High energy yield bifacial spectrum-splitting photovoltaic system

2020 ◽  
Vol 59 (22) ◽  
pp. G8
Author(s):  
Benjamin D. Chrysler ◽  
Raymond K. Kostuk
Keyword(s):  
High Energy ◽  
Photovoltaic System ◽  
Energy Yield ◽  
Spectrum Splitting

scholarly journals Development of Amorphous/Microcrystalline Silicon Tandem Thin-Film Solar Modules with Low Output Voltage, High Energy Yield, Low Light-Induced Degradation, and High Damp-Heat Reliability

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Chin-Yi Tsai ◽  
Chin-Yao Tsai
Keyword(s):  
Thin Film ◽  
Output Voltage ◽  
Low Voltage ◽  
Crystalline Silicon ◽  
High Energy ◽  
Photovoltaic System ◽  
Performance Ratio ◽  
Energy Yield ◽  
Microcrystalline Silicon ◽  
Low Light

In this work, tandem amorphous/microcrystalline silicon thin-film solar modules with low output voltage, high energy yield, low light-induced degradation, and high damp-heat reliability were successfully designed and developed. Several key technologies of passivation, transparent-conducting-oxide films, and cell and segment laser scribing were researched, developed, and introduced into the production line to enhance the performance of these low-voltage modules. A 900 kWp photovoltaic system with these low-voltage panels was installed and its performance ratio has been simulated and projected to be 92.1%, which is 20% more than the crystalline silicon and CdTe counterparts.

scholarly journals Design and Development of an Online Smart Monitoring and Diagnosis System for Photovoltaic Distributed Generation

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8552
Author(s):  
Thiago A. Felipe ◽  
Fernando C. Melo ◽  
Luiz C. G. Freitas
Keyword(s):  
Power Plants ◽  
High Energy ◽  
Photovoltaic System ◽  
Maintenance Cost ◽  
Energy Yield ◽  
Energy Productivity ◽  
Partial Shading ◽  
Photovoltaic Modules ◽  
Field Experimentation ◽  
Photovoltaic Plants

In photovoltaic power plants, fault diagnosis tools are essential for ensuring a high energy yield. These tools should be capable of accurately identifying and quantifying the factors behind the various fault mechanisms commonly found in photovoltaic plants. Considering the aforementioned factors, this article proposes an online smart PV monitoring solution, which is capable of detecting malfunctions that arise from accidental and/or technical causes through the analysis of I-V curves, however, without the necessity to interrupt the operation of the system, thus reducing the maintenance cost. Accidental causes can lead to the reduction of energy productivity due to the excessive accumulation of dirt on the photovoltaic modules, partial shading and eventual errors that occur during its installation. On the other hand, technical causes can be attributed to faults found on the photovoltaic modules, which lead to gradual losses in their electric and material characteristics. Therefore, by using the electric characteristics supplied by the manufacturer of the installed modules, the I-V and P-V curves of the operational photovoltaic strings were obtained in real time, compared to the respective theoretical curves obtained through mathematical modeling. In order to validate the proposed online monitoring system and its potential for predictive maintenance application, a field experimentation was mounted in a 93.8 kWp photovoltaic system.

Optimizing genotype-environment-management interactions to ensure silage maize production in the Chinese Maize Belt

2020 ◽  
Vol 80 (2) ◽  
pp. 133-146
Author(s):  
L Zhang ◽  
Z Zhang ◽  
J Cao ◽  
Y Luo ◽  
Z Li
Keyword(s):  
Field Experiments ◽  
Weather Conditions ◽  
Growth Cycle ◽  
High Energy ◽  
Risk Level ◽  
Energy Yield ◽  
Maize Production ◽  
Early Date ◽  
Environment Management ◽  
Silage Maize

Grain maize production exceeds the demand for grain maize in China. Methods for harvesting good-quality silage maize urgently need a theoretical basis and reference data in order to ensure its benefits to farmers. However, research on silage maize is limited, and very few studies have focused on its energetic value and quality. Here, we calibrated the CERES-Maize model for 24 cultivars with 93 field experiments and then performed a long-term (1980-2017) simulation to optimize genotype-environment-management (G-E-M) interactions in the 4 main agroecological zones across China. We found that CERES-Maize could reproduce the growth and development of maize well under various management and weather conditions with a phenology bias of <5 d and biomass relative root mean square error values of <5%. The simulated results showed that sowing long-growth-cycle cultivars approximately 10 d in advance could yield good-quality silage. The optimal sowing dates (from late May to July) and harvest dates (from early October to mid-November) gradually became later from north to south. A high-energy yield was expected when sowing at an early date and/or with late-maturing cultivars. We found that Northeast China and the North China Plain were potential silage maize growing areas, although these areas experienced a medium or even high frost risk. Southwestern maize experienced a low risk level, but the low soil fertility limited the attainable yield. The results of this paper provide information for designing an optimal G×E×M strategy to ensure silage maize production in the Chinese Maize Belt.

