Evaluating a model to estimate GHI, DNI, &amp; DHI from POA irradiance

Gostein, Michael; Stueve, Bill; Passow, Kendra; Panchula, Alex

doi:10.1109/pvsc.2016.7749749

Cited by 6 publications

(4 citation statements)

References 4 publications

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“…Optimally, correlating satellite and ground-based weather data with photovoltaic system performance requires knowledge of four different quantities: GHI, DNI, DHI, and plane of array (POA) radiation. High accuracy instrumentation measure all four quantities can be used in weather stations for utility scale projects [21].…”

Section: Related Studiesmentioning

confidence: 99%

Solar irradiation forecastby deep learning architectures

et al. 2022

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Global solar irradiation data is a crucial component to measure solar energy potential when we plan, size, and design solar photovoltaic fields. Often, due to the absence of measuring equipment at meteorological stations, data for the place of interest are not available. However, solar irradiation can be estimated by ordinary meteorological data such as humidity, and air temperature. Herein we propose two different deep learning methods, one based on a deep neural network regression and the other based on multivariate long short term memory unit networks, to estimate solar irradiation at given locations. Validation criteria include mean absolute error, mean squared error, and coefficient of determination (R2 value). According to the simulation results, multivariate long short term memory unit networks performs slightly better than deep neural network. Even though both have very close R2 values, multivariate long short term memory?s R2 values are more consistent. The same is true for mean squared error and mean absolute error.

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Section: Related Studiesmentioning

confidence: 99%

Solar irradiation forecastby deep learning architectures

et al. 2022

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“…Considered solar irradiance types are [22]: 1. Global Horizontal Irradiance (GHI): the total of both direct and diffused irradiance on a horizontal unit area.…”

Section: Solar Irradiance Datamentioning

confidence: 99%

A Review of Solar Energy Prospects in Palestine

Ajlouni¹,

Alsamamra²

2019

AJME

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Energy is the main player in the community's development in several aspects. Palestine is an occupied developing country which has a complicated energy sector. Renewable Energy (RE) resources are considered the optimal practical solution to mitigate or resolve the energy crisis in Palestine. Most of Palestine receives solar radiation about 3000 hours annually, and the average solar radiation values range from 5.4 kWh/m 2 .day to 6.0 kWh/m 2 .day. These results of solar radiation, in addition to the absence of political restrictions on the use of solar energy technology, make solar energy the most viable and feasible choice among other renewable sources. This work objective is to introduce a comprehensive review of the solar energy prospects in Palestine, its geographical data, applications, legislative, and economic potential in contrast to established projects and modules. This review is based on introducing analyzed information about solar energy characteristics in Palestine, Applied solar systems and technology, the policies and legislation, and a recap of strengths, drawbacks, and recommendations. Results showed that best locations for PV solar energy exploitation are Gaza and south West Bank, and worst is Jericho, which leads to resolve many developmental issues in both rural and urban areas.

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“…models allowing the estimation of the different components of the global irradiation -are usually developed for the global horizontal irradiation (GHI). Such measurements being not available at the two considered plants, two possibilities from the literature are possible: estimating the GHI from POA measurement [15,8] or using satellite-derived GHI data. These two methods enable to decompose the POA and can be used in the proposed model.…”

Section: Estimation Of the Three Components Of The Plane-of-array Irrmentioning

confidence: 99%

Data-analysis and modelling of the effect of inter-row shading on the power production of photovoltaic plants

Saint‐Drenan

Barbier

2019

Solar Energy

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The aim of this work is to propose a fast and easily implementable model allowing the consideration of inter-row shading in the simulation of the power production of PV plants. Our objective is to find the simplest model with the least number of input parameters. A formulation of the shaded fraction of the module area dependent on the PV configuration and the sun position is first proposed. An analysis of the measurements of two plants is then carried out to understand the effect of inter-row shading for a complete PV array. Based on this analysis, a model is proposed and validated. It is shown that the consideration of inter-row shading with the proposed model allows a relative improvement of the simulation accuracy (RMSE) ranging between 18 and 32 % for time steps affected by inter-row shading and between 7 and 12 % for a complete year.

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Evaluating a model to estimate GHI, DNI, & DHI from POA irradiance

Cited by 6 publications

References 4 publications

Solar irradiation forecastby deep learning architectures

Solar irradiation forecastby deep learning architectures

A Review of Solar Energy Prospects in Palestine

Data-analysis and modelling of the effect of inter-row shading on the power production of photovoltaic plants

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