International Journal of Sustainable Energy 

About: International Journal of Sustainable Energy is an academic journal published by Taylor & Francis. The journal publishes majorly in the area(s): Renewable energy & Photovoltaic system. It has an ISSN identifier of 1478-6451. Over the lifetime, 863 publications have been published receiving 11138 citations.

PV-GIS: a web-based solar radiation database for the calculation of PV potential in Europe

Abstract: Solar radiation is a key factor determining electricity produced by photovoltaic (PV) systems. This paper presents a solar radiation database of Europe developed in the geographical information system, and three interactive web applications providing an access to it. The database includes monthly and yearly average values of the global irradiation on horizontal and inclined surfaces, as well as climatic parameters needed for an assessment of the potential PV electricity generation (Linke atmospheric turbidity, the ratio of diffuse to global irradiation, an optimum inclination angle of modules to maximize energy yield). In the first web application, a user may browse radiation maps and query irradiation incident on a PV module for different inclination angles. The second application simulates daily profiles of irradiance for a chosen month and module inclination and orientation. The third web application estimates electricity generation for a chosen PV configuration. It also calculates optimal inclination ...

Residential load and rooftop PV generation: an Australian distribution network dataset

Abstract: Despite the rapid uptake of small-scale solar photovoltaic (PV) systems in recent years, public availability of generation and load data at the household level remains very limited. Moreover, such data are typically measured using bi-directional meters recording only PV generation in excess of residential load rather than recording generation and load separately. In this paper, we report a publicly available dataset consisting of load and rooftop PV generation for 300 de-identified residential customers in an Australian distribution network, with load centres covering metropolitan Sydney and surrounding regional areas. The dataset spans a 3-year period, with separately reported measurements of load and PV generation at 30-min intervals. Following a detailed description of the dataset, we identify several means by which anomalous records (e.g. due to inverter failure) are identified and excised. With the resulting ‘clean’ dataset, we identify key customer-specific and aggregated characteristics of ...

Fault diagnosis of photovoltaic modules through image processing and Canny edge detection on field thermographic measurements

Abstract: Today, conventional condition monitoring of installed, operating photovoltaic (PV) modules is mainly based on electrical measurements and performance evaluation. However, such practices exhibit restricted fault-detection ability. This study proposes the use of standard thermal image processing and the Canny edge detection operator as diagnostic tools for module-related faults that lead to hot-spot heating effects. The intended techniques were applied on thermal images of defective PV modules, from several field infrared thermographic measurements conducted during this study. The whole approach provided promising results with the detection of hot-spot formations that were diagnosed to specific defective cells in each inspected module. These evolving hot spots lead to abnormally low performance of the PV modules, a fact that is also validated by the manufacturer's standard electrical tests.

The relationship between CO2 emissions, energy consumption and economic growth in Italy

Abstract: This study examines the relationship between CO2 emissions, energy consumption and economic growth in Italy over the period 1970–2006. Results of unit root tests show that all variables are non-stationary in their level form, but stationary in first differences form. The causal relationship between variables is examined using causality test in a vector autoregressive framework. Our empirical results show that CO2 emissions, energy consumption and economic growth are not cointegrated. Moreover, the Toda and Yamamoto Granger non-causality test shows a bidirectional causality between CO2 emissions and economic growth, as well as between CO2 emissions and energy consumption. Forecast error variance decompositions evidence that the errors in real per capita GDP are mainly due to uncertainty in GDP itself, while the errors in predicting the energy consumption and the CO2 emissions are sensitive to disturbances in the other two equations.

Evaluating the role of renewable energy, economic growth and agriculture on CO2 emission in E7 countries

Abstract: This study examines the dynamic links between per capita CO2 emission, economic growth, agricultural value added, renewable and non-renewable energy consumption and investigates the existence of En...