{'fraction_non_alphanumeric': 0.015636105188343994, 'fraction_numerical': 0.0, 'mean_word_length': 5.579439252336448, '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}}
Economic impact of data integrity attacks on distributed DC optimal power flow algorithm

A variety of distributed energy management algorithms are being developed for DC optimal power flow (DCOPF) application owing to their flexibility and scalability in the presence of high distributed Energy Resources (DERs) penetration. However, these algorithms are vulnerable to malicious cyber attacks due to the absence of control centers. In this paper, we study and analyze the economic impact of the data integrity attack to distributed DC-OPF algorithms. In particular, we demonstrate how a malicious generator could gain more economic profit by compromising the distributed controller of its bus, modifying the information sent to neighboring buses and manipulating the power dispatch commands. To our best knowledge, this is the first paper to show the economic impact of malicious attacks in distributed DC-OPF. By revealing such potential financial risks, this paper conveys the message that besides the efforts of designing novel distributed energy management algorithms to address the DERs integration challenges, it is equally important to protect the distributed energy management algorithms from possible malicious attacks to avoid potential economic loss. The economic impact of the data integrity attack is illustrated in the Future Renewable Electric Energy Delivery and Management (FREEDM) system.