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dc.contributor.authorNguyen, H. T.
dc.contributor.otherQueen's University (Kingston, Ont.). Theses (Queen's University (Kingston, Ont.))en
dc.date2011-05-26 15:35:19.118en
dc.date.accessioned2017-02-14T16:39:45Z
dc.date.available2017-02-14T16:39:45Z
dc.identifier.urihttp://hdl.handle.net/1974/15384
dc.descriptionThesis (Master, Mechanical and Materials Engineering) -- Queen's University, 2011-05-26 15:35:19.118en
dc.description.abstractAn understanding of the urban local potential (roof space and solar exposure) is critical for utility planning, accommodating grid capacity, deploying financing schemes and formulating future adaptive policies to take advantage of PV technology's continued price declines. This thesis provides a sequence of methodologies to acquire and pre-process data and access solar PV potential from i) a regional scale, ii) a municipal scale and iii) a municipal district unit. This research explores and confirms the robustness and versatility of the r.sun module within the open source Geographic Resources Analysis Support System (GRASS) for the purpose of solar irradiation modeling at different levels of surface complexity. At the regional scale, the fourteen counties in southeastern Ontario that served as a case study was found to possess over 935,000 acres appropriate for solar farm development, which could provide 90 GW of PV. At the municipal scale, another methodology was developed to provide urban solar PV resource assessments, which is widely applicable throughout the world. The results of the case study indicate that utilities needing to plan for large scale solar electric generation in urban areas can make a rule of thumb estimate. In the absence of advanced computational expertise and high quality remotely sensed data, 30% of the projected area of roofprints can be used as a first pass estimation of the available area for PV installation. Finally, for the municipal district unit, a separate workflow that attains a 95% accurate segmentation from raw and randomly chosen Light Detection And Ranging (LiDAR) data was demonstrated. The solar PV resource assessment on this scale returned 22,000m2 of roof area out of a two dimensional extent of approximately 40,000m2 in building coverage as suitable for the purpose of solar PV installations. With higher integration of urban texture, it was found that the global horizontal irradiation is lower than the regional scale by 30% due to near shadowing effects in downtown Kingston. The three methodologies presented here at three scales provide the foundation to enable automated analysis of solar PV potential and planning for any given region with marginal LiDAR data.en
dc.languageenen
dc.language.isoenen
dc.relation.ispartofseriesCanadian thesesen
dc.rightsThis publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.en
dc.subjectGISen
dc.subjectshadingen
dc.subjectsolar photovoltaicen
dc.subjectglobal horizontal irradianceen
dc.subjectr.sunen
dc.subjectLight Detection And Rangingen
dc.titleSolar Photovoltaic Resource Assessment From The Macro Scale To The Meso Scale Using Airborne Laser Scanning Data And Open Source Toolsen
dc.typeThesisen
dc.description.degreeMasteren
dc.contributor.supervisorPearce, Joshua M.en
dc.contributor.departmentMechanical and Materials Engineeringen
dc.embargo.terms1825
dc.embargo.liftdate2017-11-22


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