Recent advances in solar photovoltaic systems for emerging trends and advanced applications

Pandey, A.K.; Tyagi, V.V.; Jeyraj, A; Selvaraj, Laveen Prabhu; Rahim, N.A.; Tyagi, S. K.

doi:10.1016/j.rser.2015.09.043

Cited by 261 publications

(104 citation statements)

References 40 publications

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“…By 2020, the energy consumption within developing countries is expected to double from 2015 levels [1]. This additional generation capacity, especially if based on non-renewable resources, will have negative consequences to Earth's climate, which in turn adds urgency to the development and integration of renewable energy technologies.…”

Section: Introductionmentioning

confidence: 99%

Comparative Study on KNN and SVM Based Weather Classification Models for Day Ahead Short Term Solar PV Power Forecasting

et al. 2017

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Accurate solar photovoltaic (PV) power forecasting is an essential tool for mitigating the negative effects caused by the uncertainty of PV output power in systems with high penetration levels of solar PV generation. Weather classification based modeling is an effective way to increase the accuracy of day-ahead short-term (DAST) solar PV power forecasting because PV output power is strongly dependent on the specific weather conditions in a given time period. However, the accuracy of daily weather classification relies on both the applied classifiers and the training data. This paper aims to reveal how these two factors impact the classification performance and to delineate the relation between classification accuracy and sample dataset scale. Two commonly used classification methods, K-nearest neighbors (KNN) and support vector machines (SVM) are applied to classify the daily local weather types for DAST solar PV power forecasting using the operation data from a grid-connected PV plant in Hohhot, Inner Mongolia, China. We assessed the performance of SVM and KNN approaches, and then investigated the influences of sample scale, the number of categories, and the data distribution in different categories on the daily weather classification results. The simulation results illustrate that SVM performs well with small sample scale, while KNN is more sensitive to the length of the training dataset and can achieve higher accuracy than SVM with sufficient samples.

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Section: Introductionmentioning

confidence: 99%

Comparative Study on KNN and SVM Based Weather Classification Models for Day Ahead Short Term Solar PV Power Forecasting

et al. 2017

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“…However, the highest efficiency for non-concentrated silicon solar cell design reported so far is 25% only [10]. It is difficult to further increase the efficiency, although following methods have been employed:  Use of hydrogenated silicon [11]  Use of nano particles as the back electrodes [12]  Use of textured back surface reflector [13]  Use of ZnO based back reflector in triple junction thin film solar cell [14]  Use of concentrators on different substrates [15]  Use of double and triple junctions [16]  Incorporation of oxygen in Si, etc.…”

Section: Introductionmentioning

confidence: 99%

Advances in nanostructured thin film materials for solar cell applications

Ali

Hussain

Abdiche

et al. 2016

Renewable and Sustainable Energy Reviews

152

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“…The extensive research and global interest in BIPV over the last one decade is not likely to abate. Areas such as daylighting, self-cleaning PV glazing, aesthetics using color, form or shapes, concentrating BIPV, perovskite-based solar cells and solar trees are some of the emerging areas [36,45,[100][101][102][103]. With shifting policies, government tariffs and policy changes, it will also be interesting to investigate the possibility of using demonstration projects in certain regions as a push for BIPV-wide acceptance.…”

Section: Discussionmentioning

confidence: 99%

A Review on Building Integrated Photovoltaic Façade Customization Potentials

Attoye

Aoul

Hassan³

2017

Sustainability

103

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Technological advancement in Building Integrated Photovoltaics (BIPV) has converted the building façade into a renewable energy-based generator. The BIPV façade is designed to provide energy generation along with conventional design objectives such as aesthetics and environmental control. The challenge however, is that architectural design objectives sometimes conflict with energy performance, such as the provision of view and daylight versus maximum power output. In innovative cases, the characteristics of conventional BIPV façades have been modified by researchers to address such conflicts through customization as an emerging trend in BIPV façade design. Although extensive reviews exist on BIPV product types, design integration, adoption barriers and performance issues, research on BIPV customization has not been reviewed as a solution to BIPV adoption. This paper seeks to review the potential of BIPV façade customization as a means of enhancing BIPV adoption. The current paper identifies customization parameters ranging from the customization category, level, and strategies, and related architectural potential along with an assessment of their impact. The findings reflect that elemental and compositional level customization using combined customization strategies provide enhanced BIPV products. These products are well integrated for both energy generation and aesthetic applications with a power output increase of up to 80% in some cases. The paper concludes that a wide range of BIPV adoption barriers such as aesthetics, architectural integration, and performance can be overcome by appropriate BIPV customization.

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Recent advances in solar photovoltaic systems for emerging trends and advanced applications

Cited by 261 publications

References 40 publications

Comparative Study on KNN and SVM Based Weather Classification Models for Day Ahead Short Term Solar PV Power Forecasting

Comparative Study on KNN and SVM Based Weather Classification Models for Day Ahead Short Term Solar PV Power Forecasting

Advances in nanostructured thin film materials for solar cell applications

A Review on Building Integrated Photovoltaic Façade Customization Potentials

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