Waste facilities siting is one of the complex problems encountered by decision makers of waste management in urban developing areas. Waste to Energy (WtE) facilities siting alongside transfer stations involves a Multi-Criteria Decision Analysis (MCDA) and has leveraged waste value chain. However, the process requires to consider the interlinked fields of environment, socio-cultural and economic/technical factors as Geographical Information Systems (GIS) in a context of lack of knowledge and expertise. This study aims to propose a framework of WtE facilities siting through a GIS-based Fuzzy Analytical Hierarchy Process (FAHP) and location-allocation method in Lomé’s case study in Togo. This method was applied with boolean logic and fuzzy overlay operators, to assess the potential sites and optimize their selection through a location-allocation solver considering transfer stations and road networks under ArcGIS. Moreover, WtE technologies were attributed to sites based on the territorial aspect. As result, 30.70% of the study area was excluded and three potential areas with a minimum value of 3.47 km² comprised between 0.81% and 1.01% of the study area, and have been obtained with an acceptable consistency ratio of 0.09. The potential sites are more influenced by slope and residence criteria under economic/technical and socio-cultural factors, with 29.13% and 19.84% of weight respectively. Therefore, through the location-allocation method two optimized sites are obtained and assigned to transfer stations; the first suitable site close to industrial area is appropriate for the gasifier which consequently classified ahead of the anaerobic digester that is suitable for the second suitable site close to agricultural area. As result, prioritizing WtE technologies and site selection should take into account territory aspect, waste sources as well other environmental, socio-cultural and economic/technical factors. This approach has demonstrated its robustness and serves as a stepwise tool for decision makers in WtE facilities siting in developing urban areas.

Undoped and Barium (Ba) doped ZnO thin films were deposited on glass substrates by successive ion layer adsorption and reaction (SILAR) method using zinc acetate, barium chloride and ammonium hydroxide solution. In the present work the effect of Barium doping on structural, optical and morphological properties were investigated. Structural characterization by X-ray diffraction reveals that ZnO films are polycrystalline with wurtzite structure. SEM images showed that Ba doping influenced surface morphology and grain size was found to increase with increase in doping level. Optical analysis showed that all the films had good transmittance in the visible region. The presence of defects into ZnO films was detected through photoluminescence studies.

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.

The exploitation and development of photovoltaic (PV) modules faces several technical challenges, including those related to variability in electrical performance under real conditions, such as temperature fluctuations, irradiance variability, and dust accumulation. One solution for evaluating and controlling these performances is to conduct electrical characterization under natural conditions. Many characterization techniques have been developed and proposed in the literature, with the aim of verifying manufacturer performance guarantees and better understanding the behavior of PV modules in their installation environment, where the climatic parameters, such as solar irradiation and temperature, fluctuate constantly. These techniques are based on recognized standards, including those established by the International Electrotechnical Commission (IEC) and American Society for Testing and Materials (ASTM). They are also based on methods of transposing basic electrical parameters, allowing the prediction of the performance of modules under various environmental conditions. In this work, a classification and a critical analysis of the main methods of electrical characterization were undertaken, highlighting their respective advantages and disadvantages. The experimental protocols used to evaluate the impact of environmental parameters on the performance of PV modules were examined in detail.

A smart and decentralized electrical system, powered by grid-connected renewable energy (RE) with a reliable storage system, has the potential to change the future socio-economic dynamics. Climate change may, however, affect the potential of RE and its related technologies. This study investigated the impact of climate change on photovoltaic cells’ temperature response and energy potential under two CO₂ emission scenarios, RCP2.6 and 8.5, for the near future (2024–2040) and mid-century (2041–2065) in Togo. An integrated Regional Climate Model version 4 (RegCM4) from the CORDEX-CORE initiative datasets has been used as input. The latter platform recorded various weather variables, such as solar irradiance, air temperature, wind speed and direction, and relative humidity. Results showed that PV cells’ temperature would likely rise over all five regions in the country and may trigger a decline in the PV potential under RCP2.6 and 8.5. However, the magnitude of the induced change, caused by the changing climate, depended on two major factors: (1) the PV technology and (2) geographical position. Results also revealed that these dissimilarities were more pronounced under RCP8.5 with the amorphous technology. It was further found that, nationally, the average cell temperature would have risen by 1 °C and 1.82 °C under RCP2.6 and 8.5, in that order, during the 2024–2065 period for a-Si technology. Finally, the PV potential would likely decrease, on average, by 0.23% for RCP2.6 and 0.4% for RCP8.5 for a-Si technology.

Most developing countries' electric power system is stressed by an unprecedented demand growth as well as obstacles that call for urgent actions. Therefore, tackling the present-day power-related challenges and ensure dependable and safe electricity may result in improving living conditions. This research aims to comprehend the primary factors that impede power companies in emerging economies and propose ways of addressing them with a focus on Togolese electricity system as a case study., The methodology utilized to study a complex and dynamic system like electricity sector is an integrated model composed of a survey and review of available literature, an interview with energy experts and the SWOT/PESTLE analysis to perform an in-depth and all-encompassing analysis. The study revealed that the electrification poverty was 39.47 % at countrywide level that requires an additional power of 220.95 MW to that of 2021 to achieve 100 % of electricity access by 2030. Moreover, the system's performance is hindered by a number of internal and external bottlenecks. They include but not limited to limitations in policies and regulations; technical difficulties in the transmission, distribution and off-grid subsystems; insufficient investments; and a lack of incentives and taxes rebates. In light of these findings, a model prioritizing a resilient power system was proposed for transforming the outdated power infrastructure in developing countries laying stress upon energy mix planning, transmission and distribution subsectors innovation and effective regional collaboration.