V. Alcaraz-González

Instrumentation and control of anaerobic digestion processes : A review and some research challenges

AbstractTo enhance energy production from methane or resource recovery from digestate, anaerobic digestion processes require advanced instrumentation and control tools. Over the years, research on these topics has evolved and followed the main fields of application of anaerobic digestion processes: from municipal sewage sludge to liquid—mainly industrial—then municipal organic fraction of solid waste and agricultural residues. Time constants of the processes have also changed with respect to the treated waste from minutes or hours to weeks or months. Since fast closed loop control is needed for short time constant processes, human operator is now included in the loop when taking decisions to optimize anaerobic digestion plants dealing with complex solid waste over a long retention time. Control objectives have also moved from the regulation of key variables—measured on-line—to the prediction of overall process performance—based on global off-line measurements—to optimize the feeding of the processes. Additionally, the need for more accurate prediction of methane production and organic matter biodegradation has impacted the complexity of instrumentation and should include a more detailed characterization of the waste (e.g., biochemical fractions like proteins, lipids and carbohydrates) and their bioaccessibility and biodegradability characteristics. However, even if in the literature several methodologies have been developed to determine biodegradability based on organic matter characterization, only a few papers deal with bioaccessibility assessment. In this review, we emphasize the high potential of some promising techniques, such as spectral analysis, and we discuss issues that could appear in the near future concerning control of AD processes.

Anaerobic treatment of tequila vinasses under seasonal operating conditions: Start-up, normal operation and restart-up after a long stop and starvation period

This study examines the performance of an anaerobic fixed-film bioreactor under seasonal operating conditions prevailing in medium and small size Tequila factories: start-up, normal operation and particularly, during the restart-up after a long stop and starvation period. The proposed start-up procedure attained a stable biofilm in a rather short period (28 days) despite unbalanced COD/N/P ratio and the use of non-acclimated inoculum. The bioreactor was restarted-up after being shut down for 6 months during which the inoculum starved. Even when biofilm detachment and bioreactor clogging were detected at the very beginning of restart-up, results show that the bioreactor performed better as higher COD removal and methane yield were attained. CE-SSCP and Q-PCR analyses, conducted on the biofilm prokaryotic communities for each operating condition, confirmed that the high COD removal results after the bioreactor clogging and the severe starvation period were mainly due to the stable archaeal and resilient bacterial populations.

Regulation of the organic pollution level in anaerobic digesters by using off-line COD measurements.

A sampled delayed scheme is proposed to regulate the organic pollution level in anaerobic digestion processes by using off-line COD measurements. The proposed scheme is obtained by combining an error feedback control with a steady state estimator to track constant references and attenuate process load disturbances. The controller performance is tested experimentally for the treatment of tequila vinasses over a period of 68days under different set-point values and several uncertain scenarios which include badly known kinetic parameters and load disturbances. Experimental results show that the COD concentration can be effectively regulated under the influence of set-point changes and high load disturbances by using only a daily off-line COD measurement, which makes the industrial application of the proposed control scheme feasible.

Neural network modeling of the light profile in a novel photobioreactor

An artificial neural network (ANN) was implemented to model the light profile pattern inside a photobioreactor (PBR) that uses a toroidal light arrangement. The PBR uses Tequila vinasses as culture medium and purple non-sulfur bacteria Rhodopseudomonas palustris as biocatalyzer. The performance of the ANN was tested for a number of conditions and compared to those obtained by using deterministic models. Both ANN and deterministic models were validated experimentally. In all cases, at low biomass concentration, model predictions yielded determination coefficients greater than 0.9. Nevertheless, ANN yielded the more accurate predictions of the light pattern, at both low and high biomass concentration, when the bioreactor radius, the depth, the rotational speed of the stirrer and the biomass concentration were incorporated in the ANN structure. In comparison, most of the deterministic models failed to correlate the empirical data at high biomass concentration. These results show the usefulness of ANNs in the modeling of the light profile pattern in photobioreactors.

