{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/72768"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/72768","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"A power sharing based approach for optimizing photovoltaic generation in autonomous microgrids","abstract":"In an effort to reduce the electric industry's dependence on fossil fuels, renewable energy resources are being deployed in the power grid. However, the intermittent nature of some popular renewable resources presents the problem of optimizing their use. This work presents a control strategy for the optimization of available photovoltaic generation in an autonomous microgrid. The deepening penetration of rooftop solar panels motivates our case study of a microgrid with photovoltaic (PV) generators and microturbines. Building upon centralized generation concepts such as droop control, automatic generation control and area control error, the strategy ensures effective provision of power raise/lower actions to the system based on some locally measured variables, with the ability to turn-off the microturbine in the event of adequate PV generation for such actions. A 5-bus test system with three PV generators and one microturbine is considered, and preliminary simulation results are presented to demonstrate the effectiveness of this approach","abstract_html":"In an effort to reduce the electric industry&#x27;s dependence on fossil fuels, renewable energy resources are being deployed in the power grid. However, the intermittent nature of some popular renewable resources presents the problem of optimizing their use. This work presents a control strategy for the optimization of available photovoltaic generation in an autonomous microgrid. The deepening penetration of rooftop solar panels motivates our case study of a microgrid with photovoltaic (PV) generators and microturbines. Building upon centralized generation concepts such as droop control, automatic generation control and area control error, the strategy ensures effective provision of power raise/lower actions to the system based on some locally measured variables, with the ability to turn-off the microturbine in the event of adequate PV generation for such actions. A 5-bus test system with three PV generators and one microturbine is considered, and preliminary simulation results are presented to demonstrate the effectiveness of this approach","abstract_has_math":false,"creators":["Ajala, Olaoluwapo"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Sauer, Peter W."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-01-21T19:47:57Z","date_published":"2015-01-21T19:47:57Z","updated_at":"2026-07-22T22:26:07Z","subjects":["Autonomous microgrids","photovoltaic generation","microturbine","droop control","area control error"],"languages":["en"],"rights":["Copyright 2014 Olaoluwapo Ajala"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/72768","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Sauer, Peter W."]},{"key":"dc:creator","label":"Author","values":["Ajala, Olaoluwapo"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-01-21T19:47:57Z","2014-12","2015-01-21"]},{"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":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"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":["Autonomous microgrids","photovoltaic generation","microturbine","droop control","area control error"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2014 Olaoluwapo