{"id":"W6992893980","doi":"","title":"Modeling and Detection of False Data Injection Attacks for State Estimation and Automatic Generation Control in Power Systems","year":2024,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds de recherche du Québec – Nature et technologies; Hydro-Québec; Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"State (computer science); Automatic Generation Control; Control system; Estimation; Power (physics); Electric power system; Control (management)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001265196,0.0008229939,0.0008984135,0.0004784046,0.0003729277,0.001149911,0.0007984024,0.0006624584,0.001079732],"category_scores_gemma":[0.008022787,0.0005055657,0.0006041071,0.0003687021,0.0006421663,0.001376156,0.0007902002,0.00153716,0.0002273505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008085585,"about_ca_system_score_gemma":0.001035707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00779526,"about_ca_topic_score_gemma":0.004559785,"domain_scores_codex":[0.9993838,0.0001473961,0.00003485363,0.0001493167,0.0001746314,0.0001099494],"domain_scores_gemma":[0.9959868,0.002895762,0.0003278793,0.0002015516,0.0005250328,0.00006299522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001432277,0.00004331196,0.001787733,0.00004569937,0.00003418927,0.00005705512,0.00008174858,0.9640591,0.001898288,0.005396829,0.0004488743,0.02600399],"study_design_scores_gemma":[7.868727e-7,0.000006269152,0.00008909738,0.000001131398,0.0000027778,0.000003514627,0.000001572948,0.9992187,0.0002657791,0.0003912386,0.00001764467,0.000001348155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07285166,0.0002993798,0.9245231,0.0002980721,0.00005599488,0.00002657126,0.00005005324,0.0004259665,0.001469293],"genre_scores_gemma":[0.9849414,0.0001611223,0.01341647,0.00003459725,0.00002085784,0.00002573041,0.0000542165,0.00003503172,0.001310599],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00779526,"threshold_uncertainty_score":0.01549983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01744117380587817,"score_gpt":0.2458566025417932,"score_spread":0.2284154287359151,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}