{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/78496"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/78496","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Differential power processing for increased solar array energy harvest","abstract":"The integration of power electronics in series-connected photovoltaics (PV) has provided a new approach to handling the well-known current mismatch problem. One such technique, known as differential power processing (DPP), has demonstrated high efficiency mismatch handling, as well as scalability, in PV applications. This thesis investigates the potential benefits of DPP in large-scale solar arrays. Mitigating mismatch is an important design parameter in the layout and orientation of solar arrays. To compare different designs, a solar simulator is developed which models annual energy production for arrays with and without DPP. Models for expected sources of loss are implemented to determine any improvement DPP offers over conventional methods. Two common and predictable sources of mismatch are self-shading and diffuse masking. Both these shading effects are influential in designing arrays. The simulation model is used to compare the impact of these two effects. Annual solar data, given in hourly measurements, is used to simulate the arrays. A test site is chosen to provide an in-depth analysis of DPP improvements. Results are then extended to sites across the United States to show the broader benefits of DPP. Analysis shows DPP improves the energy output per unit area of arrays, compared to conventional arrays. This is accomplished in two ways: array size can be reduced without sacrificing energy production, or energy production for identically sized arrays is increased. In addition to self-shading and diffuse masking, an analysis is performed on the effects of factory binning. Factory binning is assumed to be a static source of mismatch which will persist and worsen over the life of the array. Variations in panels are modeled using a bi-variate Gaussian distribution. A Monte Carlo simulation is used to quantify the impact of factory binning on an array's power output. With DPP, energy reduction due to factory binning is significantly decreased. Results indicate that arrays with DPP can handle wider ranges of binning mismatch than conventional arrays. This could ultimately decrease the installed price of installations, as both manufacturers and installers do not need to follow such stringent binning techniques.","abstract_html":"The integration of power electronics in series-connected photovoltaics (PV) has provided a new approach to handling the well-known current mismatch problem. One such technique, known as differential power processing (DPP), has demonstrated high efficiency mismatch handling, as well as scalability, in PV applications. This thesis investigates the potential benefits of DPP in large-scale solar arrays. Mitigating mismatch is an important design parameter in the layout and orientation of solar arrays. To compare different designs, a solar simulator is developed which models annual energy production for arrays with and without DPP. Models for expected sources of loss are implemented to determine any improvement DPP offers over conventional methods. Two common and predictable sources of mismatch are self-shading and diffuse masking. Both these shading effects are influential in designing arrays. The simulation model is used to compare the impact of these two effects. Annual solar data, given in hourly measurements, is used to simulate the arrays. A test site is chosen to provide an in-depth analysis of DPP improvements. Results are then extended to sites across the United States to show the broader benefits of DPP. Analysis shows DPP improves the energy output per unit area of arrays, compared to conventional arrays. This is accomplished in two ways: array size can be reduced without sacrificing energy production, or energy production for identically sized arrays is increased. In addition to self-shading and diffuse masking, an analysis is performed on the effects of factory binning. Factory binning is assumed to be a static source of mismatch which will persist and worsen over the life of the array. Variations in panels are modeled using a bi-variate Gaussian distribution. A Monte Carlo simulation is used to quantify the impact of factory binning on an array's power output. With DPP, energy reduction due to factory binning is significantly decreased. Results indicate that arrays with DPP can handle wider ranges of binning mismatch than conventional arrays. This could ultimately decrease the installed price of installations, as both manufacturers and installers do not need to follow such stringent binning techniques.","abstract_has_math":false,"creators":["Galtieri, Jason A"],"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":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-07-22T22:17:43Z","date_published":"2015-07-22T22:17:43Z","updated_at":"2026-07-22T22:26:11Z","subjects":["differential power processing","solar simulator","self-shading","modeling","irradiance","factory binning"],"languages":["en"],"rights":["Copyright 2015 Jason A. Galtieri"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/78496","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Galtieri, Jason A"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-07-22T22:17:43Z","2015-05","2015-04-28","2015-5"]},{"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":["differential power processing","solar simulator","self-shading","modeling","irradiance","factory binning"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2015 Jason A. Galtieri"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/78496"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The integration of power electronics in series-connected photovoltaics (PV) has provided a new approach to handling the well-known current mismatch problem. One such technique, known as differential power processing (DPP), has demonstrated high efficiency mismatch handling, as well as scalability, in PV applications. This thesis investigates the potential benefits of DPP in large-scale solar