation management, storage control, and operation assessment among others.