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This study describes the industrial use of waste generated from the brewing industry, specifically sludge from a wastewater treatment plant. The processing technique was developed to produce ceramic material with the potential for use as a lightweight aggregate in construction. This waste is usually dumped in landfills, but the current increase in restrictions on dumping and interest in improving the environment make our proposal for gaining value from this sludge a significant contribution. The chemical composition of the raw materials was analyzed (using X-ray fluorescence and elemental analysis) and their thermal behavior evaluated (thermogravimetric analysis and differential thermal analysis). To determine the effect of adding sludge to the aggregate, different compositions were then prepared and tested. To obtain the material's final resistance and cohesion, the dried sample was subjected to a firing process in a kiln. The samples were prepared without special pre-treatment steps, such as milling, and without the addition of expansive additive. The new aggregate has a low bulk density, due to the formation of an internal cellular structure, a porous internal and a partially vitrified external shell. As waste is added, water absorption increases by values of 17-26 %, as does the porosity, resulting in a linear relationship between the pore volume and percentage of sludge added.

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In this study, a method for solving a probabilistic three-phase power flow in radial distribution networks and taking into account the technical constraints of the system is presented. Regulation of voltage is one of the main problems to be taken into account in networks with distributed generation. The present study introduces a probabilistic model to determine the performance of the distribution system. This study considers the random nature of lower heating value of biomass and loads. This study presents a new hybrid technique combining the shuffled frog leaping algorithm with probabilistic three-phase power flow that is solved by Monte Carlo method. Feasible results are achieved in a few iterations. The results show that the proposed technique can be applied to keep the voltages within the limits specified at each node of a distribution network with biomass power plants. The outcomes are attained using the unbalanced distribution system IEEE-13 node and connecting biomass power plants at some nodes. This study shows that the power losses and voltage unbalance are reduced as a result of the inclusion of distributed generation.