Due to photovoltaic (PV) technology advantages as a clean, secure, and pollution-free energy source, PV power plants installation have shown an essential role in the energy sector. Nevertheless, the PV power plant cost of energy must be competitive when compared to traditional energy sources. Therefore, numerous studies are continuously being conducted aiming to optimize PV power plants, including components arrangements within the installation site, the inverter topology, cables, PV modules and inverters numbers, PV module tilt angle and shadow effect. For selecting the most suitable combinations for system parameters, this study seeks to systematically analyze and synthesize the design of the PV power plant optimization from the current literature. The study also examines component sizing for PV power plants, involving PV modules tilt angle, inverter, transformer, and cables. Moreover, it provides an overview of the main components employed to install the PV power plant, which includes PV modules, inverter, transformer and wiring. It examines the different inverter topologies used in PV power plants along with a comparison between these topologies.

Green electricity and green transportation are the primary requirements for smart cities. Maximizing the EV utilization is the key requirement in the development of green transportation. However, the EV technology faces challenges due to the long battery recharging time and heavy batteries to achieve extended driving ranges. Different approaches are investigated to charge the EV by battery swapping, plugin or wireless. Recently the wireless charging approach is gaining popularity because of safety, extended driving range, dynamic charging and human intervention free recharging. However, multiple factors need to considered in the design of WPT system and requires expertise in different domains. This paper discusses a systematic approach on the various parameters involved in a dynamic wireless charging system design. The major functional units in WPT such as charging couplers, compensation network, and power inverters topologies are addressed. Additionally, this paper discusses the issues involved in grid-tied and renewable integrated dynamic charging systems. Moreover, the step by step procesdure is described to understand the process involved in the dynamic charging system design. Finally, various case studies at different power levels are presented to get more insights into practical design.

Technology for electric vehicles (EVs) is a developing subject that offers numerous advantages, such as reduced operating costs. Since the goal of EVs has always been to have long-lasting batteries, any new hardware might drastically diminish battery life. Errors are common among human beings. Because of that, accidents and fatalities may occur due to drivers’ different behaviors such as sports style and moderation. To advance driver safety, security, and comfort, Advanced Driver Assistance Systems (ADAS) must be personalized. Modern cars have ADAS that relieves the driver of some of the tasks they perform while driving. As a part of this research, a driver identification system based on a deep driver classification model (deep neural network as DNN) with feature reduction techniques (random forest as RF and principal component analysis as PCA) is implemented to help automate and aid in crucial jobs such as the brake system in an efficient manner. Using task models, we simulate a low-cost driver assisted scheme in real time, where various scenarios are explored and the schedulability of tasks is established before implementing them in EV. The new driver assistance scheme has several advantages over the existing options. It lowers the risk of an accident and ensures driver safety. The proposed model (RF-DNN) achieved 97.05% of accuracy and the PCA-DNN model achieved 95.55% of accuracy, whereas the artificial neural network as ANN with PCA and RF achieved nearly 92% of accuracy.

Underwater image processing always a challenging problem in oceanic engineering applications. Images captured in underwater are commonly suffers due to color distortion, detail blur, bluish or greenish tone, and low contrast to light scattering and absorption in the water medium. The image visibility is affected drastically during capturing caused by the degradation of light absorption and scattering effect. Hence, the effective Underwater Image Enhancement(UIE) and restoration techniques are primarily required for the underwater ecological study applications. Various UIE techniques are studied for different data sets, and applications. However, the selection of suitable method for particular applications among available techniques is still a challenging task. In this paper, an overview of recent UIE and restoration techniques and classification methods are elaborated with data sets and applications. The UIE techniques are grouped under various category such as spatial domain, transform domain, color constancy based method, retinex based approach. Similarly, the image restoration techniques are grouped under underwater optical imaging technique, polarization based approach, prior knowledge and convolutional neural networks. Finally, we review the research process of the underwater image enhancement and restoration with the essential background of the water images and recognize challenges.

The heliostat field layout in a central receiver solar thermal power plant has significant optical losses that can ultimately affect the overall output power of the plant. In this paper, an optimized heliostat field layout based on annual efficiency and power of 50 MW for the local coordinates of Quetta, Pakistan, is proposed. The performance of two different heliostat field layouts such as radial staggered and Fermat's spiral distribution are evaluated and different design points in a year are considered for the analysis. The field layouts are then optimized using a rejection sampling based Genetic Algorithm (GA). It considers the output power and mean overall efficiency for vernal equinox, summer solstice, autumnal equinox, and winter solstice as objective functions. The GA optimizes the heliostat field parameters, namely, security distance (DS), tower height (TH), heliostat width to length ratio (WR), and the length of heliostats (LH). The study system was developed in MATLAB for validation. It was observed that for the radial staggered layout, the number of heliostats decreased by 364 and the efficiency was improved by 8.52 % using GA optimization relative to unoptimized results field layout. The annual efficiency for Fermat's spiral configuration was improved by 14.62 % and correspondingly, the number of heliostats decreased by 434.

Renewable energy sources like sun and wind are intermittent, hence a hybrid system incorporating them is necessary. However, certain systems are more cost-effective and efficient than others, and they are not only more expensive but also far more harmful to the environment. To make up for the energy shortage in unconnected remote regions and urban areas with linked networks, renewable energies offer an alternative. This effort is focused on eliminating both load shedding and the pollution caused by conventional power plants that burn fossil fuels. In order to improve the interconnected Northern Cameroon grid, researchers looked into the possibility of using the permanently accessible sun and wind at the Waibé-Lokoro-Kalfou location in Cameroon. For the hot and humid climate of Waibé-Lokoro, Cameroon, based on four distributed generations, four combinations were established in the scenario. The goal was to maximize the net present value while minimising the energy expense. Electricity costs were found to drop from USD 0.097/kWh to USD 0.085/kWh under the PV-Wind-Grid-Battery scenario, saving a total of USD 0.54 million in net present cost. The particle swarm optimization method (PSO), genetic algorithmic algorithm (GA), cuckoo search approaches (CSA), as well as whale optimization algorithm (WOA) were utilized to calculate power losses as well as system size allocation. PSO was the only algorithm to converge quickly. The level of distortion caused by harmonics is measured experimentally to verify that power grid connectivity regulations are being followed. The standards for the IEEE 33-bus as well as IEEE 69-bus tests provide more precise voltage profiles for use in loss evaluation. Graphical Abstract