Understanding Renewable Energy Systems

Quaschning, Volker

doi:10.4324/9781315800493

Cited by 55 publications

(68 citation statements)

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“…Using the Shockley equation in one-diode model (3), it can be assumed that ideally, the short circuit current ISC is equal to the photocurrent IPh [32][33][34].…”

Section: Mathematical Equationsmentioning

confidence: 99%

Comparison of the indoor performance of 12 commercial PV products by a simple model

Apostolou

Reinders

Verwaal

2016

Energy Science & Engineering

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This article presents a simple comparative model which has been developed for the estimation of the performance of photovoltaic (PV) products' cells in indoor environments. The model predicts the performance of PV solar cells, as a function of the distance from a spectrum of artificial (fluorescent light, halogen light, and light-emitting diodes) and natural light. It intends to support designers, while creating PV-integrated products for indoor use. For the model's validation, PV cells of 12 commercially available PV-powered products with power ranging from 0.8 to 4 mWp were tested indoors under artificial illumination and natural light. The model is based on the physical measurements of natural and artificial irradiance indoors, along with literature data of PV technologies under low irradiance conditions. The input data of the model are the surface of the solar cell (in m 2 ), the wavelength-dependent spectral response (SR) of the PV cell, the spectral irradiance indoors, and solar cell's distance from light sources. The model calculates solar cells' efficiency and power produced under the specific indoor conditions. If using the measured SR of a PV cell and the irradiance as measured indoors, the model can predict the performance of a PV product under mixed indoor light with a typical inaccuracy of around 25%, which is sufficient for a design process. Measurements revealed that under mixed indoor lighting of around 20 W/m 2 , the efficiency of solar cells in 12 commercially available PV products ranges between 5% and 6% for amorphous silicon (a-Si) cells, 4-6% for multicrystalline silicon (mc-Si) cells, and 5-7% for the monocrystalline silicon (c-Si) cells. 70

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“…Using the Shockley equation in one-diode model (3), it can be assumed that ideally, the short circuit current ISC is equal to the photocurrent IPh [32][33][34].…”

Section: Mathematical Equationsmentioning

confidence: 99%

Comparison of the indoor performance of 12 commercial PV products by a simple model

Apostolou

Reinders

Verwaal

2016

Energy Science & Engineering

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“…The solar irradiance profiles are classified and the most common profiles are used for the calculation. The efficiency of the solar collector is given in Equation (1) [5]:…”

Section: Determination Of Solar Collector Heat Outputmentioning

confidence: 99%

“…Solar thermal technology, on the other hand, captures solar radiation by heating a fluid, which is then used to generate electricity or process heating. A solar thermal energy system is often used in the industrial sector to supply low-grade thermal heat (80 to 100 • C) [4], and it becomes more favorable in situations of high solar irradiances and high ambient air temperature to guarantee high efficiency of a solar collector [5]. The solar thermal system design is essential to assure its optimal performance and maximize economic benefits.…”

Section: Introductionmentioning

confidence: 99%

Time-Dependent Integration of Solar Thermal Technology in Industrial Processes

et al. 2020

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Solar energy is currently an underutilized renewable energy source that could fulfill low-temperature industrial heat demands with significant potential in high solar irradiance counties such as Malaysia. This study proposes a new systematic method for optimization of solar heat integration for different process options to minimize the levelized cost of heat by combining different methods from the literature. A case study from the literature is presented to demonstrate the proposed method combined with meteorological data in Malaysia. The method estimates capital cost and levelized cost of solar heating considering important physical constraints (e.g., available space) and recovery of waste heat. The method determines and optimizes important physical dimensions, including collector area, storage size, and control design. As the result of the case study, the solar thermal integration with Clean-In-Place streams (hot water) gives the lowest levelized cost of heat with RM 0.63/kWh (0.13 EUR/kWh) due to its lowest process temperature requirement. The sensitivity analysis indicates that collector price and collector efficiency are the critical parameters of solar thermal integration.

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“…Since the meteorological stations usually measure the global solar radiation on a horizontal surface (ℜ hor ), solar radiation received on PV module is calculated as [39]:…”

Section: Appendix Amentioning

confidence: 99%

ANN-based correlation of measurements in micro-grid state estimation

Ranković

Maksimović

Sarić

et al. 2014

Int. Trans. Electr. Energ. Syst.

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Summary This paper examines the influence of correlated pseudo measurements on the three‐phase (sequence component‐based) micro‐grid state estimation. Pseudo measurements are used as the external inputs to replace the unavailable real‐time measurements on distributed generation (DG) units and loads to provide the minimum bus observability. Output powers of unmonitored DG (photovoltaic and wind‐based) units and loads are evaluated using the weather (either measured or forecasted) data, historically recorded state estimation patterns and available real‐time measurements. The historical data are classified into clusters by the Self‐Organization Map Artificial Neural Network (SOM ANN). The correlation coefficients between dependent pseudo measurements are calculated from clustered weather data and corresponding powers from DG units or loads, where the Feed Forward Artificial Neural Networks (FF ANNs) with backpropagation are used for approximating the output active power of unmonitored elements. The results and practical aspects of the proposed three‐phase state estimation methodology with correlated measurements are demonstrated on two (benchmark and real‐world) micro‐grids. Copyright © 2014 John Wiley & Sons, Ltd.

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Understanding Renewable Energy Systems

Cited by 55 publications

References 0 publications

Comparison of the indoor performance of 12 commercial PV products by a simple model

Comparison of the indoor performance of 12 commercial PV products by a simple model

Time-Dependent Integration of Solar Thermal Technology in Industrial Processes

ANN-based correlation of measurements in micro-grid state estimation

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