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dc.contributor.advisorNewman, Alexandra M.
dc.contributor.authorScioletti, Michael S.
dc.date.accessioned2016-05-19T21:46:50Z
dc.date.accessioned2022-02-03T12:58:05Z
dc.date.available2016-05-19T21:46:50Z
dc.date.available2022-02-03T12:58:05Z
dc.date.issued2016
dc.identifierT 8020
dc.identifier.urihttps://hdl.handle.net/11124/170107
dc.descriptionIncludes bibliographical references.
dc.description2016 Spring.
dc.description.abstractRenewable energy technologies, specifically, solar photovoltaic cells, combined with battery storage and diesel generators, form a hybrid system capable of independently powering remote locations, i.e., those isolated from the grid. If sized correctly, hybrid systems reduce fuel consumption compared to generator-only alternatives. We present an optimization model to solve the hybrid power system design and dispatch problem for remote locations, modeling the acquisition of different power technologies as integer variables and their operation using nonlinear expressions. Our cost-minimizing, nonconvex, nonlinear, mixed-integer program contains a detailed set of battery-only constraints that (i) considers rate-capacity effects in assigning discharge current; (ii) calculates both voltage and lifetime as a function of state-of-charge and current; and (iii) adjusts rate-capacity and resistance parameters to temperature. We demonstrate that neglecting these characteristics, which is common to facilitate tractability of the problem, could lead to over-estimation of battery performance by as much as 30%. Due to the complexities of this model, we present symmetry reduction and linearizations, the latter of which includes exact and convex under-estimation techniques. Specifically, we demonstrate how to employ the convex envelope of a bilinear term as a relaxation to bound and solve the problem, and also how to tighten this relaxation by partitioning on one or both of these variables in the bilinear term. Although partitioning is computationally expensive, we demonstrate that by providing the solver with an initial feasible solution as a "warm-start," we are able to solve model instances in a reasonable amount of time. We determine, in a matter of hours, solutions within 5% of global optimality that closely resemble those from the nonlinear model. Our instances contain real data spanning a yearly horizon at hour fidelity and demonstrate that a hybrid system could reduce fuel consumption by as much as 50% compared to a generator-only solution.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado School of Mines. Arthur Lakes Library
dc.relation.ispartof2010-2019 - Mines Theses & Dissertations
dc.rightsCopyright of the original work is retained by the author.
dc.subjectbattery
dc.subjectenergy
dc.subjecthybrid system
dc.subjectinteger programming
dc.subjectnonlinear programming
dc.subjectoptimization
dc.titleMixed-integer program for the design and dispatch of a hybrid power generation system, A
dc.typeText
dc.contributor.committeememberCoffey, Mark
dc.contributor.committeememberHering, Amanda S.
dc.contributor.committeememberTurner, Cameron J.
thesis.degree.nameDoctor of Philosophy (Ph.D.)
thesis.degree.levelDoctoral
thesis.degree.disciplineMechanical Engineering
thesis.degree.grantorColorado School of Mines


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