A decision making tool for evaluating uncertainties in electric power system planning

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dc.contributor.authorOsareh, Ali Rezaen
dc.contributor.committeechairRahman, Saifuren
dc.contributor.committeememberBroadwater, Roberten
dc.contributor.committeememberDe La Ree Lopez, Jaimeen
dc.contributor.committeememberLiu, Yiluen
dc.contributor.committeememberJohnson, Lee W.en
dc.contributor.departmentElectrical Engineeringen
dc.date.accessioned2014-03-14T21:13:53Zen
dc.date.adate2008-06-06en
dc.date.available2014-03-14T21:13:53Zen
dc.date.issued1994en
dc.date.rdate2008-06-06en
dc.date.sdate2008-06-06en
dc.description.abstractPlanning of today's electric utilities demand careful consideration of issues such as environment, demand-side management, non-utility generation, and new technologies which are subject to different constraints and uncertainties. Utilities have long developed and used models for their short and long-term planning, most of which are single purpose, large, data intensive, and do not fully account for uncertainties. New techniques have emerged to deal with uncertainties in utility planning. Among them, the Analytic Hierarchy Process (AHP) has been more successful in assessing uncertainties, and found to be well structured and applicable to individual as well as group decision makers. However, the results of this method are merely point estimate values. It is the objective of this research to identify a methodology which is capable of evaluating uncertainties with relative ease and accuracy without the need for a large volume of data and complicated software packages. The Analytic Hierarchy Process has been extended to estimate the variance of the error in judgments and therefore the confidence interval of values instead of point estimate values. A simulation study was carried out to check the accuracy of error variance (QI) in confidence interval calculations. The results showed that QI has a linear relationships with the variance of weights. The extended AHP method is applied to three case studies, including 1) Third party generation bidding evaluation criteria, 2) Identification and evaluation of different load management programs on utility peak reduction, and 3) Oil price prediction for electric utilities. This method promises to be an effective decision making tool for evaluating uncertainties in electric power system planning.en
dc.description.degreePh. D.en
dc.format.extentxiii, 226 leavesen
dc.format.mediumBTDen
dc.format.mimetypeapplication/pdfen
dc.identifier.otheretd-06062008-164950en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-06062008-164950/en
dc.identifier.urihttp://hdl.handle.net/10919/38313en
dc.language.isoenen
dc.publisherVirginia Techen
dc.relation.haspartLD5655.V856_1994.O837.pdfen
dc.relation.isformatofOCLC# 32777987en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subject.lccLD5655.V856 1994.O837en
dc.subject.lcshElectric power systems -- Decision makingen
dc.subject.lcshElectric power systems -- Planningen
dc.titleA decision making tool for evaluating uncertainties in electric power system planningen
dc.typeDissertationen
dc.type.dcmitypeTexten
thesis.degree.disciplineElectrical Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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