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Shading the greenhouses is necessary in summer to reduce the solar radiation load. This however generates a considerable amount of thermal radiation heat load that needs to be removed via cooling systems. This study aimed to evaluate the effect of different shading configurations on the solar and thermal radiation in a greenhouse. Nets at four different locations were employed to shade the roof and side-walls of a polycarbonate, mechanically ventilated greenhouse. The spectral radiative properties of all these plastic materials were measured in short and long wave spectrum bands. The net solar and thermal radiations and air temperature were measured outside and inside two identical shaded and unshaded greenhouses. The results showed that external roof-shading is desirable, as it reduced the generated thermal radiation in the greenhouse by 21% and 15% during the day and night time, respectively and reduced the greenhouse air temperature during the day. The internal shading (roof and side walls) is undesirable, since it drastically increased the generated thermal radiation in the greenhouse by 147% and strongly increased the greenhouse air temperature during the day. Shading the side-walls is not recommended because it significantly reduces the transmitted solar radiation in the morning and afternoon (when the outside irradiance is low) and is useless at around noon when the outside irradiance is extremely high.

Deployment of photovoltaic (PV) systems has recently been encouraged for large-scale and small-scale businesses in order to meet the global green energy targets. However, one of the most significant hurdles that limits the spread of PV applications is the dust accumulated on the PV panels’ surfaces, especially in desert regions. Numerous studies sought the use of cameras, sensors, power datasets, and other detection elements to detect the dust on PV panels; however, these methods pose more maintenance, accuracy, and economic challenges. Therefore, this paper proposes an intelligent system to detect the dust level on the PV panels to optimally operate the attached dust cleaning units (DCUs). Unlike previous strategies, this study utilizes the expanded knowledge and collected data for solar irradiation and PV-generated power, along with the forecasted ambient temperature. An expert artificial intelligence (AI) computational system, adopted with the MATLAB platform, is utilized for a high level of data prediction and processing. The AI was used in this study in order to estimate the unprovided information, emulate the provided measurements, and accommodate more input/output data. The feasibility of the proposed system is investigated using actual field data during all possible weather conditions.

In the event of a fault isolation process, all loads located downstream from the faulted point become out of service, and as a consequence, the power interruption affects a greater portion of the radial distribution system. This paper proposes an optimal Service Restoration (SR) method that entails changing the network topology configuration via optimal tie-switch and section switch combinations. However, when the network topology configuration is performed, it results in increased load currents. As a result, some Protective Devices (PDs) can operate undesirably and some network branches may become unprotected. Therefore, it is essential to consider protection constraints in the SR problem to maintain service continuity during power interruptions. The proposed method aims at optimal SR with minimum out-of-service loads, minimum power loss, and improved voltage profiles and at the same time ensures PDs operate correctly during the normal and overloading conditions. The proposed method was carried out on the Debre Markos distribution networks, using the Teaching Learning Based Optimization (TLBO), Particle Swarm Optimization (PSO), and Differential Evolutionary (DEV) algorithms. The proposed SR was carried out considering and without considering protection constraints. The obtained SR topology was not feasible for SR without considering protection constraints, since some PDs fail to operate properly in normal loading conditions. After executing the proposed SR algorithms by considering protection constraints for a single fault case, the power loss reductions in TLBO, DEV, and PSO were 64.9073%, 45.9073%, and 55.358 %, respectively. The minimum voltage profiles obtained in each proposed TLBO, DEV, and PSO algorithm were 0.96%, 0.95%, and 0.96%, respectively. In each algorithm, except for the branch under fault, all healthy out-of-service branches were restored. When the protection constraints were considered in an optimal SR, load current did not exceed the rating of the fuses. The results show the importance of considering protection constraints during SR to prevent dysfunction of the PDs in the network. Comparative analyses were carried out on each algorithm and TLBO algorithms performed better than PSO and DEV for search functions.

Globally, solar energy has become a major contributor to the rapid adoption of renewable energy. Significant energy savings have resulted from the widespread utilization of solar energy in the industrial, residential, and commercial divisions. This review article comprises research conducted over the past 15 years (2008–2023), utilizing a comprehensive collection of 163 references. Significantly, a considerable focus is directed towards the period from 2020 to 2023, encompassing an extensive investigation into the latest developments in solar panel technology in civil engineering. The article examines the incorporation of solar panels into building designs and addresses installation-related structural considerations. In addition, the present review examines the applications of solar panels in terms of innovative infrastructure development applications of solar panels, such as photovoltaic parking lot canopies and photovoltaic noise barriers, which contribute to improved energy efficiency. It also emphasizes their role in water management systems, including water treatment plants, water pumping and irrigation systems, energy-efficient solar desalination technologies, and promoting sustainable water practices. In addition, this study examines how solar panels have been incorporated into urban planning, including smart cities and public parks, thereby transforming urban landscapes into greener alternatives. This study also examined the use of solar panels in building materials, such as façade systems and solar-powered building envelope solutions, demonstrating their versatility in the construction industry. This review explores the diverse applications of solar energy, which promotes sustainable practices in various industries. Owing to the ongoing research, solar energy holds great promise for a greener and cleaner future.