ROBUST REGULATION OF VOLATILE FATTY ACIDS IN AN ANAEROBIC DIGESTER

Abstract This paper deals with the robust regulation of volatile fatty acids (VFA) in an anaerobic digester. The digester is used for the treatment of industrial wine distillery wastewater. The robust approach is composed by an input-output linearizing feedback control and a Luenberger observer used to achieve the VFA regulation in spite of modelling errors (uncertain kinetics), actuator restrictions and load perturbations due to uncertain changes in the influent composition. The robust stability of the control approach is evaluated via numerical simulations under different operation conditions.

Evaluation of alkalinity spatial distribution in an up-flow fixed bed anaerobic digester

In this paper, an experimental study upon alkalinity and hydrodynamic behavior in an anaerobic up-flow fixed bed reactor for the treatment of tequila vinasses is presented. Measurements of volatile fatty acids, pH, alkalinity and bicarbonate were obtained at three sampling points in the reactor in the axial axis. Then, the spatial distribution of alkalinity is studied and discussed. Moreover, for further control process purposes, a hydrodynamic model based on the use of two interconnected two-steps reduced AM2 type models is proposed and its parameters are identified using experimental data.

Interval-Based Diagnosis of Biological Systems - Application to an Anaerobic Digestion Pilot Plant

Abstract Anaerobic digestion is a highly nonlinear time-varying process used for biological wastewater treatment which is subject to large disturbances of both influent concentrations and flow rates. These perturbations can lead to the crash of the digester and thus, the dynamics of the main state variables - including biomass - must be closely monitored to use this information in the design and implementation of advanced control schemes. However, such processes still suffer From a lack of reliable and cheap sensors. As a consequence, efficient monitoring, control and decision support systems are needed in order to insure the correct process operation. Particularly, there is an increasing interest on the proposal of Fault Detection and Isolation (FDI) and Fault Detection and Analysis (FDA) integrated systems. In this paper, we propose the use of interval observers in order to detect and isolate sensor faults as well as input changes in biological systems that are not observable. This approach is experimentally implemented on a 1 m 3 pilot scale anaerobic digestion continuous process.

NONLINEAR APPROACH FOR THE VFA REGULATION IN AN ANAEROBIC DIGESTER

This paper presents the design and the experimental validation of a nonlinear control approach for the regulation of volatile fatty acids (VFA) in an anaerobic digester. Such an approach is conformed by an output feedback control and an extended Luenberger observer which allows the estimation of the uncertain terms associated to the VFA dynamics (i.e., in∞uent composition and kinetic terms). The nonlinear approach is experimentally validated in a 0.528m 3 up-∞ow flxed-bed anaerobic digester used for the treatment of industrial wine distillery wastewater. The experimental results show that the VFA regulation is achieved in spite of uncertain kinetics, restrictions in the control input and unknown load disturbances. Copyright c ∞2007 IFAC

COD AND VFA'S CONTROL IN A TWO-PHASE ANAEROBIC DIGESTION PROCESS

Abstract In this paper, a two-phase anaerobic digestion system is considered to control the outlet concentration of both the Volatile Fatty Acids (VFAs) and the organic matter (other than the VFAs) characterized by its Chemical Oxygen Demand. The two-phase system consists of two fixed bed reactors whose dynamics are described by Partial Differential Equations. The recycle flow rates in each reactor are used as the manipulated variables to reach the control objective. The control laws designed here are decoupled and they are tested by means of simulation runs obtaining satisfactory results in spite of system input disturbances and changes on the set points.

Advanced Modelling for Media Composition Optimization of Phototrophic Growth

Abstract An Artificial Neural Network model was implemented in order to correlate media composition with the maximal efficiency in biomass and the maximal specific growth rate of the purple bacteria Rhodopseudomonas palustris. The performance of the ANN model was compared with the full quadratic model used in the response surface methodology to optimize the media composition. The fit grade was improved for both response variables by the ANN, being particularly effective for the specific growth rate, which was improved up to 20 percentage units.