Characterization of the methanol recovery process at Prio Biocombustíveis S. A.

In a industrial environment, to know the process one is working with is crucial to ensure its good functioning. In the present work, developed at Prio Biocombustíveis S.A. facilities, using process data, collected during the present work, and historical process data, the methanol recovery process was characterized, having started with the characterization of key process streams. Based on the information retrieved from the stream characterization, Aspen Plus® process simulation software was used to replicate the process and perform a sensitivity analysis with the objective of accessing the relative importance of certain key process variables (reflux/feed ratio, reflux temperature, reboiler outlet temperature, methanol, glycerol and water feed compositions). The work proceeded with the application of a set of statistical tools, starting with the Principal Components Analysis (PCA) from which the interactions between process variables and their contribution to the process variability was studied. Next, the Design of Experiments (DoE) was used to acquire experimental data and, with it, create a model for the water amount in the distillate. However, the necessary conditions to perform this method were not met and so it was abandoned. The Multiple Linear Regression method (MLR) was then used with the available data, creating several empiric models for the water at distillate, the one with the highest fit having a R2 equal to 92.93% and AARD equal to 19.44%. Despite the AARD still being relatively high, the model is still adequate to make fast estimates of the distillate’s quality. As for fouling, its presence has been noticed many times during this work. Not being possible to directly measure the fouling, the reboiler inlet steam pressure was used as an indicator of the fouling growth and its growth variation with the amount of Used Cooking Oil incorporated in the whole process. Comparing the steam cost associated to the reboiler’s operation when fouling is low (1.5 bar of steam pressure) and when fouling is high (reboiler’s steam pressure of 3 bar), an increase of about 58% occurs when the fouling increases.

Simulation of a resonant inverter

Mostly developed since the Industrial Revolution, the automation of systems and equipment around us is responsible for a technological progress and economic growth without precedents, but also by a relentless energy dependence. Currently, fossil fuels still tend to come as the main energy source, even in developed countries, due to the ease in its extraction and the mastery of the technology needed for its use. However, the perception of its ending availability, as well as the environmental impact of this practice has led to a growing energy production originated from renewable sources. Easy maintenance, coupled with the fact that they are virtually inexhaustible, makes the solar and wind energy very promising solutions. In this context, this work proposes to facilitate energy production from these sources. To this end, in this work the power inverter is studied, which is an equipment responsible for converting DC power available by solar or wind power in traditional AC power. Then it is discussed and designed a new architecture which, in addition to achieve a high energy e - ciency, has also the ability to adapt to the type of conversion desired by the user, namely if he wants to sell electricity to the power grid, be independent of it or bet on a self consumption system. In order to achieve the promised energy e ciency, the projected inverter uses a resonant DC-DC converter, whose architecture signi cantly decreases the energy dissipated in the conversion, allowing a higher power density. The adaptability of the equipment is provided by an adaptive control algorithm, responsible for assessing its behavior on every iteration and making the necessary changes to achieve maximum stability throughout the process. To evaluate the functioning of the proposed architecture, a simulation is presented using the PLECS simulation software.