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Building a highly accurate model for solar cells and photovoltaic (PV) modules based on experimental data is becoming increasingly important for the simulation, evaluation, control, and optimization of PV systems. Powerful, accurate, and more robust optimization algorithms are needed to solve this problem. In this study, a new optimization approach based on the Levenberg-Marquardt algorithm (ImLM) is proposed to estimate the parameters of PV cells and modules and simulate their electrical behavior under all environmental conditions efficiently and accurately. To avoid the premature convergence of the Levenberg-Marquardt algorithm and the long computation time caused by a bad choice of initial values, we propose a new approach. This is a new reduced form leading to a nonlinear relationship of the series resistance and thus allowing to calculate the optimal initial values of the model parameters. Comparisons with other published methods show that the proposed approach gives not only a more accurate final solution but also a fast convergence speed and a better stability. Furthermore, tests on three PV modules of different technologies (multi-crystalline, thin film, and monocrystalline) reveal that the proposed algorithm performs well at different irradiations and temperatures. These results confirm that the ImLM approach is a valuable tool and can be an effective and efficient alternative for extracting PV model parameters and simulating PV module behavior under different conditions. [ABSTRACT FROM AUTHOR]

Urban areas’ energy consumption accounts for almost three fourths the global energy use with 70% of the related emissions. Therefore, cities play a meaningful role in decoupling economic growth from greenhouse gases (GHGs) emissions. This study presents a system dynamic approach to model the energy efficiency impact on the Togolese capital city’s residential electricity consumption and carbon dioxide emissions reduction. The time spans from 2000 to 2050. An assessment of household appliances, such as lighting, refrigeration, cooling, and ventilation, was conducted along with monitoring electricity consumption of used and newly bought televisions, refrigerators, and freezers. Then, using Stella software, Lomé’s residential electricity consumption model was built based on the following variables: (1) population, (2) the number of existing households with access to electricity, (3) new homes having access to electricity, and (4) per capita electricity consumption. The model was calibrated and validated using data for the years 2000 to 2016. Afterward, this previous knowledge was used to evaluate three efficient energy policies: 1) business-as-usual scenario, 2) new policies scenario, and 3) sensitivity scenario. Lomé’s households present a predominantly low efficient appliances percentage. Therefore, the study found that substituting inefficient electric appliances with new and efficient models can lead Togo to substantial energy savings and reduce CO2 emissions of about 680 GWh and 350 kt in the horizon of 2050, respectively. Additionally, the findings of this study could stimulate policymakers to audit other sectors to implement related energy efficiency policies and/or set up corresponding energy management strategies in neighboring emerging countries. [ABSTRACT FROM AUTHOR]

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]

Abstract: Sprayed ZnO films were grown on glass substrate at 400°C using zinc chloride as precursor with different molar concentrations varying from 0.05 to 0.2M. X-ray diffraction patterns reveal that ZnO films are polycrystalline with hexagonal wurtzite structure with preferred orientation in (002) plane. Optical measurements show that transmittance reaches a maximum value of 95% in the visible region for ZnO films prepared from precursor with 0.05M concentration. The films obtained from the precursor with 0.1M concentration have the highest electrical conductivity and photocurrent values. [Copyright &y& Elsevier]

CuInS 2 absorber thin films were prepared by spray pyrolysis deposition at different substrate temperatures (250 °C, 300 °C and 350 °C) using an aqueous solution of CuCl 2 , InCl 3 and SC(NH 2 ) 2 at a precursor molar ratio of Cu:In:S=1:1.25:4.5. The effect of the substrate׳s temperature on the structural, morphological, optical and electrical properties of CuInS 2 thin films was investigated. The X-ray diffraction patterns showed that CuInS 2 has a tetragonal structure. The results show that the films deposited at 300 °C have improved electrical conduction and photocurrent values. When increasing the substrate׳s temperature the absorbance decreases while the band gap energy increases, as a combined effect of crystallinity, morphology and deviation from stoichiometry. [ABSTRACT FROM AUTHOR]

Abstract: Original ZnO/Cu/Ag/MoO3 multilayer structures were deposited under vacuum. The optical transmittance spectrum of these structures is significantly broadened by using a double layer as metal interlayer. While the thickness of Ag was 6nm, that of Cu was used as parameter. The highest averaged transmittance, 88% between 400 and 700nm is obtained with the structure ZnO (20nm)/ Cu (3nm)/Ag (6nm)/ MoO3. However, a better factor of merit is achieved, Φ M=16×10−3, when the Cu thickness is 4nm, making that these innovative ZnO/Cu/Ag/MoO3 structures are very promising for use as substitute to ITO electrodes. [Copyright &y& Elsevier]