Chance Constrained Voltage Regulation via Affine Inverter Control Policies

dc.contributor.advisorGatsis, Nikolaos
dc.contributor.authorAyyagari, Krishna Sandeep
dc.contributor.committeeMemberTaha, Ahmad
dc.contributor.committeeMemberDong, Bing
dc.creator.orcidhttps://orcid.org/0000-0002-9908-5694
dc.date.accessioned2024-01-25T22:33:22Z
dc.date.available2024-01-25T22:33:22Z
dc.date.issued2018
dc.descriptionThis item is available only to currently enrolled UTSA students, faculty or staff. To download, navigate to Log In in the top right-hand corner of this screen, then select Log in with my UTSA ID.
dc.description.abstractVoltage control plays an important role in the operation of electricity distribution networks. Especially with increasing penetration of solar power generation in distribution networks, rapid and substantial changes in voltage magnitude can occur. However, with the revised IEEE 1547 standard, smart inverters can participate in voltage regulation by injecting or absorbing reactive power and can facilitate other network-wide objectives, such as minimization of thermal losses. To cope with the stochastic nature of the solar power generation and random fluctuations of user real and reactive power consumption, this thesis introduces a stochastic optimal power flow where the control actions are expressed as affine functions of uncertain quantities. Voltage security constraints are also introduced in a stochastic optimization framework as probabilistic constraints. Assuming the uncertainties follow a Gaussian distribution, the resulting optimization problem is shown to be a second-order cone program. We illustrate the results using real data taken from Pecan Street and tested on standard distribution test feeders which include the IEEE-13 feeder, the SCE -47 feeder, a modified SCE-47 feeder with overvoltage and the UKGDS-95 feeder.
dc.description.departmentElectrical and Computer Engineering
dc.format.extent53 pages
dc.format.mimetypeapplication/pdf
dc.identifier.isbn9780438300354
dc.identifier.urihttps://hdl.handle.net/20.500.12588/2420
dc.languageen
dc.subjectAffine policy
dc.subjectChance constraints
dc.subjectDistributed energy resources
dc.subjectDistribution systems
dc.subjectOptimal power flow
dc.subjectVoltage regulation
dc.subject.classificationElectrical engineering
dc.titleChance Constrained Voltage Regulation via Affine Inverter Control Policies
dc.typeThesis
dc.type.dcmiText
dcterms.accessRightspq_closed
thesis.degree.departmentElectrical and Computer Engineering
thesis.degree.grantorUniversity of Texas at San Antonio
thesis.degree.levelMasters
thesis.degree.nameMaster of Science

Files

Original bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Ayyagari_utsa_1283M_12632.pdf
Size:
928.32 KB
Format:
Adobe Portable Document Format