Solar panels are safe and one of the commonly used renewable sources of energy generation now-a-days and are subjected to different atmospheric conditions. Data loggers are used to monitor the condition of solar panels with the help of data acquisition system. Zigbee is used as a transferring solar data from solar panels to the recording system (laptop). QR code is basically used to store and share any content, here in this paper an advanced technique is used to store the solar panel data in QR code in video form followed by developing a web application. This solar panel data can easily be accessed by scanning the generated QR code through QR code scanner installed in android mobile phone. One of the advantages of technique used in this research paper is to visualize the variations of graphs and values of data logger which were displayed on the screen of laptop during online in video format. This video format file is stored in QR code which reduces the size of pre-stored solar panel data file. Second advantage of technique used here that QR code allows reducing the size of pre-stored video format file of solar panel data monitoring system into image format without any loss of data. 

Solar batteries are the essential component in an off-grid solar photovoltaic generation system and used for the purpose of storage. Normally lead acid batteries are used for solar applications and are placed in a battery room where the temperature must be maintained with in safe working limits. The temperature of battery depends on several factors like ambient temperature, load current drawn by the battery, sulphur deposition terminals, charging and discharging cycles. When temperature of a battery increases beyond safe limit problems of heating arises. Heating reduces the battery life and may be one of the reasons of explosion in batteries. The ambient temperature measuring device used in battery room is not sufficient to measure the heat generated by batteries. Installation of a normal camera in battery room is capable to monitor the smoke or spark in battery components but not the amount of temperature so it is also not fulfilling the need. Thermal imaging camera captures heat coming out from a battery and produces a thermal image with temperatures associated with it. This thermal image is used for representing high and low temperatures with a range of maximum and minimum values of temperature. In this paper a heated battery is identified in a battery room for solar photovoltaic generation system and thermal image analysis is performed to determine the regions of high temperature with the help of image segmentation and 3D temperature plot. The image segmentation is done using marker based watershed transform technique to achieve the heated region of interest from thermal image and 3D temperature plot shows the area of maximum temperature with location in thermal image of heated solar battery.  

Sun is an ultimate source of energy, which is clean, inexhaustible and safe for environment. The energy obtained from sun is known as solar energy. When solar radiations fall on earth surface solar cells convert these solar radiations into electrical energy. Solar cells are one of the important components of solar panels. Many solar cells combine in series or in parallel to form solar module and solar panels. A solar photovoltaic array is a combination of solar panels and is installed in open atmospheric condition. The natural conditions such as dust and dirt, shade of tree affect operation of solar panels. These natural conditions cannot be avoided but can be analyzed using visual inspection and thermal camera. The visual inspection approach is useful only when the defects are visible by naked human eye but when defects cannot be visualized by naked human eye thermo-graphical approach is used. This paper discusses the identification of various defects in solar panels by applying image processing technique applied for thermal images under natural atmospheric conditions for visual inspection, shading effect of tree, dust and dirt deposition effects on solar panels using thermal imaging camera. 

To obtain solar energy from solar photo-voltaic panels is not a new task now a days. Solar panels are designed to give their maximum possible output when exposed to the solar radiations. The operating conditions of solar panels affected by the atmospheric conditions like dust, dirt, solar INSOLATION, temperature etc. Here the effect of cement and bird deposits on the surface of solar panels is considered. Temperature rise due to cement and bird deposits develop hot-spots and affects the electrical power output of the solar panel. The cement and bird deposits can be seen by visually on solar panel surface but their effect can not be visualized by naked eye. The infrared THERMOGRAPHY helps to analyze these effects by using thermal imaging camera. This paper focus to study the temperature effects of cement and bird deposition on solar panel surface by capturing thermal images along with analyzing the thermal images using MATLAB digital image processing for better understanding. Image segmentation for cement and bird deposits is performed using watershed transform to achieve the desired region of interest from thermal images.

Sun being a non-conventional source of energy produces solar energy which is clean and available in abundance. The power obtained from solar panels is used to charge solar batteries and utilized to get continuous power supply. Solar panels are installed in open atmosphere and when subjected to different weather conditions involve many problems such as damage to different components, loss of power generation and heating. The different deposits on solar panel surface such as cement deposits, bird droppings increase temperature of deposited area and produce heating. The heating in solar panels develop hot spots. Batteries placed in a battery room attain high temperature and produce heat. This overheating affect working and performance of solar panels and batteries. These effects of heat are not visible by naked eye but are visible in thermal images, captured using thermal imaging camera. This paper focus on implementing an efficient visualization technique to segment the desired portion of heat from thermal images of solar panels and batteries using watershed transform. 

Inrush current is a very important phenomenon which occurs during energization of transformer at no load due to temporary over fluxing. It depends on several factors like magnetization curve, resistant and inductance of primary winding, supply frequency, switching angle of circuit breaker etc. Magnetizing characteristics of core represents nonlinearity which requires improved nonlinearity solving technique to know the practical behavior of inrush current. Since several techniques still working on modeling of transformer inrush current but neural network ensures exact modeling with experimental data. Therefore, the objective of this study was to develop an Artificial Neural Network (ANN) model based on data of switching angle and remanent flux for predicting peak of inrush current. Back Propagation with Levenberg-Marquardt (LM) algorithm was used to train the ANN architecture and same was tested for the various data sets. This research work demonstrates that the developed ANN model exhibits good performance in prediction of inrush current’s peak with an average of percentage error of -0.00168 and for modeling of inrush current with an average of percentage error of -0.52913.