Analysis of Solar Census Remote Solar Access Value Calculation Methodology

Nangle, John

doi:10.2172/1176739

Cited by 1 publication

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References 1 publication

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“…Although a typical aerial overflight produces flat images, 3D data can be obtained from special instrumentation, such as stereo photogrammetry or Light Detection and Ranging [12][13][14][15]. Previous comparisons of the solar access values (SAVs) from aerial imagery site survey techniques versus those generated by the Solmetric SunEye [36,37] have shown that the methods give statistically equivalent results. Specifically, these previous validation efforts have found statistical equivalence between aerial imagery techniques and rooftop site surveys within ±3% on an annual basis and 10% on a monthly basis for a given PV installation.…”

Section: Aerial Imagery Shade Estimationmentioning

confidence: 99%

Measured and estimated performance of a fleet of shaded photovoltaic systems with string and module‐level inverters

MacAlpine

Deline

Dobos

2017

Progress in Photovoltaics

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Shade obstructions can significantly impact the performance of photovoltaic (PV) systems. Although there are many models for partially shaded PV arrays, there is a lack of information available regarding their accuracy and uncertainty when compared with actual field performance. This work assesses the recorded performance of 46 residential PV systems, equipped with either string-level or module-level inverters, under a variety of shading conditions. We compare their energy production data to annual PV performance predictions, with a focus on the practical models developed here for National Renewable Energy Laboratory's SYSTEM ADVISOR MODEL software. This includes assessment of shade extent on each PV system by using traditional onsite surveys and newer 3D obstruction modelling. The electrical impact of shade is modelled by either a nonlinear performance model or assumption of linear impact with shade extent, depending on the inverter type. When applied to the fleet of residential PV systems, performance is predicted with median annual bias errors of 2.5% or less, for systems with up to 20% estimated shading loss. The partial shade models are not found to add appreciable uncertainty to annual predictions of energy production for this fleet of systems but do introduce a monthly root-mean-square error of approximately 4%-9% due to seasonal effects. Use of a detailed 3D model results in similar or improved accuracy over site survey methods, indicating that, with proper description of shade obstructions, modelling of partially shaded PV arrays can be done completely remotely, potentially saving time and cost. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

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