Regional integration of biogas – developing an intersectoral research action plan for Northern Ireland

Bioenergy is a key component of the European Union long term energy strategy across all sectors, with a target contribution of up to 14% of the energy mix by 2020. It is estimated that there is the potential for 1TWh of primary energy from biogas per million persons in Europe, derived from agricultural by-products and waste. With an agricultural sector that accounts for 75% of land area and a large number of advanced engineering firms, Northern Ireland is a region with considerable potential for an integrated biogas industry. Northern Ireland is also heavily reliant on imported fossil fuels. Despite this, the industry is underdeveloped and there is a need for a collaborative approach from research, business and policy-makers across all sectors to optimise Northern Ireland’s abundant natural resources. ‘Developing Opportunities in Bio-Energy’ (i.e. Do Bioenergy) is a recently completed project that involved both academic and specialist industrial partners. The aim was to develop a biogas research action plan for 2020 to define priorities for intersectoral regional development, co-operation and knowledge transfer in the field of production and use of biogas. Consultations were held with regional stakeholders and working groups were established to compile supporting data, decide key objectives and implementation activities. Within the context of this study it was found that biogas from feedstocks including grass, agricultural slurry, household and industrial waste have the potential to contribute from 2.5% to 11% of Northern Ireland’s total energy consumption. The economics of on-farm production were assessed, along with potential markets and alternative uses for biogas in sectors such as transport, heat and electricity. Arising from this baseline data, a Do Bioenergy was developed. The plan sets out a strategic research agenda, and details priorities and targets for 2020. The challenge for Northern Ireland is how best to utilise the biogas – as electricity, heat or vehicle fuel and in what proportions. The research areas identified were: development of small scale solutions for biogas production and use; solutions for improved nutrient management; knowledge supporting and developing the integration of biogas into the rural economy; and future crops and bio-based products. The human resources and costs for the implementation were estimated as 80 person-years and £25 million respectively. It is also clear that the development of a robust bio-gas sector requires some reform of the regulatory regime, including a planning policy framework and a need to address social acceptance issues. The Action Plan was developed from a regional perspective but the results may be applicable to other regions in Europe and elsewhere. This paper presents the methodology, results and analysis, and discussion and key findings of the Do Bioenergy report for Northern Ireland.

Resistivity and Induced Polarization Monitoring of Biogas combined with Microbial Ecology on a Brown field Site

The accumulation of biogenic greenhouse gases (methane, carbon dioxide) in organic sediments is an important factor in the redevelopment and risk management of many brownfield sites. Good practice with brownfield site characterization requires the identification of free-gas phases and pathways that allow its migration and release at the ground surface. Gas pockets trapped in the subsurface have contrasting properties with the surrounding porous media that favor their detection using geophysical methods. We have developed a case study in which pockets of gas were intercepted with multilevel monitoring wells, and their lateral continuity was monitored over time using resistivity. We have developed a novel interpretation procedure based on Archie’s law to evaluate changes in water and gas content with respect to a mean background medium. We have used induced polarization data to account for errors in applying Archie’s law due to the contribution of surface conductivity effects. Mosaics defined by changes in water saturation allowed the recognition of gas migration and groundwater infiltration routes and the association of gas and groundwater fluxes. The inference on flux patterns was analyzed by taking into account pressure measurements in trapped gas reservoirs and by metagenomic analysis of the microbiological content, which was retrieved from suspended sediments in groundwater sampled in multilevel monitoring wells. A conceptual model combining physical and microbiological subsurface processes suggested that biogas trapped at depth may have the ability to quickly travel to the surface.

Investigations Into the Performance of a Turbogenerated Biogas Engine During Speed Transients

Turbogenerating is a form of turbocompounding whereby a Turbogenerator is placed in the exhaust stream of an internal combustion engine. The Turbogenerator converts a portion of the expelled energy in the exhaust gas into electricity which can then be used to supplement the crankshaft power. Previous investigations have shown how the addition of a Turbogenerator can increase the system efficiency by up to 9%. However, these investigations pertain to the engine system operating at one fixed engine speed. The purpose of this paper is to investigate how the system and in particular the Turbogenerator operate during engine speed transients. On turbocharged engines, turbocharger lag is an issue. With the addition of a Turbogenerator, these issues can be somewhat alleviated. This is done by altering the speed at which the Turbogenerator operates during the engine’s speed transient. During the transients, the Turbogenerator can be thought to act in a similar manner to a variable geometry turbine where its speed can cause a change in the turbocharger turbine’s pressure ratio. This paper shows that by adding a Turbogenerator to a turbocharged engine the transient performance can be enhanced. This enhancement is shown by comparing the turbogenerated engine to a similar turbocharged engine. When comparing the two engines, it can be seen that the addition of a Turbogenerator can reduce the time taken to reach full power by up to 7% whilst at the same time, improve overall efficiency by 7.1% during the engine speed transient.

