This paper is focused on the study of fluid-dynamic behavior of mixtures of the sugarcane bagasse particles and quartz sand in a transparent fluidized bed column. The minimum fluidization velocity (V mf ) was determined by different mean particle diameters and different mass fractions in the mixture compositions. The values of V mf increased with amount of biomass in the mixture increased as well as with the size of the biomass particles in the range of 9.5 ! d pb > 0.225 mm. Binary mixtures with diameter ratios biomass/sand 1 had a (V mf ) almost constant as a function of mass fraction of biomass. It is suggested a practical upper limit of biomass fraction in the mixtures less than 5% of the overall bed mass to obtain a good mixing and uniform distribution in the bed. New correlations were developed to predict the values of (V mf ). It was found that the present proposed correlation predicted the (V mf ) for binary mixtures of sugarcane bagasse and sand particles more accurately than other correlations reported in the literature available.

A B S T R A C TThis study refers to an experimental analysis of the fluid-dynamics of particles of sugarcane bagasse in a fluidization column with an internal diameter of 190 mm, which determined the minimum fluidization velocity of the particles with different characteristic diameters (0 < dp < 9.5 mm), using air as fluidization means. The results have shown that the minimum fluidization velocity has a tendency to increase as the diameter of the particle increases. However, in a certain range of diameter (0.88 mm < dp < 9.5 mm), where the particles have a high aspect ratio (length/diameter), it has not been possible to fluidize them. High superficial air velocities have been used, mainly due to the strong trend to interlace and to develop high adhesion forces in this type of particles, as well as the high porosity that is displayed. Based on the experimental results, two new models have been developed in order to determine the minimum fluidization velocity and the complete fluidization velocity of the sugarcane bagasse with diameters that range from 0.075 to 0.445 mm. The comparisons have been made by using correlations from the literature for the determination of the minimum fluidization velocity, and the experimental results have shown that the new suggested correlations finely predict this parameter, with a maximum error range of 6%, respecting the experimental values.

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Iran is one of the most potent energy exporters and fastest‐growing energy consumers in the world. Its large amount of energy exported can directly impact the economy of importer countries. Iran's energy matrix mostly consists of hydrocarbons, while the remaining portion is compounded by a blend of biofuels, hydropower, wind, solar, and other renewable sources. Even though the country has an excellent potential to reach a large amount of renewable power, it is most likely that Iran will deal with a shortage in its electricity segment during the upcoming years. Besides wind and solar energy, bioenergy appears to be a good alternative for enhancing the country's energy matrix and transit Iran's energy consumption pattern from a high‐level usage of hydrocarbons to a more renewable scenario. Therefore, in the present paper, the role of Iran in global energy production is discussed, and its potential for renewable energy generation is described. The review presents a vast set of data related to environmental, infrastructural, economic, and social aspects to clarify the potential and benefits of Iran's transition to a more renewable energy matrix. The investigations revealed the country's extremely favourable conditions to use bioenergy resources as a key solution to avoiding future energy crises, besides improving quality of life. The context can help researchers, power suppliers, and energy consumers know how renewable energies, especially bioenergy, can modify the energy matrix of a country rich in hydrocarbon resources.

The distribution system reconfiguration (DSR) is a complex large-scale optimization problem, which is usually formulated with one or more objective functions and should satisfy multiple sets of linear and non-linear constraints. As the exploration of feasible solutions in large and nonconvex search space of DSR is typically hard, it is important to develop efficient algorithms and methods for finding optimal solutions for DSR problem in reasonably short computational times. In traditional DSR, the configuration of distribution network can be changed by opening and closing sectional and tie switches, where active power losses are minimized, while radial network configuration and supply to all connected loads are both preserved. Accordingly, this paper provides a comprehensive review of a number of existing metaheuristic reconfiguration methods and introduces a novel efficient genetic algorithm (efficient GA) for DSR with loss minimization. In order to demonstrate benefits and effectiveness of the proposed efficient GA for DSR, the paper also provides a detailed comparison of results with an improved genetic algorithm (improved GA) for several test systems and real distribution networks. The obtained simulation results clearly show higher accuracy and improved convergence performance of the proposed efficient GA method, compared to the improved GA and other considered reconfiguration methods.