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This study analyzed biogas production from the anaerobic digestion of Coffee Wastewater (CWW), in Brazil. Physicochemical analyzes of CWW were performed before and after biodigestion. Four biodigesters B1, B2, B3, B4 maintained at 37 °C ± 2 °C were connected to a gasometer. 1.35 L of CWW and 0.15 L of inoculum (sludge from an Upflow Anaerobic Sludge Blanket) were fed into biodigesters B3 and B4, resulting in a total substrate level of 1.5 L for each one. Biodigesters B1 and B2 were fed 1.5 L of CWW that was pH adjusted to 6–8 in all four biodigesters at the start of the biodigestion. Theoretical estimations were given for the biomethane potential (BMP) arising from the chemical oxygen demand (COD). Given the BMP values, economic feasibility analysis was performed for a biogas system implemented in a coffee roasting production system under three scenarios: I - BMP for CWW COD without inoculum; II - BMP for CWW COD with inoculum; and III - BMP for the minimum required level of CWW COD needed for the system to be economically viable. The highest methane content observed was 11.4% in B4, which had the highest relative methane production to removed volatile solids (17.31 LkgVS−1rem).

This paper presents a model of electricity generator that integrates a dual fluidized bed gasifier and a 200 kW gas microturbine; the main objective of this research is to analyze the feasibility of using solid biomass as a fuel in the proposed assemblage. At the beginning, the latest advances in dual fluidized bed gasifier are presented, then the prime mover - gas microturbine - is addressed and after, both technologies operate jointly. The methodology implemented throughout this research is described in order to present and validate the model, which delivered an electrical power of 44.85 kW and showed an overall efficiency of 13.42%. A mathematical expression to determine the generated electrical power by system was developed. Finally, the results are discussed from the perspective of feasibility of implementing this technology.

After some hours of operation, every power plant’s equipment begins to show degraded performance. The amount of equipment degradation and the gain that can be achieved in plant heat rate and power generation by the replacement or repairing of each component is important information for proper plant maintenance management. This paper aims to show how diagnosis and prognosis of a power plant can be performed based on thermodynamic data measured by plant instrumentation on site. Some important points such as how to increase the accuracy of the prognostic by developing the complete Taylor series and how it affects the thermodynamic state are also explained. Practical considerations for implementing a thermodynamic diagnosis/prognosis system in a real plant are also discussed. The system receives thermodynamic data from the plant information system (PI) and after a filtering step, the performance factors (PFs) of each component are calculated based on the component’s performance curves. Thus, the current state can be modeled using these PFs. By replacing the calculated performance factors, component by component, with factors that represents no degradation, future cycle performance can be estimated. This work is a partial result of an ongoing research program that implements a thermodynamic diagnosis/prognosis system on a 130 MW combined cycle co-generation power plant.Copyright © 2009 by ASME