This paper deals with a comparative study of AC and DC breakdown voltages of based mineral oil mixtures with natural and synthetic esters mainly used in high voltage power transformers. The goal was to analyze the performances of oil mixtures from the dielectric withstand point of view and to predict the behavior of transformers originally filled with mineral oil and re-filled with synthetic or natural ester oils when emptied for maintenance. The study concerns mixtures based on 20%, 50%, and 80% of natural and synthetic ester oils. AC breakdown voltages were measured using a sphere-sphere electrode system according to IEC 60156 specifications; the same specification was adopted for DC measurements since there is no standard specifications for this voltage waveform. A statistical analysis of the mean values, standard deviations, and histograms of breakdown voltage data was carried out. The Normal and Weibull distribution functions were used to analyze the experimental data and the best function that the data followed was used to estimate the breakdown voltage with risk of 1%, 10%, and 50% probability. It was shown that whatever the applied voltage waveforms, ester oils always have a significantly higher breakdown voltage than mineral oil. The addition of only 20% of natural or synthetic ester oil was sufficient to considerably increase the breakdown voltage of mineral oil. The dielectric strength of such a mixture is much higher than that of mineral oil alone and can reach that of ester oils. From the point of view of dielectric strength, the mixtures constitute an option for improving the performance of mineral oil. Thus, re-filling of transformers containing up to 20% mineral oil residues with ester oils, does not present any problem; it is even advantageous when considering only the breakdown voltage. Under AC, the mixtures with natural ester always follow the behavior of vegetable oil alone. With the exception of the 20% mixture of natural ester in DC, the breakdown voltage values of all the tested mixtures were in accordance with the normal distribution, which made it possible to define the breakdown voltages for the risk levels of 1%, 10%, and 50% of probability.

The problem of voltage collapse in power systems due to increased loads can be solved by adding renewable energy sources like wind and photovoltaic (PV) to some bus-bars. This option can reduce the cost of the generated energy and increase the system efficiency and reliability. In this paper, a modified smart technique using particle swarm optimization (PSO) has been introduced to select the hourly optimal load flow with renewable distributed generation (DG) integration under different operating conditions in the 30-bus IEEE system. Solar PV and wind power plants have been introduced to selected buses to evaluate theirs benefits as DG. Different solar radiation and wind speeds for the Dammam site in Saudi Arabia have been used as an example to study the feasibility of renewable energy integration and its effect on power system operation. Sensitivity analysis to the load and the other input data has been carried out to predict the sensitivity of the results to any deviation in the input data of the system. The obtained results from the proposed system prove that using of renewable energy sources as a DG reduces the generation and operation cost of the overall power system.

This paper deals with the effects of conductive and insulating nanoparticles at various sizes and concentrations on the AC dielectric strength of natural ester oil namely MIDEL 1204. The investigated nanoparticles are conductive (Fe3O4) and two insulating (Al2O3 and SiO2). The measurements of breakdown voltages are achieved according to IEC 60156 standard. Experimental findings show that the investigated nanoparticles have not a significant influence on insulation performances of natural ester oil as it is the case with mineral oils and synthetic esters. The best improvement does not exceed 7%; it is obtained with Fe3O4 (50nm) at a concentration 0.4 g/L and Al2O3 (13nm) at a concentration of 0.05 g/L. In some cases, the addition of nanoparticles even reduces the dielectric strength of natural ester oil. Indeed, a decrease of 15% is observed with SiO2 at a concentration of 0.05 g/L. Statistical analysis of experimental results is performed using two probabilistic functions, namely Normal and Weibull laws. It is shown that the breakdown voltage values of the investigated nano-liquids generally obey the normal and Weibull distributions. In addition, the breakdown voltage with risk of 1% and 50% probability are deduced.

