Journal of Solar Energy Research
Volume:7 Issue: 1, Winter 2022

In this study, pure phase nanostructured strontium-doped lanthanum manganite, La0.75Sr0.25MnO3 (LSM), with a hexagonal structure was synthesized by sonochemical method. Then, XRD and SEM estimated the size of the LSM nanopowders. The results are exhibited that products synthesized in this method are compatible with particle size and morphology. Magnetic measurement was done by vibrating sample measurement (VSM) on LSM nanoparticles at room temperature. According to the results obtained from VSM displayed the saturation magnetization of LSM nanoparticles exhibited a maximum of 24.25 emu/g at room temperature. Then, the influence of LSM nanoparticle as an additive on the film morphology of CH3NH3PbI3 and the performance of perovskite solar cells was examined. We explore by using 5wt % of additive can increase the short current density (Jsc) from 14.45±0.55 to 18.29±0.38 mA/cm2 (~ 26.5 % enhancement) and power-conversion efficiency (PCE) from 8.33±0.40 to 12.41±0.35 (~ 49 % enhancement). Moreover, the morphology, and band gap of the new perovskite layer was improved.

The subject of this article is about the lifetime of solar devices consisting of number (n) of tubes. The solar energy devices, when they reach an aging stage, the tubes start to fail, the maintenance costs increase, and the production of the device decreases.The costs of solar energy device maintenance companies increase as the device gets old. Therefore, maintenance companies are looking for the age to replace the device with a new device. In this article, we searched for the best age to replace device (in aging stage) with a new device.By relying on strategy of balance the costs of tubes failure in unexpected time, we have determined the optimum time for preventive replacement of solar energy device. Then we studied the factors that influence the optimum time for preventive replacement of solar energy device.

With advent of the modern Hybrid Renewable Energy System (HRES), the application of different energy storage systems has increasingly expanded. When the solar radiation or wind speed has low values, the energy storage system (ESS) injects the required energy to supply the load demand, continuously. Due to large numbers of equipment and different control loops in the HRES, effective contribution of ESS needs an efficient control approach to coordinate the ESS with other equipment within HRES. To fulfill this gap, a Proportional Integral (PI)-based control synthesis approach is presented for the tuning of the PI controllers. In the proposed method, all PI controllers for different types of ESS are designed based on root-locus trajectory, damping coefficient of dominant poles, and coordination among different equipment. Finally, comparison among different types of ESS based on presented control approach is performed. Results show that the presented control technique has adequate capability to damp the frequency deviations against multiple disturbances and parameter variations.

Because of the rise in electricity consumption, renewable energy sources such as the solar and wind are increasingly being used to generate electricity. The integration of renewable energy sources into the grid is critical to energy utilization. The major goal of the new proposed structures is to achieve high output voltage while using fewer power electronic elements such as switches, diodes, and DC input voltage sources, unlike conventional topologies. In addition to lowering costs, size, and complexity, reducing the number of switches and DC voltage sources improves inverter performance. This paper presents a general multilevel inverter based on full-bridge cells. Two specific cases of proposed topology are investigated in detail. The proposed structures have the advantage of reducing the power electronic elements and the switching complexity. It is also possible to configure asymmetric sources to achieve maximum output levels. The first special case is a synthesis with seventeen levels of output, four input voltage sources, and nine switches achieved to the Total Harmonic Distortion (THD) of output voltage equal to 5.68% in 100 HZ frequency of switching carriers and THD of output voltage equal to 6.69% for 5000 HZ frequency of switching carriers. The second case involves the synthesis of forty-three levels of output with six input voltage sources and twelve switches achieved to the THD of output voltage equal to 3.49% in 100 HZ frequency of switching carriers and THD of output voltage 3.99% for 5000 HZ frequency of switching carriers. The proposed topologies are switched using a multicarrier pulse width modulation method. When compared to conventional structures, two special cases of this general topology have significantly reduced the number of power electronic switches. Also, a comparison of the proposed topology with the other structures, results show that the proposed structure has optimally reduced the number of power elements.

In this study, the nonlinear autoregressive neural network with exogenous input (NARX) model was employed to predict solar power in different geoclimatic zones of Nigeria using six solar radiation parameters. The solar power was first deduced using the surface direct and diffuse solar radiation data obtained from the archives of the Modern-Era Retrospective Analysis for Research and Application, Version 2, over 20 stations spread across Nigeria. NARX model was then created and trained using Levenberg-Marquardt (LM), Bayesian regularization (BR), scaled conjugate gradient (SCG), and Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithms, and the values were compared to the calculated values of the solar power. The performance of the four algorithms were assessed using standard evaluation metrics. Error analyses showed that all the algorithms had desirable performances with root mean square error (RMSE) values ranging from 0.162 to 0.544 W/m2. Regionally, the NARX-BFGS model had the best performance in the Coastal and Guinea Savanna zones, whereas the NARX-LM and NARX-BR models had the best performances in the Sahel and Derived Savanna zones, respectively. The results of this study will assist solar engineers in calibrating the performance of solar conversion systems for the future planning of sustainable renewable energy policies.

Increasing energy consumption and reducing fossil energy reserves and its environmental consequences can lead to the use of clean and renewable energy sources such as solar energy. With an inappropriate placement of these units, the system losses is increased and voltage profile will be decreased, So the system efficiency will be decreased. Choosing the best placement of these power plants affects the amount of production of energy and its cost, and consequently amount of the emissions of pollutants. The purpose of this study is to find the best place of solar photovoltaic (SPV) plant to increase energy efficiency by reducing losses and improving voltage profiles. It is crucial task due to the stochastic variation of the PV output power which is related to the solar irradiance variations. In this paper, an improved clustering method with a non-iterative flow approach named as holomorphic embedding method (HEM) are used to solve the problem under the uncertainty condition. It is developed on the base of a tip how it possible to reduce the computation time of calculations. Achieving the mentioned goals has been made faster and easier by reducing the considered scenarios and by using the holomorphic load flow algorithm. Obtaining the solution is possible by using the particle swarm optimization (PSO) algorithm. The decision is based on converting the multi-objective function to a single-objective one. These objective functions are considered to have the lowest line loss and the lowest voltage deviation. The proposed approach is able to include a variety of possible scenarios in the problem analysis and it is applied on IEEE 14-bus test system by considering uncertainty of solar irradiance. Best results are obtained from the placement of PV unit in bus number 3 with operation at -0.27 Pf.