Ajala"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/72768"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["In an effort to reduce the electric industry's dependence on fossil fuels, renewable energy resources are being deployed in the power grid. However, the intermittent nature of some popular renewable resources presents the problem of optimizing their use. This work presents a control strategy for the optimization of available photovoltaic generation in an autonomous microgrid. The deepening penetration of rooftop solar panels motivates our case study of a microgrid with photovoltaic (PV) generators and microturbines. Building upon centralized generation concepts such as droop control, automatic generation control and area control error, the strategy ensures effective provision of power raise/lower actions to the system based on some locally measured variables, with the ability to turn-off the microturbine in the event of adequate PV generation for such actions. A 5-bus test system with three PV generators and one microturbine is considered, and preliminary simulation results are presented to demonstrate the effectiveness of this approach","Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2014-12-03T14:36:18Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 20 Ajala_Olaoluwapo.tex: 5181 bytes, checksum: 0feed6a0957c4b633eb4fac046645875 (MD5) TransitionMatrices.m: 624 bytes, checksum: 6ae7476b2ea7c56dad894b8e36787a64 (MD5) SynchGenInitial_withAGC2.m: 1149 bytes, checksum: 48bc1ac4d507a3ae9103711fa8df15af (MD5) PVsystem2_withAGC_5bus_inertia.m: 8091 bytes, checksum: ec2e0aba19216156fc7d31e6a4c5d999 (MD5) PVsystem_INITIAL_5bus.m: 806 bytes, checksum: 0c58ee1f5e567fe8c1e4fec41dc0b7ca (MD5) PV_DC_output_inertia.m: 1318 bytes, checksum: eecc380ee03c349cef6758775c3e097e (MD5) NetworkLoadFlow_5bus.m: 1561 bytes, checksum: c497aa3f7c78bcebf30368568ba42694 (MD5) Network_Equation_SG_ONorOFF_5bus.m: 1980 bytes, checksum: 701097af70f92c0a839bc7d1b7b8859a (MD5) MPP_BattMPP_Qrated_Pload_inertia.m: 3672 bytes, checksum: 32529c2d1a7aac7925b3d8dd055be4b3 (MD5) Microgrid_withAGC_5bus_inertia.m: 12951 bytes, checksum: 1f6cf53d7d24d8a29f8b817ccbe4c32e (MD5) loadfunction.m: 1963 bytes, checksum: 19be247f06f17f444185533d80ba725d (MD5) Initialize_withAGC_5bus_inertia.m: 2455 bytes, checksum: 3df13acfa26f107b53fc229bd133d4da (MD5) Initial_Power_and_Frequency_AGC_5bus_inertia.m: 228 bytes, checksum: 33393b80cbc54a505c729391668bffeb (MD5) CloudCoverTransitionProbabilities.m: 9090 bytes, checksum: eb455f9930557fe930fc7e75f6f1a01a (MD5) CloudCover.m: 2243 bytes, checksum: 10197dc82055df8e9d787ab43c0fed7c (MD5) AlgebraicEquationsNOSG_5bus.m: 2399 bytes, checksum: dc06f534480e504735ada1086f6bf014 (MD5) AlgebraicEquations_5bus.m: 2557 bytes, checksum: 1e5293e60721d456659112c8b8c19fa9 (MD5) AGC_Network_Equation_SG_ONorOFF_5bus_inertia.m: 4125 bytes, checksum: 25359e22a0b307a1f370c51f9833f81d (MD5) AGC_5bus_inertia.m: 5084 bytes, checksum: b85b1b3199742a9ef9eafd743b6a99f8 (MD5) Ajala_Olaoluwapo.pdf: 3766903 bytes, checksum: 9ad96cd3d6849a1018c7047f398cff2d (MD5)","Made available in DSpace on 2015-01-21T19:47:57Z (GMT). No. of bitstreams: 20 Olaoluwapo_Ajala.pdf: 3766903 bytes, checksum: 9ad96cd3d6849a1018c7047f398cff2d (MD5) TransitionMatrices.m: 624 bytes, checksum: 6ae7476b2ea7c56dad894b8e36787a64 (MD5) SynchGenInitial_withAGC2.m: 1149 bytes, checksum: 48bc1ac4d507a3ae9103711fa8df15af (MD5) PVsystem2_withAGC_5bus_inertia.m: 8091 bytes, checksum: ec2e0aba19216156fc7d31e6a4c5d999 (MD5) PVsystem_INITIAL_5bus.m: 806 bytes, checksum: 