This paper deals with an experimental study of the influence of conductive (Fe₃O₄) and insulating (Al₂O₃) nanoparticles at various concentrations on the dielectric strength of transformer mineral oil. The method of preparation and characterization of these nanofluids (NFs) through the measurements of zeta potential, the real and imaginary parts of dielectric permittivity as well as the concentration and size of nanoparticles using scanning electron microscope images of nanoparticles powders and energy dispersive x-ray spectroscopy analysis are presented. Experimental findings reveal that these two types of nanoparticles materials significantly improve AC breakdown voltage and the magnitude of this enhancement depends on the nanoparticle concentration, and the size and nature (material) of nanoparticles. For a given type of nanoparticle, the effect is more marked with the smallest nanoparticles. The conductive nanoparticles offer higher enhancement of dielectric strength compared with insulating nanoparticle based nanofluids. With Fe₃O₄, the breakdown voltage (BDV) can exceed twice that of mineral oil and it increases by more than 76% with Al₂O₃. The physicochemical mechanisms implicated in this improvement are discussed.

To avert climate change, there has been a rise in the usage of green energy sources that are also beneficial to the environment. To generate sustainable energy in a financially and technically efficient manner, our research attempts to close the gaps. The potential of green sources like photovoltaic (PV) and biomass for a rural community southwest of Sohag Al Gadida City, Sohag, Egypt, is examined in this research considering its techno-economic (TE) and eco-friendly feasibility. The HOMER Pro v3.14 package is used as a scaling and optimization instrument, to calculate the price of the PV/biomass setup and the size and characteristics of its parts. This is to estimate the corresponding electrical production and reduce the total annual cost for the customer. The suggested system structure is validated through the presentation of simulation outcomes and evaluations utilizing MATLAB/SIMULINK R2022a. In addition, a TE-environmental investigation of the optimized PV/biomass structure is performed. The optimum structure is carefully chosen from the best four configurations using the demand predilection by analogy to the perfect technique based on the generation cost, operation cost, energy production, and renewable fraction. The results also indicate that using hybrid PV/biomass is an attractive choice with the initial capital cost (ICC: USD 8.144), net present cost (NPC: USD 11,026), a low cost of energy (LCOE: 0.184 USD/kWh), and the high renewable fraction (RF: 99.9%) of the system. The annual CO₂ emission performance of a PV/biomass system is much better than that of the grid alone and PV/diesel. This method might be applied in rural areas in other developing countries.

Date fruit drying is a process that consumes a significant amount of energy due to the long duration required for drying. To better understand how moisture flows through the fruit during drying and to speed up this process, drying studies must be conducted in conjunction with mathematical modeling, energy analysis, and environmental economic analysis. In this study, twelve thin-layer mathematical models were designed utilizing experimental data for three different date fruit varieties (Sakkoti, Malkabii, and Gondaila) and two solar drying systems (automated solar dryer and open-air dryer). These models were then validated using statistical analysis. The drying period for the date fruit varieties varied between 9 and 10 days for the automated solar dryer and 14 to 15 days for open-air drying. The moisture diffusivity coefficient values, determined using Fick’s second law of diffusion model, ranged from 7.14 × 10⁻¹² m²/s to 2.17 × 10⁻¹¹ m²/s. Among the twelve thin-layer mathematical models, we chose the best thin drying model based on a higher R² and lower χ² and RMSE. The Two-term and Modified Page III models delivered the best moisture ratio projections for date fruit dried in an open-air dryer. For date fruit dried in an automated solar dryer, the Two-term Exponential, Newton (Lewis), Approximation diffusion or Diffusion Method, and Two-term Exponential modeling provided the best moisture ratio projections. The energy and environmental study found that the particular amount of energy used varied from 17.936 to 22.746 kWh/kg, the energy payback time was 7.54 to 7.71 years, and the net CO₂ mitigation throughout the lifespan ranged from 8.55 to 8.80 tons. Furthermore, economic research showed that the automated solar dryer’s payback period would be 2.476 years.