Showing papers by "Violeta Holmes published in 2019"

Novel Photovoltaic Micro Crack Detection Technique

Abstract: This paper presents a novel detection technique for inspecting solar cells’ micro cracks. Initially, the solar cell is captured using the electroluminescence (EL) method, then processed by the proposed technique. The technique consists of three stages: the first stage combines two images, the first image is the crack-free (healthy) solar cell, whereas the second is the cracked solar-cell image. Both output images are processed into a bit-by-bit gridding technique, which enables the detection of all bits in the considered area of the cracked solar cell. The second stage uses an OR gate between each examined bit for both healthy and cracked solar cells. The final calibrated image presents a high-quality and low-noise structure, thus making it easier to identify the micro crack size, location, and its orientation. In order to examine the effectiveness of the proposed technique, three different cracked photovoltaic (PV) solar cells have been examined. The results show that the micro cracks’ size, orientation, and location are more visible using the proposed technique. In addition, the developed technique has been validated using a full-scale PV module, and compared with up-to-date available PV micro crack detection methods.

Game-based learning in mechanical engineering education: Case study of games-based learning application in computer aided design assembly

Abstract: In our research, we aim to evaluate the effectiveness of games-based learning within a computer aided design and manufacture undergraduate module. Although widely used in a selection of subject are...

Novel Photovoltaic Hot-Spotting Fault Detection Algorithm

Abstract: In this paper, a novel photovoltaic (PV) hot-spotting fault detection algorithm is presented. The algorithm is implemented using the analysis of 2580 polycrystalline silicon PV modules distributed across the U.K. The evaluation of the hot-spots is analyzed based on the cumulative density function (CDF) modeling technique, whereas the percentage of power loss (PPL) and PV degradation rate are used to categorize the hot-spots into eight different categories. Next, the implemented CDF models are used to predict possible PV hot-spots affecting the PV modules. The developed algorithm is evaluated using three different PV modules affected by three different hot-spots. Remarkably, the proposed CDF models precisely categorize the PV hot-spots with a high rate of accuracy of almost above 80%.

CDF modelling for the optimum tilt and azimuth angle for PV installations: case study based on 26 different locations in region of the Yorkshire UK

Abstract: The optimum tilt and azimuth angle for PV installations in 26 different locations within the county of Yorkshire, UK have been evaluated. In order to examine the performance of the PV systems, a selection of criteria has been identified as follows: (i) the maximum difference in the age of the PV installations is no older than two years, (ii) PV modules technology is crystalline-Silicon (c-Si), (iii) maximum area of study in each location is 20 km 2 , and (iv) PV systems have either the same tilt or azimuth angle within ±2°. The Huddersfield area was used as the primary example to evaluate the proposed methodology. The optimum tilt and azimuth angle for PV installations in the area is 39° and -1° respectively. Moreover, based on 4 kWp PV installations observed in all studied locations, a geographical map representing the annual energy production in the 26 locations has been drawn. The maximum annual energy production is observed for the city of Hull, whereas the minimum observed for the town of Keighley. Finally, the evaluation of the overall annual energy production is discussed using the analysis of the direct normal irradiance (DNI), ambient temperature, air frost, and the cloudiness.