This research focuses on improving the photoelectrochemical performance of binary heterostructure Ag2S/ZnO NRs/ITO by manipulating synthesis conditions, particularly the concentrations of sliver nitrate AgNO3 and thiourea CS(NH2)2. The photoelectrochemical performance of Ag2S/ZnO nanorods on indium tin oxide (ITO) nanocomposite was compared to pristine ZnO NRs/ITO photoanode. The hydrothermal technique, an eco-friendly, low-cost method, was used to successfully produce Ag2S/ZnO NRs at different concentrations of AgNO3 and CS(NH2)2. The obtained thin films were characterized using field emission scanning electron microscopy (FESEM), energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), ultraviolet-visible spectroscopy (UV-vis), and photoelectrochemical studies (PECs). We observed that there was an enhancement in absorbance in the visible region and effective photoelectron transfer between the Ag2S/ZnO NRs/ITO photoelectrode and the electrolyte Red-Ox when illuminated with 100 mW cm−2. Increasing the concentration of AgNO3 caused a remarkable decrease in the optical bandgap energy (Eg) values. However, we noticed that there was an unstable trend in Eg when the concentration of CS(NH2)2 was adjusted. The photoelectrochemical studies revealed that at a bias of 1.0 V, and 0.005 M of AgNO3 and 0.03 M of CS(NH2)2, the maximum photocurrent of the Ag2S/ZnO NRs/ITO photoanode was 3.97 mA/cm2, which is almost 11 times that of plain ZnO nanorods. Based on the outcomes of this investigating, the Ag2S/ZnO NRs/ITO photoanode is proposed as a viable alternative photoanode in photoelectrochemical applications.

Wave Energy Converters (WECs) need to be deployed in large numbers in an array layout in order to have a significant power production. Each WEC has an impact on the incoming wave field, by diffracting, reflecting and radiating waves. Simulating the wave transformations within and around a WEC array is complex; it is difficult, or in some cases impossible, to simulate both these near-field and far-field wake effects using a single numerical model, in a time- and cost-efficient way in terms of computational time and effort. Within this research, a generic coupling methodology is developed to model both near-field and far-field wake effects caused by floating (e.g., WECs, platforms) or fixed offshore structures. The methodology is based on the coupling of a wave-structure interaction solver (Nemoh) and a wave propagation model. In this paper, this methodology is applied to two wave propagation models (OceanWave3D and MILDwave), which are compared to each other in a wide spectrum of tests. Additionally, the Nemoh-OceanWave3D model is validated by comparing it to experimental wave basin data. The methodology proves to be a reliable instrument to model wake effects of WEC arrays; results demonstrate a high degree of agreement between the numerical simulations with relative errors lower than 5 % and to a lesser extent for the experimental data, where errors range from 4 % to 17 % .

The rapid increase in the penetration of photovoltaic (PV) power plants results in an increased risk of grid failure, primarily due to the intermittent nature of the plant. To overcome this problem, the flexible power point tracking (FPPT) algorithm has been proposed in the literature over the maximum power point tracking (MPPT) algorithm. These algorithms regulate the PV power to a certain value instead of continuously monitoring the maximum power point (MPP). The proposed work carries out a detailed comparative study of various constant power generation (CPG) control strategies. The control strategies are categorized in terms of current-, voltage-, and power-based tracking capabilities. The comparative analysis of various reported CPG/FPPT techniques was carried out. This analysis was based on some key performance indices, such as the type of control strategy, irradiance pattern, variation in G, region of operation, speed of tracking, steady-state power oscillations, drift severity scenario, partial shading scenario, implementation complexity, stability, fast dynamic response, robustness, reactive power, cost, and tracking efficiency. Among existing FPPT algorithms, model-based control has a superior performance in terms of tracking speed and low steady-state power oscillations, with a maximum tracking efficiency of 98.57%.

The present work aims at optimizing the geometry of curved trapezoidal winglets to enhance heat transfer rates (expressed as Colburn factor, j) and minimize pressure losses (expressed as friction factor, f). A fin-and-tube heat exchanger was analyzed with winglets mounted on the alternate tube and on either side of the fins. Multi-objective optimization was performed using the genetic algorithm (GA) to maximize j and minimize f. Two surrogate models, viz. response surface methodology (RSM) and artificial neural network (ANN), were considered as inputs to GA. To reduce the number of runs, a sensitivity analysis was first performed to select the most influential geometrical parameters for optimization. The values of j and f in the design of the experiments table were computed using CFD. The Pareto front points elucidated a significant improvement compared with the reference model along with a broad choice for the designers, not only for the design condition but also for the off-design inlet condition.