Quo Vadis Solar Energy Research?

Bibliometric Studies on Renewable Energy—Poland Compared to Other EU Countries

The necessity to use renewable energy sources (RES), especially in EU countries, is becoming more and more urgent in the face of environmental degradation. It is reflected not only in technological solutions for obtaining energy from renewable sources, but also in scientific research supporting RES technology development. There are an increasing number of papers on renewable energy. The aim of the study was to compare research areas concerning renewable energy in Poland and other EU countries by analyzing scientific works. A selected collection of publications available in the Scopus scientific databases was selected as the subject of the study. After cleaning the data and elaborating the thesaurus, the analysis of the article content was conducted applying text processing methods. Conceptual maps of keywords and keyword co-occurrences were created, which enables arranging and classifying knowledge from the subject area. Research hotspots and the directions of science development in the field of renewable energy were identified. The computer program VOSviewer was used in the investigation. Lorenz curves and Gini coefficients were used to identify quite a strong concentration of RES articles in leading journals on the publication market.

Numerical Modelling Analysis for Carrier Concentration Level Optimization of CdTe Heterojunction Thin Film–Based Solar Cell with Different Non–Toxic Metal Chalcogenide Buffer Layers Replacements: Using SCAPS–1D Software

Cadmium telluride (CdTe), a metallic dichalcogenide material, was utilized as an absorber layer for thin film–based solar cells with appropriate configurations and the SCAPS–1D structures program was used to evaluate the results. In both known and developing thin film photovoltaic systems, a CdS thin–film buffer layer is frequently employed as a traditional n–type heterojunction partner. In this study, numerical simulation was used to determine a suitable non–toxic material for the buffer layer that can be used instead of CdS, among various types of buffer layers (ZnSe, ZnO, ZnS and In2S3) and carrier concentrations for the absorber layer (NA) and buffer layer (ND) were varied to determine the optimal simulation parameters. Carrier concentrations (NA from 2 × 1012 cm−3 to 2 × 1017 cm−3 and ND from 1 × 1016 cm−3 to 1 × 1022 cm−3) differed. The results showed that the use of CdS as a buffer–layer–based CdTe absorber layer for solar cell had the highest efficiency (%) of 17.43%. Furthermore, high conversion efficiencies of 17.42% and 16.27% were for the ZnSe and ZnO-based buffer layers, respectively. As a result, ZnO and ZnSe are potential candidates for replacing the CdS buffer layer in thin–film solar cells. Here, the absorber (CdTe) and buffer (ZnSe) layers were chosen to improve the efficiency by finding the optimal density of the carrier concentration (acceptor and donor). The simulation findings above provide helpful recommendations for fabricating high–efficiency metal oxide–based solar cells in the lab.

Optimal Integration of Photovoltaic Sources in Distribution Networks for Daily Energy Losses Minimization Using the Vortex Search Algorithm

This paper deals with the optimal siting and sizing problem of photovoltaic (PV) generators in electrical distribution networks considering daily load and generation profiles. It proposes the discrete-continuous version of the vortex search algorithm (DCVSA) to locate and size the PV sources where the discrete part of the codification defines the nodes. Renewable generators are installed in these nodes, and the continuous section determines their optimal sizes. In addition, through the successive approximation power flow method, the objective function of the optimization model is obtained. This objective function is related to the minimization of the daily energy losses. This method allows determining the power losses in each period for each renewable generation input provided by the DCVSA (i.e., location and sizing of the PV sources). Numerical validations in the IEEE 33- and IEEE 69-bus systems demonstrate that: (i) the proposed DCVSA finds the optimal global solution for both test feeders when the location and size of the PV generators are explored, considering the peak load scenario. (ii) In the case of the daily operative scenario, the total reduction of energy losses for both test feeders are 23.3643% and 24.3863%, respectively; and (iii) the DCVSA presents a better numerical performance regarding the objective function value when compared with the BONMIN solver in the GAMS software, which demonstrates the effectiveness and robustness of the proposed master-slave optimization algorithm.

Hybrid Floating Solar Plant Designs: A Review

The world’s demand for electricity will double by 2050. Despite its high potential as an eco-friendly technology for generating electricity, solar energy only covers a small percentage of the global demand. One of the challenges is associated with the sustainable use of land resources. Floating PV (FPV) plants on water bodies such as a dam, reservoir, canal, etc. are being increasingly developed worldwide as an alternative choice. In this background, the purpose of this research is to provide an outline of the hybrid floating solar system, which can be used to generate renewable energy. The hybrid technologies discussed include: FPV + hydro systems, FPV + pumped hydro, FPV + wave energy converter, FPV + solar tree, FPV + tracking, FPV + conventional power, FPV + hydrogen. The review also summarizes the key benefits and constraints of floating solar PV (FPV) in hybrid operation. Among the various hybrid FPV technologies, with solar input and hydro energy were among the most promising methods that could be potentially used for efficient power generation. The valuable concepts presented in this work provide a better understanding and may ignite sustainable hybrid floating installations for socio-economic growth with less environmental impact.

Short-Term Solar Power Forecasting Using Genetic Algorithms: An Application Using South African Data

Renewable energy forecasts are critical to renewable energy grids and backup plans, operational plans, and short-term power purchases. This paper focused on short-term forecasting of high-frequency global horizontal irradiance data from one of South Africa’s radiometric stations. The aim of the study was to compare the predictive performance of the genetic algorithm and recurrent neural network models with the K-nearest neighbour model, which was used as the benchmark model. Empirical results from the study showed that the genetic algorithm model has the best conditional predictive ability compared to the other two models, making this study a useful tool for decision-makers and system operators in power utility companies. To the best of our knowledge this is the first study which compares the genetic algorithm, the K-nearest neighbour method, and recurrent neural networks in short-term forecasting of global horizontal irradiance data from South Africa.