{'fraction_non_alphanumeric': 0.018341892883345562, 'fraction_numerical': 0.018341892883345562, 'mean_word_length': 5.373831775700935, '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}}
Extension of IEC61850 with smart EV charging

Un-coordinated Electric Vehicle (EV) charging behaviors will impact the power grid and degrade power quality. Smart charging system can optimally allocate the energy among EVs and minimize the impact on grid. IEC 61850 is an international standard for distribution & substation automation and intelligence device communication in smart grid. This paper introduces the extension of IEC 61850 with smart EV scheduling algorithms, considering current multiplexing, power sharing strategies and user behaviors. We have developed an IEC 61850 abstract data model for the information exchanged among components of smart EV charging infrastructures, including the EV charging control center, intelligent Electric Vehicle Supply Equipment (EVSE) and the EV users with mobile applications. Real-world EV usage data on UCLA campus is utilized in the simulation experiment, which is based on the predictive control paradigm. The data model is instantiated by a web service on EV control center by converting the raw data streams from EVSEs in various formats, such as JSON or raw string, etc. into a standardized IEC 61850 SCL file, which contains the critical meter data and charging session parameters. The system cost performance, the interoperability and scalability of smart EV charging infrastructure are greatly improved.