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Optimal planning and design of microgrids are priorities in the electrification of off-grid areas. Indeed, in one of the Sustainable Development Goals (SDG 7), the UN recommends universal access to electricity for all at the lowest cost. Several optimization methods with different strategies have been proposed in the literature as ways to achieve this goal. This paper proposes a microgrid installation and planning model based on a combination of several techniques. The programming language Python 3.10 was used in conjunction with machine learning techniques such as unsupervised learning based on K-means clustering and deterministic optimization methods based on mixed linear programming. These methods were complemented by the open-source spatial method for optimal electrification planning: onsset. Four levels of study were carried out. The first level consisted of simulating the model obtained with a cluster, which is considered based on the elbow and k-means clustering method as a case study. The second level involved sizing the microgrid with a capacity of 40 kW and optimizing all the resources available on site. The example of the different resources in the Togo case was considered. At the third level, the work consisted of proposing an optimal connection model for the microgrid based on voltage stability constraints and considering, above all, the capacity limit of the source substation. Finally, the fourth level involved a planning study of electrification strategies based mainly on microgrids according to the study scenario. The results of the first level of study enabled us to obtain an optimal location for the centroid of the cluster under consideration, according to the different load positions of this cluster. Then, the results of the second level of study were used to highlight the optimal resources obtained and proposed by the optimization model formulated based on the various technology costs, such as investment, maintenance, and operating costs, which were based on the technical limits of the various technologies. In these results, solar systems account for 80% of the maximum load considered, compared to 7.5% for wind systems and 12.5% for battery systems. Next, an optimal microgrid connection model was proposed based on the constraints of a voltage stability limit estimated to be 10% of the maximum voltage drop. The results obtained for the third level of study enabled us to present selective results for load nodes in relation to the source station node. Finally, the last results made it possible to plan electrification using different network technologies and systems in the short and long term. The case study of Togo was taken into account. The various results obtained from the different techniques provide the necessary leads for a feasibility study for optimal electrification of off-grid areas using microgrid systems. [ABSTRACT FROM AUTHOR]

The aim of this work is to study the effect of barium (Ba) doping on the optical, morphological and structural properties of ZnO nanoparticles. Undoped and Ba-doped ZnO have been successfully synthesized via sonochemical method using zinc nitrate, hexamethylenetetramine (HMT) and barium chloride as starting materials. The structural characterization by XRD and FTIR shows that ZnO nanoparticles are polycrystalline with a standard hexagonal ZnO wurtzite crystal structure. Decrease in lattice parameters from diffraction data shows the presence of Ba in the ZnO crystal lattice. The morphology of the ZnO nanoparticles has been determined by scanning electron microscopy (SEM). Incorporation of Ba was confirmed from the elemental analysis using EDX. Optical analysis depicted that all samples exhibit an average optical transparency over 80%, in the visible range. Room-temperature photoluminescence (PL) spectra detected a strong ultraviolet emission at 330 nm and two weak emission bands were observed near 417 and 560 nm. Raman spectroscopy analysis of Ba-doped samples reveals the successful doping of Ba ions in the host ZnO. [ABSTRACT FROM AUTHOR]

Undoped and Ba-doped ZnO nanoparticles were successfully synthesized using microwave hydrothermal method. The influence of Barium concentration on physical and optical properties of ZnO nanoparticles was investigated. X-Ray Diffraction (XRD) analysis revealed that the synthesized ZnO nanoparticles are polycrystalline with hexagonal wurtzite crystal structure and their average crystallite sizes are found to vary from 20 to 21.5 nm in diameter. The SEM images showed that surface morphology of the samples was influenced by the presence of Ba impurities. Ultraviolet and green emission bands around 415 and 603 nm, respectively were observed in photoluminescence spectra for all samples. The FTIR spectra indicated the presence of the distinct characteristic absorption peak at 489 cm−1 for Zn-O stretching modes. Raman spectra exhibited the presence of an intense peak around 437 cm−1 followed by a peak around 586 cm−1 in the higher wave number region. [ABSTRACT FROM AUTHOR]