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dc.contributor.advisorCedeño-Maldonado, José R.
dc.contributor.authorCuello-Reyna, Alfredo A.
dc.date.accessioned2019-05-15T17:59:35Z
dc.date.available2019-05-15T17:59:35Z
dc.date.issued2006
dc.identifier.urihttps://hdl.handle.net/20.500.11801/2380
dc.description.abstractThis research work presents the application of the Differential Evolution Optimization Algorithm for solving various complex power systems problems: Reactive Power Planning, Congestion Management in Restructured Power Systems, State Estimation with Phasor Measurement Units and with Equality and Inequality Constraints, and Intelligent Power Routers Based Controlled Islanding Scheme. Due to their non-continuous, non-differentiable and highly nonlinear nature; these problems are difficult or impossible to solve using the main classical optimization techniques. In order to show the flexibility and applicability of the Differential Evolution algorithm for solving these complex problems, the proposed solution methodologies were tested and validated through standard test systems with satisfactory results. The solutions obtained were compared with those obtained by means of other traditional and evolutionary optimization techniques available in the literature reviewed. Finally, we provide specific recommendations regarding to the correct adjustment of the Differential Evolution control parameters, which may lead to very successful results in complex and large scale optimization problems, in a reasonable computational time.en_US
dc.description.abstractEste trabajo de investigación presenta la aplicación del Algoritmo de Optimización Evolución Diferencial (“Differential Evolution”) para resolver varios problemas complejos de sistemas de potencia: Planeación Optima de la Potencia Reactiva, Manejo de la Congestión en Sistemas de Potencia Desregulados, Estimación de Estados utilizando Medición de Fasores Sincronizados y con Restricciones de Igualdad y Desigualdad, y el Desarrollo de Esquemas de Islas Controladas basados en los Enrutadores Inteligentes de Potencia (“Intelligent Power Routers”). Debido a su naturaleza no-continua, no-diferenciable y altamente no lineal; estos problemas son difíciles o imposible de resolver usando las técnicas de optimización convencionales. Con el objetivo de mostrar la aplicabilidad y flexibilidad del algoritmo de Evolución Diferencial para resolver estos problemas complejos, los esquemas de solución propuestos fueron probados y validados a través de sistemas de prueba estándar con muy buenos resultados. Las soluciones obtenidas se compararon con aquellas obtenidas mediante otras técnicas de optimización tradicionales y evolutivas. Finalmente, proveemos recomendaciones específicas sobre el ajuste correcto de los parámetros de control del algoritmo de Evolución Diferencial, los cuales podrían influir en la obtención de resultados satisfactorios en problemas de optimización complejos y de gran escala, en un tiempo computacional razonable.en_US
dc.description.sponsorshipSupported in part by the National Science Foundation (NSF) thru award number 0224743 as well as by the University of Puerto Rico-Mayagüez.en_US
dc.language.isoEnglishen_US
dc.titleApplications of the differential evolution optimization algorithm in power systems planning, operation and controlen_US
dc.typeThesisen_US
dc.rights.licenseAll rights reserveden_US
dc.rights.holder(c) 2006 Alfredo Antonio Cuello-Reynaen_US
dc.contributor.committeeO’Neill-Carrillo, Efraín
dc.contributor.committeeIrrizary-Rivera, Agustín
dc.contributor.representativeVásquez-Urbano, Pedro
thesis.degree.levelM.S.en_US
thesis.degree.disciplineElectrical Engineeringen_US
dc.contributor.collegeCollege of Engineeringen_US
dc.contributor.departmentDepartment of Electrical and Computer Engineeringen_US
dc.description.graduationYear2006en_US


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