scholarly journals Optimization of Lutein Recovery from Tetraselmis suecica by Response Surface Methodology

Biomolecules ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 182
Author(s):  
Kang Hyun Lee ◽  
Ye Won Jang ◽  
Hansol Kim ◽  
Jang-Seu Ki ◽  
Hah Young Yoo
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Radical Scavenging Activity ◽  
Radical Scavenging ◽  
High Energy ◽  
Solid Loading ◽  
Control Group ◽  
Energy Yield ◽  
Tetraselmis Suecica ◽  
Antioxidant Power

Microalgae have been attracting attention as feedstock for biorefinery because they have various advantages, such as carbon fixation, high growth rate and high energy yield. The bioactive compounds and lutein contained in microalgae are known to be beneficial for human health, especially eye and brain health. In this study, in order to improve the recovery of bioactive extracts including lutein from Tetraselmis suecica with higher efficiency, an effective solvent was selected, and the extraction parameters such as temperature, time and solid loading were optimized by response surface methodology. The most effective solvent for lutein recovery was identified as 100% methanol, and the optimum condition was determined (42.4 °C, 4.0 h and 125 g/L biomass loading) by calculation of the multiple regression model. The maximum content of recovered lutein was found to be 2.79 mg/mL, and the ABTS radical scavenging activity (IC50) and ferric reducing antioxidant power (FRAP) value were about 3.36 mg/mL and 561.9 μmol/L, respectively. Finally, the maximum lutein recovery from T. suecica through statistical optimization was estimated to be 22.3 mg/g biomass, which was 3.1-fold improved compared to the control group.

Potential contribution of the wastewater sector to energy supply

2011 ◽  
Vol 63 (8) ◽  
pp. 1765-1771 ◽  
Author(s):  
S. Heubeck ◽  
R. M. de Vos ◽  
R. Craggs
Keyword(s):  
New Zealand ◽  
Potential Energy ◽  
Biological Treatment ◽  
High Energy ◽  
Technology Selection ◽  
Energy Yield ◽  
Potential Contribution ◽  
Energy Potential ◽  
Treatment Technologies ◽  
Future Potential

The biological treatment of wastewater could yield high energy fuels such as methane and alcohols, however most conventional treatment systems do not recover this energy potential. With a simple model of the energy yields of various wastewater treatment technologies it is possible to demonstrate how minor shifts in technology selection can lead the industry from being identified as predominantly energy intensive, to being recognised as a source of energy resources. The future potential energy yield is estimated by applying energy yield factors to alternative use scenarios of the same wastewater loads. The method for identifying the energy potential of wastewater was demonstrated for the New Zealand wastewater sector, but can equally be applied to other countries or regions. The model suggests that by using technologies that maximise the recovery of energy from wastewater, the potential energy yield from this sector would be substantially increased (six fold for New Zealand).

scholarly journals Outdoor measurements of a photovoltaic system using diffractive spectrum-splitting and concentration

AIP Advances ◽  
2016 ◽  
Vol 6 (9) ◽  
pp. 095311 ◽  
Author(s):  
N. Mohammad ◽  
M. Schulz ◽  
P. Wang ◽  
R. Menon
Keyword(s):  
Photovoltaic System ◽  
Spectrum Splitting

scholarly journals Assessment of Wind Characteristics and Wind Power Potential of Gharo, Pakistan

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Zahid Hussain Hulio
Keyword(s):  
Wind Turbine ◽  
Wind Power ◽  
Frequency Distribution ◽  
Cost Estimation ◽  
Wind Farm ◽  
Research Work ◽  
Economic Assessment ◽  
High Energy ◽  
Energy Yield ◽  
Wind Characteristics

The objective of this research work is to assess the wind characteristics and wind power potential of Gharo site. The wind parameters of the site have been used to calculate the wind power density, annual energy yield, and capacity factors at 10, 30, and 50 m. The wind frequency distribution including seasonal as well as percentage of seasonal frequency distribution has been investigated to determine accurately the wind power of the site. The coefficient of variation is calculated at three different heights. Also, economic assessment per kWh of energy has been carried out. The site-specific annual mean wind speeds were 6.89, 5.85, and 3.85 m/s at 50, 30, and 10 m heights with corresponding standard deviations of 2.946, 2.489, and 2.040. The mean values of the Weibull k parameter are estimated as 2.946, 2.489, and 2.040 while those of scale parameter are estimated as 7.634, 6.465, and 4.180 m/s at 50, 30, and 10 m, respectively. The respective mean wind power and energy density values are found to be 118.3, 92.20, and 46.10 W/m2 and 1036.6, 807.90, and 402.60 kWh/m2. As per cost estimation of wind turbines, the wind turbine WT-C has the lowest cost of US$ Cents 0.0346/kWh and highest capacity factors of 0.3278 (32.78%). Wind turbine WT-C is recommended for this site for the wind farm deployment due to high energy generation and minimum price of energy. The results show the appropriateness of the methodology for assessing the wind speed and economic assessment at the lowest price of energy.

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