{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/102828"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/102828","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"A hierarchy of microgrid models with some applications","abstract":"This dissertation proposes a hierarchy of microgrid models that can be utilized for power system analysis and control design purposes. The microgrid models are classified according to time resolution and, consequently, according to complexity and computational cost as well. Our approach involves three key stages: (1) the formulation of high-order models, using existing circuit and control laws in the literature, followed by (2) a systematic reduction of the high-order models to reduced-order models using singular perturbation analysis and, finally (3) a hierarchical classification of the high-order and reduced-order models according to the time-scales we propose they should be utilized for. The resulting hierarchy of microgrid models is comprised of a microgrid high-order model (µHOm), the microgrid reduced-order model 1 (µROm1), the microgrid reduced-order model 2 (µROm2), and the microgrid reduced-order model 3 (µROm3), the last three of which are developed in this work. Each microgrid model we develop is composed of models for three-phase inverters, microturbines, type-C wind turbine generators, distribution line networks, and generic elements (e.g. loads) connected to the network. We identify the time resolution of the models and analyze the performance of these models using various power system test cases. We also showcase two applications of our reduced-order models: first in the design of a robust synchronization method for electric power generators, and secondly in the development of a hardware-in-the-loop laboratory for analysis and testing of microgrid controls.","abstract_html":"This dissertation proposes a hierarchy of microgrid models that can be utilized for power system analysis and control design purposes. The microgrid models are classified according to time resolution and, consequently, according to complexity and computational cost as well. Our approach involves three key stages: (1) the formulation of high-order models, using existing circuit and control laws in the literature, followed by (2) a systematic reduction of the high-order models to reduced-order models using singular perturbation analysis and, finally (3) a hierarchical classification of the high-order and reduced-order models according to the time-scales we propose they should be utilized for. The resulting hierarchy of microgrid models is comprised of a microgrid high-order model (µHOm), the microgrid reduced-order model 1 (µROm1), the microgrid reduced-order model 2 (µROm2), and the microgrid reduced-order model 3 (µROm3), the last three of which are developed in this work. Each microgrid model we develop is composed of models for three-phase inverters, microturbines, type-C wind turbine generators, distribution line networks, and generic elements (e.g. loads) connected to the network. We identify the time resolution of the models and analyze the performance of these models using various power system test cases. We also showcase two applications of our reduced-order models: first in the design of a robust synchronization method for electric power generators, and secondly in the development of a hardware-in-the-loop laboratory for analysis and testing of microgrid controls.","abstract_has_math":false,"creators":["Ajala, Olaolu"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Domínguez-García, Alejandro D.","Sauer, Peter W.","Liberzon, Daniel M.","Bose, Subhonmesh"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-02-07T20:44:08Z","date_published":"2019-02-07T20:44:08Z","updated_at":"2026-07-22T22:24:42Z","subjects":["Microgrids, Distributed Energy Resources, High-Order Modeling, Reduced-Order Modeling, Singular Perturbation Analysis"],"languages":["en"],"rights":["Copyright 2018 Olaoluwapo Ajala"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/102828","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Domínguez-García, Alejandro D.","Sauer, Peter W.","Liberzon, Daniel M.","Bose, Subhonmesh"]},{"key":"dc:creator","label":"Author","values":["Ajala, Olaolu"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2019-02-07T20:44:08Z","2021-02-08T10:15:11Z","2018-12-04","2018-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Microgrids, Distributed Energy Resources, High-Order Modeling, Reduced-Order Modeling, Singular Perturbation Analysis"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2018 Olaoluwapo Ajala"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/102828"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This dissertation proposes a hierarchy of microgrid models that can be utilized for power system analysis and control design purposes. The microgrid models are classified according to time resolution and, consequently, according to complexity and computational cost as well. Our approach involves three key stages: (1) the formulation of high-order models, using existing circuit and control laws in the literature, followed by (2) a systematic reduction of the high-order models to reduced-order models using singular perturbation analysis and, finally (3) a hierarchical classification of the high-order and reduced-order models according to the time-scales we propose they should be utilized for. The resulting hierarchy of microgrid models is comprised of a microgrid high-order model (µHOm), the microgrid reduced-order model 1 (µROm1), the microgrid reduced-order model 2 (µROm2), and the microgrid reduced-order model 3 (µROm3), the last three of which are developed in this work. Each microgrid model we develop is composed of models for three-phase inverters, microturbines, type-C wind turbine generators, distribution line networks, and generic elements (e.g. loads) connected to the network. We identify the time resolution of the models and analyze the performance of these models using various power system test cases. We also showcase two applications of our reduced-order models: first in the design of a robust synchronization method for electric power generators, and secondly in the development of a hardware-in-the-loop laboratory for analysis and testing of microgrid controls.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2020-12-01","The student, Olaolu Ajala, accepted the attached license on 2018-12-03 at 16:35.","The student, Olaolu Ajala, submitted this Dissertation for approval on 2018-12-03 at 17:39.","This Dissertation was approved for publication on 2018-12-04 at 10:06.","DSpace SAF Submission Ingestion Package generated from Vireo submission #13182 on 2019-02-07 at 14:18:51","Made available in DSpace on 2019-02-07T20:44:08Z (GMT). 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The microgrid models are classified according to time resolution and, consequently, according to complexity and computational cost as well. Our approach involves three key stages: (1) the formulation of high-order models, using existing circuit and control laws in the literature, followed by (2) a systematic reduction of the high-order models to reduced-order models using singular perturbation analysis and, finally (3) a hierarchical classification of the high-order and reduced-order models according to the time-scales we propose they should be utilized for. The resulting hierarchy of microgrid models is comprised of a microgrid high-order model (µHOm), the microgrid reduced-order model 1 (µROm1), the microgrid reduced-order model 2 (µROm2), and the microgrid reduced-order model 3 (µROm3), the last three of which are developed in this work. Each microgrid model we develop is composed of models for three-phase inverters, microturbines, type-C wind turbine generators, distribution line networks, and generic elements (e.g. loads) connected to the network. We identify the time resolution of the models and analyze the performance of these models using various power system test cases. We also showcase two applications of our reduced-order models: first in the design of a robust synchronization method for electric power generators, and secondly in the development of a hardware-in-the-loop laboratory for analysis and testing of microgrid controls.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2020-12-01","The student, Olaolu Ajala, accepted the attached license on 2018-12-03 at 16:35.","The student, Olaolu Ajala, submitted this Dissertation for approval on 2018-12-03 at 17:39.","This Dissertation was approved for publication on 2018-12-04 at 10:06.","DSpace SAF Submission Ingestion Package generated from Vireo submission #13182 on 2019-02-07 at 14:18:51","Made available in DSpace on 2019-02-07T20:44:08Z (GMT). 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