Measured and modeled photovoltaic system energy losses from snow for Colorado and Wisconsin locations

Marion, Bill; Schaefer, Robert; Caine, Holden; Sánchez, Gonzalo García de Casasola

doi:10.1016/j.solener.2013.07.029

Cited by 114 publications

(70 citation statements)

References 7 publications

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“…All of the SAM simulations use appropriate nearby (within 50 km) weather data collected through Measurement and Instrumentation Data Center, adjusted for system downtime indicated by the performance data. The PV systems located in Colorado also use SAM's snow loss model [43,44].…”

Section: Methodsmentioning

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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Section: Methodsmentioning

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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“…Contributing research on this problem includes a study on a method that models the snowfall and melting processes, 1 and a method that models the "sliding off" of accumulated snow from the PV panels. 2 The second has to do with the PV output estimation method using information about snow accumulation on the PV panels. There have been studies on methods of estimating power output by calculating the snow accumulation area using mesh accumulation data within the power supply area, 3 methods of statistically calculating, according to snow depth, the efficiency coefficient for calculating the amount of power generation from the amount of sunlight, 4 and methods that employ the Lambert-Beer law to physically calculate the degree of attenuation of solar radiation due to the depth of snow accumulated on a PV panel.…”

Section: Introductionmentioning

confidence: 99%

Estimation Method of Photovoltaic Power Output using Extended Lambert-Beer Law

2020

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In recent years, there have been growing needs for accurate estimation of photovoltaic (PV) power due to the widespread use of PV power generation. PV power is usually estimated based on the amount of solar radiation, air temperature, and wind velocity. However, when the PV panel is covered with snow, the solar radiation is blocked by the snow and expected PV output cannot be obtained. In this paper, for accurate PV power estimation, we propose an Extended Lambert-Beer law, and investigate a method to estimate the degree of attenuation of PV power by snow cover. And, accuracy verification of the proposed method is carried out with actual PV power records from when snow accumulated in the Tokyo Electric Power Company (TEPCO) service area in 2018. K E Y W O R D SLambert-Beer law, output estimation, photovoltaic, snow Electr Eng Jpn. 2020;212:35-42.

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“…The first has to do with the estimation of the presence of snow on PV panels. Contributing research on this problem includes a study on a method that models the snowfall and melting processes, 1 and a method that models the “sliding off” of accumulated snow from the PV panels 2 . The second has to do with the PV output estimation method using information about snow accumulation on the PV panels.…”

Section: Introductionmentioning

confidence: 99%

Estimation method of photovoltaic power output using extended Lambert‐Beer law

Odashima

Shinoda

Takeda

2020

Electrical Engineering Japan

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In recent years, there have been growing needs for accurate estimation of photovoltaic (PV) power due to the widespread use of PV power generation. PV power is usually estimated based on the amount of solar radiation, air temperature, and wind velocity. However, when the PV panel is covered with snow, the solar radiation is blocked by the snow and expected PV output cannot be obtained. In this paper, for accurate PV power estimation, we propose an Extended Lambert‐Beer law, and investigate a method to estimate the degree of attenuation of PV power by snow cover. And, accuracy verification of the proposed method is carried out with actual PV power records from when snow accumulated in the Tokyo Electric Power Company (TEPCO) service area in 2018.

show abstract

Measured and modeled photovoltaic system energy losses from snow for Colorado and Wisconsin locations

Cited by 114 publications

References 7 publications

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

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

Estimation Method of Photovoltaic Power Output using Extended Lambert-Beer Law

Estimation method of photovoltaic power output using extended Lambert‐Beer law

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