0c58ee1f5e567fe8c1e4fec41dc0b7ca (MD5) PV_DC_output_inertia.m: 1318 bytes, checksum: eecc380ee03c349cef6758775c3e097e (MD5) NetworkLoadFlow_5bus.m: 1561 bytes, checksum: c497aa3f7c78bcebf30368568ba42694 (MD5) Network_Equation_SG_ONorOFF_5bus.m: 1980 bytes, checksum: 701097af70f92c0a839bc7d1b7b8859a (MD5) MPP_BattMPP_Qrated_Pload_inertia.m: 3672 bytes, checksum: 32529c2d1a7aac7925b3d8dd055be4b3 (MD5) Microgrid_withAGC_5bus_inertia.m: 12951 bytes, checksum: 1f6cf53d7d24d8a29f8b817ccbe4c32e (MD5) loadfunction.m: 1963 bytes, checksum: 19be247f06f17f444185533d80ba725d (MD5) Initialize_withAGC_5bus_inertia.m: 2455 bytes, checksum: 3df13acfa26f107b53fc229bd133d4da (MD5) Initial_Power_and_Frequency_AGC_5bus_inertia.m: 228 bytes, checksum: 33393b80cbc54a505c729391668bffeb (MD5) CloudCoverTransitionProbabilities.m: 9090 bytes, checksum: eb455f9930557fe930fc7e75f6f1a01a (MD5) CloudCover.m: 2243 bytes, checksum: 10197dc82055df8e9d787ab43c0fed7c (MD5) AlgebraicEquationsNOSG_5bus.m: 2399 bytes, checksum: dc06f534480e504735ada1086f6bf014 (MD5) AlgebraicEquations_5bus.m: 2557 bytes, checksum: 1e5293e60721d456659112c8b8c19fa9 (MD5) AGC_Network_Equation_SG_ONorOFF_5bus_inertia.m: 4125 bytes, checksum: 25359e22a0b307a1f370c51f9833f81d (MD5) AGC_5bus_inertia.m: 5084 bytes, checksum: b85b1b3199742a9ef9eafd743b6a99f8 (MD5) Ajala_Olaoluwapo.tex: 5181 bytes, checksum: 0feed6a0957c4b633eb4fac046645875 (MD5)"]},{"key":"dc:title","label":"Title","values":["A power sharing based approach for optimizing photovoltaic generation in autonomous microgrids"]}]}],"canonical_facts":{"dc:contributor":["Sauer, Peter W."],"dc:creator":["Ajala, Olaoluwapo"],"dc:date":["2015-01-21T19:47:57Z","2014-12","2015-01-21"],"dc:description":["In an effort to reduce the electric industry's dependence on fossil fuels, renewable energy resources are being deployed in the power grid. However, the intermittent nature of some popular renewable resources presents the problem of optimizing their use. This work presents a control strategy for the optimization of available photovoltaic generation in an autonomous microgrid. The deepening penetration of rooftop solar panels motivates our case study of a microgrid with photovoltaic (PV) generators and microturbines. Building upon centralized generation concepts such as droop control, automatic generation control and area control error, the strategy ensures effective provision of power raise/lower actions to the system based on some locally measured variables, with the ability to turn-off the microturbine in the event of adequate PV generation for such actions. A 5-bus test system with three PV generators and one microturbine is considered, and preliminary simulation results are presented to demonstrate the effectiveness of this approach","Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2014-12-03T14:36:18Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 20 Ajala_Olaoluwapo.tex: 5181 bytes, checksum: 0feed6a0957c4b633eb4fac046645875 (MD5) TransitionMatrices.m: 624 bytes, checksum: 6ae7476b2ea7c56dad894b8e36787a64 (MD5) SynchGenInitial_withAGC2.m: 1149 bytes, checksum: 48bc1ac4d507a3ae9103711fa8df15af (MD5) PVsystem2_withAGC_5bus_inertia.m: 8091 bytes, checksum: ec2e0aba19216156fc7d31e6a4c5d999 (MD5) PVsystem_INITIAL_5bus.m: 806 bytes, checksum: 0c58ee1f5e567fe8c1e4fec41dc0b7ca (MD5) PV_DC_output_inertia.m: 1318 bytes, checksum: eecc380ee03c349cef6758775c3e097e (MD5) NetworkLoadFlow_5bus.m: 1561 bytes, checksum: c497aa3f7c78bcebf30368568ba42694 (MD5) Network_Equation_SG_ONorOFF_5bus.m: 