arrays. Mitigating mismatch is an important design parameter in the layout and orientation of solar arrays. To compare different designs, a solar simulator is developed which models annual energy production for arrays with and without DPP. Models for expected sources of loss are implemented to determine any improvement DPP offers over conventional methods. Two common and predictable sources of mismatch are self-shading and diffuse masking. Both these shading effects are influential in designing arrays. The simulation model is used to compare the impact of these two effects. Annual solar data, given in hourly measurements, is used to simulate the arrays. A test site is chosen to provide an in-depth analysis of DPP improvements. Results are then extended to sites across the United States to show the broader benefits of DPP. Analysis shows DPP improves the energy output per unit area of arrays, compared to conventional arrays. This is accomplished in two ways: array size can be reduced without sacrificing energy production, or energy production for identically sized arrays is increased. In addition to self-shading and diffuse masking, an analysis is performed on the effects of factory binning. Factory binning is assumed to be a static source of mismatch which will persist and worsen over the life of the array. Variations in panels are modeled using a bi-variate Gaussian distribution. A Monte Carlo simulation is used to quantify the impact of factory binning on an array's power output. With DPP, energy reduction due to factory binning is significantly decreased. Results indicate that arrays with DPP can handle wider ranges of binning mismatch than conventional arrays. This could ultimately decrease the installed price of installations, as both manufacturers and installers do not need to follow such stringent binning techniques.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2015-07-22 without embargo terms","The student, Jason Galtieri, accepted the attached license on 2015-04-24 at 16:41.","The student, Jason Galtieri, submitted this Thesis for approval on 2015-04-24 at 16:56.","This Thesis was approved for publication on 2015-04-28 at 12:59.","DSpace SAF Submission Ingestion Package generated from Vireo submission #8103 on 2015-07-22 at 10:34:01","Made available in DSpace on 2015-07-22T22:17:43Z (GMT). No. of bitstreams: 2 GALTIERI-THESIS-2015.pdf: 5738307 bytes, checksum: 1d15fab4a488db5b7a3d7598f07a4926 (MD5) LICENSE.txt: 4211 bytes, checksum: b3502b0b34645a529f253c2bea28e0a3 (MD5) Previous issue date: 2015-04-28"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Differential power processing for increased solar array energy harvest"]}]}],"canonical_facts":{"dc:creator":["Galtieri, Jason A"],"dc:date":["2015-07-22T22:17:43Z","2015-05","2015-04-28","2015-5"],"dc:description":["The integration of power electronics in series-connected photovoltaics (PV) has provided a new approach to handling the well-known current mismatch problem. One such technique, known as differential power processing (DPP), has demonstrated high efficiency mismatch handling, as well as scalability, in PV applications. This thesis investigates the potential benefits of DPP in large-scale solar arrays. Mitigating mismatch is an important design parameter in the layout and orientation of solar arrays. To compare different designs, a solar simulator is developed which models annual energy production for arrays with and without DPP. Models for expected sources of loss are implemented to determine any improvement DPP offers over conventional methods. Two common and predictable sources of mismatch are self-shading and diffuse masking. Both these shading effects are influential in designing arrays. The simulation model is used to compare the impact of these two effects. Annual solar data, given in hourly measurements, is used to simulate the arrays. A test site is chosen to provide an in-depth analysis of DPP improvements. Results are then extended to sites across the United States to show the broader benefits of DPP. Analysis shows DPP improves the energy output per unit area of arrays, compared to conventional arrays. This is accomplished in two ways: array size can be reduced without sacrificing energy production, or energy production for identically sized arrays is increased. In addition to self-shading and diffuse masking, an analysis is performed on the effects of factory binning. Factory binning is assumed to be a static source of mismatch which will persist and worsen over the life of the array. Variations in panels are modeled using a bi-variate Gaussian distribution. A Monte Carlo simulation is used to quantify the impact of factory binning on an array's power output. With DPP, energy reduction due to factory binning is significantly decreased. Results indicate that arrays with DPP can handle wider ranges of binning mismatch than conventional arrays. This could ultimately decrease the installed price of installations, as both manufacturers and installers do not need to follow such stringent binning techniques.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2015-07-22 without embargo terms","The student, Jason Galtieri, accepted the attached license on 2015-04-24 at 16:41.","The student, Jason Galtieri, submitted this Thesis for approval on 2015-04-24 at 16:56.","This Thesis was approved for publication on 2015-04-28 at 12:59.","DSpace SAF Submission Ingestion Package generated from Vireo submission #8103 on 2015-07-22 at 10:34:01","Made available in DSpace on 2015-07-22T22:17:43Z (GMT). No. of bitstreams: 2 GALTIERI-THESIS-2015.pdf: 5738307 bytes, checksum: 1d15fab4a488db5b7a3d7598f07a4926 (MD5) LICENSE.txt: 4211 bytes, checksum: b3502b0b34645a529f253c2bea28e0a3 (MD5) Previous issue date: 2015-04-28"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/78496"],"dc:language":["en"],"dc:rights":["Copyright 2015 Jason A. Galtieri"],"dc:subject":["differential power processing","solar simulator","self-shading","modeling","irradiance","factory binning"],"dc:title":["Differential power processing for increased solar array energy harvest"],"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":"2026-07-22T22:26:11Z"}