A Study on Solar Power Generation Efficiency Empirical Analysis according to Temperature and Wind speed

Cha, Wang-Cheol; Park, Joung-Ho; Cho, Uk-Rae; Kim, Jae-Chul

doi:10.5370/kieep.2015.64.1.001

Cited by 4 publications

(3 citation statements)

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“…Equation (1) represents the most popular model to estimate solar energy (E, kWh) based on three factors, namely daily solar radiation per unit area (S, kWh/m 2 /day), capacity of a PV module per unit area (P out , kW/m 2 ), and efficiency of electricity generation (k) [26,27].…”

Section: Solar Radiation-based Modelmentioning

confidence: 99%

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Performance Estimation Modeling via Machine Learning of an Agrophotovoltaic System in South Korea

Kim

2021

Energies

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The Agrophotovoltaic (APV) system is a novel concept in the field of Renewable Energy Systems. This system enables the generation of solar energy via photo-voltaic (PV) modules above crops, to mitigate harmful impact on food production. This study aims to develop a performance evaluation model for an APV system in a temperate climate region, such as South Korea. To this end, both traditional electricity generation models (solar radiation-based model and climate-based model) of PV modules and two major machine learning (ML) techniques (i.e., polynomial regression and deep learning) have been considered. Electricity generation data was collected via remote sensors installed in the APV system at Jeollanam-do Agricultural Research and Extension Services in South Korea. Moreover, economic analysis in terms of cost and benefit of the subject APV system was conducted to provide information about the return on investment to farmers and government agencies. As a result, farmers, agronomists, and agricultural engineers can easily estimate performance and profit of their APV systems via the proposed performance model.

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Section: Solar Radiation-based Modelmentioning

confidence: 99%

“…To overcome the limitation of the solar radiation-based model, the climate-based model involving air temperature and windspeed was devised [27].…”

Section: Climate-based Modelmentioning

confidence: 99%

Performance Estimation Modeling via Machine Learning of an Agrophotovoltaic System in South Korea

Kim

2021

Energies

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“…The PV module temperature has a significant effect on the energy output of a PV power system because it determines the maximum power output. Atmospheric parameters, such as the ambient temperature, irradiance, and wind speed, vary according to the installation conditions [1], [2]. Because of these environmental factors, it is common to use Nominal operating cell parameter (NOCT) according to IEC 61215:2005 [3] as an indicator of the module operating temperature.…”

Section: Introductionmentioning

confidence: 99%

Analysis on the Features of NOCT and NMOT Tests With Photovoltaic Module

et al. 2020

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The operating temperature of the photovoltaic (PV) module plays a major role among the parameters affecting the energy yield of photovoltaic (PV) power generation systems. This paper compared the requirements of Nominal Operating Cell Temperature (NOCT), which is used to estimate the PV module operating temperature according to IEC 61215:2005, with those of the recently revised IEC 61215: 2016 Nominal Module Operating Temperature (NMOT). Through this, each feature of the parameters used to calculate the NOCT and NMOT could be determined, and it was assumed that the NMOT is lower than NOCT. And, among the parameters, the wind speed was found to be a significant variable affecting the temperature, and non-linear clusters and skewed data are improved if some data in the morning were deleted considering the period of module activation. Moreover, it is found that the method summing up the daily data for the calculation can reduce the correlation and deviation of NMOT.

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Empirical Analysis on the Correlation Between Mono-crystalline Si Photovoltaic Module Temperature and Irradiance and Ambient Temperature in Seoul Area

Yun¹,

Park²,

Lee³

et al. 2017

ksmer

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A Study on Solar Power Generation Efficiency Empirical Analysis according to Temperature and Wind speed

Cited by 4 publications

References 0 publications

Performance Estimation Modeling via Machine Learning of an Agrophotovoltaic System in South Korea

Performance Estimation Modeling via Machine Learning of an Agrophotovoltaic System in South Korea

Analysis on the Features of NOCT and NMOT Tests With Photovoltaic Module

Empirical Analysis on the Correlation Between Mono-crystalline Si Photovoltaic Module Temperature and Irradiance and Ambient Temperature in Seoul Area

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