1980 bytes, checksum: 701097af70f92c0a839bc7d1b7b8859a (MD5) MPP_BattMPP_Qrated_Pload_inertia.m: 3672 bytes, checksum: 32529c2d1a7aac7925b3d8dd055be4b3 (MD5) Microgrid_withAGC_5bus_inertia.m: 12951 bytes, checksum: 1f6cf53d7d24d8a29f8b817ccbe4c32e (MD5) loadfunction.m: 1963 bytes, checksum: 19be247f06f17f444185533d80ba725d (MD5) Initialize_withAGC_5bus_inertia.m: 2455 bytes, checksum: 3df13acfa26f107b53fc229bd133d4da (MD5) Initial_Power_and_Frequency_AGC_5bus_inertia.m: 228 bytes, checksum: 33393b80cbc54a505c729391668bffeb (MD5) CloudCoverTransitionProbabilities.m: 9090 bytes, checksum: eb455f9930557fe930fc7e75f6f1a01a (MD5) CloudCover.m: 2243 bytes, checksum: 10197dc82055df8e9d787ab43c0fed7c (MD5) AlgebraicEquationsNOSG_5bus.m: 2399 bytes, checksum: dc06f534480e504735ada1086f6bf014 (MD5) AlgebraicEquations_5bus.m: 2557 bytes, checksum: 1e5293e60721d456659112c8b8c19fa9 (MD5) AGC_Network_Equation_SG_ONorOFF_5bus_inertia.m: 4125 bytes, checksum: 25359e22a0b307a1f370c51f9833f81d (MD5) AGC_5bus_inertia.m: 5084 bytes, checksum: b85b1b3199742a9ef9eafd743b6a99f8 (MD5) Ajala_Olaoluwapo.pdf: 3766903 bytes, checksum: 9ad96cd3d6849a1018c7047f398cff2d (MD5)","Made available in DSpace on 2015-01-21T19:47:57Z (GMT). No. of bitstreams: 20 Olaoluwapo_Ajala.pdf: 3766903 bytes, checksum: 9ad96cd3d6849a1018c7047f398cff2d (MD5) TransitionMatrices.m: 624 bytes, checksum: 6ae7476b2ea7c56dad894b8e36787a64 (MD5) SynchGenInitial_withAGC2.m: 1149 bytes, checksum: 48bc1ac4d507a3ae9103711fa8df15af (MD5) PVsystem2_withAGC_5bus_inertia.m: 8091 bytes, checksum: ec2e0aba19216156fc7d31e6a4c5d999 (MD5) PVsystem_INITIAL_5bus.m: 806 bytes, checksum: 0c58ee1f5e567fe8c1e4fec41dc0b7ca (MD5) PV_DC_output_inertia.m: 1318 bytes, checksum: eecc380ee03c349cef6758775c3e097e (MD5) NetworkLoadFlow_5bus.m: 1561 bytes, checksum: c497aa3f7c78bcebf30368568ba42694 (MD5) Network_Equation_SG_ONorOFF_5bus.m: 1980 bytes, checksum: 701097af70f92c0a839bc7d1b7b8859a (MD5) MPP_BattMPP_Qrated_Pload_inertia.m: 3672 bytes, checksum: 32529c2d1a7aac7925b3d8dd055be4b3 (MD5) Microgrid_withAGC_5bus_inertia.m: 12951 bytes, checksum: 1f6cf53d7d24d8a29f8b817ccbe4c32e (MD5) loadfunction.m: 1963 bytes, checksum: 19be247f06f17f444185533d80ba725d (MD5) Initialize_withAGC_5bus_inertia.m: 2455 bytes, checksum: 3df13acfa26f107b53fc229bd133d4da (MD5) Initial_Power_and_Frequency_AGC_5bus_inertia.m: 228 bytes, checksum: 33393b80cbc54a505c729391668bffeb (MD5) CloudCoverTransitionProbabilities.m: 9090 bytes, checksum: eb455f9930557fe930fc7e75f6f1a01a (MD5) CloudCover.m: 2243 bytes, checksum: 10197dc82055df8e9d787ab43c0fed7c (MD5) AlgebraicEquationsNOSG_5bus.m: 2399 bytes, checksum: dc06f534480e504735ada1086f6bf014 (MD5) AlgebraicEquations_5bus.m: 2557 bytes, checksum: 1e5293e60721d456659112c8b8c19fa9 (MD5) AGC_Network_Equation_SG_ONorOFF_5bus_inertia.m: 4125 bytes, checksum: 25359e22a0b307a1f370c51f9833f81d (MD5) AGC_5bus_inertia.m: 5084 bytes, checksum: b85b1b3199742a9ef9eafd743b6a99f8 (MD5) Ajala_Olaoluwapo.tex: 5181 bytes, checksum: 0feed6a0957c4b633eb4fac046645875 (MD5)"],"dc:identifier":["http://hdl.handle.net/2142/72768"],"dc:language":["en"],"dc:rights":["Copyright 2014 Olaoluwapo Ajala"],"dc:subject":["Autonomous microgrids","photovoltaic generation","microturbine","droop control","area control error"],"dc:title":["A power sharing based approach for optimizing photovoltaic generation in autonomous microgrids"],"dc:type":["text"],"thesis:degree_discipline":["Electrical & Computer Engr"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:26:07Z"}