Security Measures for Assessing Vulnerability to Large      Deviations and Voltage Collapse in Electric Power Systems
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
{'SignBlockName': 'Kristen M. Biggar, N-BioS', 'PO_EMAI': None, 'PO_PHON': None}
In many large engineering systems it is important to maintain the               system state at an acceptable operating point in the face of random             disturbances.  For power system analyses, evaluation of the effect of           small random load variations has relied on examining the behavior of            the linearized system about the operating point of interest.  However,          results on large deviation phenomena in stochastic differential                 equations indicate that under certain conditions, such linearized               analysis may not be adequate.  While the linearized system (without the         random disturbance) may be asymptotically stable, the presence of the           disturbance causes the state to behave as a diffusion process,                  "wandering" about the equilibrium.  If the region of attraction for the         stable equilibrium in the nonlinear system has a portion of its                 boundary sufficiently close to the equilibrium, the state may                   eventually leave the attracting set.  The deterministic dynamics then           dominate, pushing the state away from the desired operating point,              resulting in a "large deviation."  This research will apply recent              theoretical results on large deviations in randomly perturbed dynamical         systems to the power system security assessment problem.  A primary             goal will be to develop a measure which indicates vulnerability to              voltage collapse, an observed large deviation effect for which standard         small disturbance stability analyses are inadequate.
{'FirstName': 'Christopher', 'LastName': 'DeMarco', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Christopher L DeMarco', 'EmailAddress': 'demarco@engr.wisc.edu', 'NSF_ID': '000116217', 'StartDate': '09/01/1986', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Wisconsin-Madison', 'CityName': 'MADISON', 'ZipCode': '537151218', 'PhoneNumber': '6082623822', 'StreetAddress': '21 North Park Street', 'StreetAddress2': 'Suite 6301', 'CountryName': 'United States', 'StateName': 'Wisconsin', 'StateCode': 'WI', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'WI02', 'ORG_DUNS_NUM': '161202122', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WISCONSIN SYSTEM', 'ORG_PRNT_DUNS_NUM': '041188822'}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
{'Code': '1454', 'Text': 'SYSTEMS THEORY'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1986&All=true', 'xml': '8611728.xml'}