Influence of trace substances on methanation catalysts used in dynamic biogas upgrading

The aim of this work was to study the possible deactivation effects of biogas trace ammonia concentrations on methanation catalysts. It was found that small amounts of ammonia led to a slight decrease in the catalyst activity. A decrease in the catalyst deactivation by carbon formation was also observed, with ammonia absorbed on the active catalyst sites. This was via a suppression of the carbon formation and deposition on the catalyst, since it requires a higher number of active sites than for the methanation of carbon oxides. From the paper findings, no special pretreatment for ammonia removal from the biogas fed to a methanation process is required.

Techno-Economic Feasibility of Selective CO2 Capture Processes from Biogas Streams using Ionic Liquids as Physical Absorbents

Biogas from anaerobic digestion of sewage sludge is a renewable resource with high energy content, which is formed mainly of CH4 (40-75 vol.%) and CO2 (15-60 vol.%) Other components such as water (H2O, 5-10 vol.%) and trace amounts of hydrogen sulfide and siloxanes can also be present. A CH4-rich stream can be produced by removing the CO2 and other impurities so that the upgraded bio-methane can be injected into the natural gas grid or used as a vehicle fuel. The main objective of this paper is to develop a new modeling methodology to assess the technical and economic performance of biogas upgrading processes using ionic liquids which physically absorb CO2. Three different ionic liquids, namely the 1-ethyl-3-methylimidazolium bis[(trifluoromethyl)sulfonyl]imide, 1-hexyl-3-methylimidazoliumbis[(trifluoromethyl)sulfonyl]imide and trihexyl(tetradecyl)phosphonium bis[(trifluoromethyl)sulfonyl]imide, are considered for CO2 capture in a pressure-swing regenerative absorption process. The simulation software Aspen Plus and Aspen Process Economic Analyzer is used to account for mass and energy balances as well as equipment cost. In all cases, the biogas upgrading plant consists of a multistage compressor for biogas compression, a packed absorption column for CO2 absorption, a flash evaporator for solvent regeneration, a centrifugal pump for solvent recirculation, a pre-absorber solvent cooler and a gas turbine for electricity recovery. The evaluated processes are compared in terms of energy efficiency, capital investment and bio-methane production costs. The overall plant efficiency ranges from 71-86 % whereas the bio-methane production cost ranges from £6.26-7.76 per GJ (LHV). A sensitivity analysis is also performed to determine how several technical and economic parameters affect the bio-methane production costs. The results of this study show that the simulation methodology developed can predict plant efficiencies and production costs of large scale CO2 capture processes using ionic liquids without having to rely on gas solubility experimental data.

Modeling of Turbulent Natural Gas and Biogas Flames of the Delft Jet-in-Hot-Coflow Burner: Effects of Coflow Temperature, Fuel Temperature and Fuel Composition on the Flame Lift-Off Height

The structure of a turbulent non-premixed flame of a biogas fuel in a hot and diluted coflow mimicking moderate and intense low dilution (MILD) combustion is studied numerically. Biogas fuel is obtained by dilution of Dutch natural gas (DNG) with CO2. The results of biogas combustion are compared with those of DNG combustion in the Delft Jet-in-Hot-Coflow (DJHC) burner. New experimental measurements of lift-off height and of velocity and temperature statistics have been made to provide a database for evaluating the capability of numerical methods in predicting the flame structure. Compared to the lift-off height of the DNG flame, addition of 30 % carbon dioxide to the fuel increases the lift-off height by less than 15 %. Numerical simulations are conducted by solving the RANS equations using Reynolds stress model (RSM) as turbulence model in combination with EDC (Eddy Dissipation Concept) and transported probability density function (PDF) as turbulence-chemistry interaction models. The DRM19 reduced mechanism is used as chemical kinetics with the EDC model. A tabulated chemistry model based on the Flamelet Generated Manifold (FGM) is adopted in the PDF method. The table describes a non-adiabatic three stream mixing problem between fuel, coflow and ambient air based on igniting counterflow diffusion flamelets. The results show that the EDC/DRM19 and PDF/FGM models predict the experimentally observed decreasing trend of lift-off height with increase of the coflow temperature. Although more detailed chemistry is used with EDC, the temperature fluctuations at the coflow inlet (approximately 100K) cannot be included resulting in a significant overprediction of the flame temperature. Only the PDF modeling results with temperature fluctuations predict the correct mean temperature profiles of the biogas case and compare well with the experimental temperature distributions.

Integrated structure selection and parameter optimisation for eng-genes neural models

The eng-genes concept involves the use of fundamental known system functions as activation functions in a neural model to create a 'grey-box' neural network. One of the main issues in eng-genes modelling is to produce a parsimonious model given a model construction criterion. The challenges are that (1) the eng-genes model in most cases is a heterogenous network consisting of more than one type of nonlinear basis functions, and each basis function may have different set of parameters to be optimised; (2) the number of hidden nodes has to be chosen based on a model selection criterion. This is a mixed integer hard problem and this paper investigates the use of a forward selection algorithm to optimise both the network structure and the parameters of the system-derived activation functions. Results are included from case studies performed on a simulated continuously stirred tank reactor process, and using actual data from a pH neutralisation plant. The resulting eng-genes networks demonstrate superior simulation performance and transparency over a range of network sizes when compared to conventional neural models. (c) 2007 Elsevier B.V. All rights reserved.