16 resultados para arine renewable energy

em CORA - Cork Open Research Archive - University College Cork - Ireland


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There has been an increased use of the Doubly-Fed Induction Machine (DFIM) in ac drive applications in recent times, particularly in the field of renewable energy systems and other high power variable-speed drives. The DFIM is widely regarded as the optimal generation system for both onshore and offshore wind turbines and has also been considered in wave power applications. Wind power generation is the most mature renewable technology. However, wave energy has attracted a large interest recently as the potential for power extraction is very significant. Various wave energy converter (WEC) technologies currently exist with the oscillating water column (OWC) type converter being one of the most advanced. There are fundemental differences in the power profile of the pneumatic power supplied by the OWC WEC and that of a wind turbine and this causes significant challenges in the selection and rating of electrical generators for the OWC devises. The thesis initially aims to provide an accurate per-phase equivalent circuit model of the DFIM by investigating various characterisation testing procedures. Novel testing methodologies based on the series-coupling tests is employed and is found to provide a more accurate representation of the DFIM than the standard IEEE testing methods because the series-coupling tests provide a direct method of determining the equivalent-circuit resistances and inductances of the machine. A second novel method known as the extended short-circuit test is also presented and investigated as an alternative characterisation method. Experimental results on a 1.1 kW DFIM and a 30 kW DFIM utilising the various characterisation procedures are presented in the thesis. The various test methods are analysed and validated through comparison of model predictions and torque-versus-speed curves for each induction machine. Sensitivity analysis is also used as a means of quantifying the effect of experimental error on the results taken from each of the testing procedures and is used to determine the suitability of the test procedures for characterising each of the devices. The series-coupling differential test is demonstrated to be the optimum test. The research then focuses on the OWC WEC and the modelling of this device. A software model is implemented based on data obtained from a scaled prototype device situated at the Irish test site. Test data from the electrical system of the device is analysed and this data is used to develop a performance curve for the air turbine utilised in the WEC. This performance curve was applied in a software model to represent the turbine in the electro-mechanical system and the software results are validated by the measured electrical output data from the prototype test device. Finally, once both the DFIM and OWC WEC power take-off system have been modeled succesfully, an investigation of the application of the DFIM to the OWC WEC model is carried out to determine the electrical machine rating required for the pulsating power derived from OWC WEC device. Thermal analysis of a 30 kW induction machine is carried out using a first-order thermal model. The simulations quantify the limits of operation of the machine and enable thedevelopment of rating requirements for the electrical generation system of the OWC WEC. The thesis can be considered to have three sections. The first section of the thesis contains Chapters 2 and 3 and focuses on the accurate characterisation of the doubly-fed induction machine using various testing procedures. The second section, containing Chapter 4, concentrates on the modelling of the OWC WEC power-takeoff with particular focus on the Wells turbine. Validation of this model is carried out through comparision of simulations and experimental measurements. The third section of the thesis utilises the OWC WEC model from Chapter 4 with a 30 kW induction machine model to determine the optimum device rating for the specified machine. Simulations are carried out to perform thermal analysis of the machine to give a general insight into electrical machine rating for an OWC WEC device.

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Diminishing non-renewable energy resources and planet-wide de-pollution on our planet are among the major problems which mankind faces into the future. To solve these problems, renewable energy sources such as readily available and inexhaustible sunlight will have to be used. There are however no readily available photocatalysts that are photocatalytically active under visible light; it is well established that the band gap of the prototypical photocatalyst, titanium dioxide, is the UV region with the consequence that only 4% of sun light is utilized. For this reason, this PhD project focused on developing new materials, based on titanium dioxide, which can be used in visible light activated photocatalytic hydrogen production and destruction of pollutant molecules. The main goal of this project is to use simulations based on first principles to engineer and understand rationally, materials based on modifying TiO2 that will have the following properties: (1) a suitable band gap in order to increase the efficiency of visible light absorption, with a gap around 2 – 2.5 eV considered optimum. (2). The second key aspect in the photocatalytic process is electron and hole separation after photoexcitation, which enable oxidation/reduction reactions necessary to i.e. decompose pollutants. (3) Enhanced activity over unmodified TiO2. In this thesis I present results on new materials based on modifying TiO2 with supported metal oxide nanoclusters, from two classes, namely: transition metal oxides (Ti, Ni, Cu) and p-block metal oxides (Sn, Pb, Bi). We find that the deposited metal oxide nanoclusters are stable at rutile and anatase TiO2 surfaces and present an analysis of changes to the band gap of TiO2, identifying those modifiers that can change the band gap to the desirable range and the origin of this. A successful collaboration with experimental researchers in Japan confirms many of the simulation results where the origin of improved visible light photocatalytic activity of oxide nanocluster-modified TiO2 is now well understood. The work presented in this thesis, creates a road map for the design of materials with desired photocatalytic properties and contributes to better understanding these properties which are of great application in renewable energy utilization.

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Wind energy is the energy source that contributes most to the renewable energy mix of European countries. While there are good wind resources throughout Europe, the intermittency of the wind represents a major problem for the deployment of wind energy into the electricity networks. To ensure grid security a Transmission System Operator needs today for each kilowatt of wind energy either an equal amount of spinning reserve or a forecasting system that can predict the amount of energy that will be produced from wind over a period of 1 to 48 hours. In the range from 5m/s to 15m/s a wind turbine’s production increases with a power of three. For this reason, a Transmission System Operator requires an accuracy for wind speed forecasts of 1m/s in this wind speed range. Forecasting wind energy with a numerical weather prediction model in this context builds the background of this work. The author’s goal was to present a pragmatic solution to this specific problem in the ”real world”. This work therefore has to be seen in a technical context and hence does not provide nor intends to provide a general overview of the benefits and drawbacks of wind energy as a renewable energy source. In the first part of this work the accuracy requirements of the energy sector for wind speed predictions from numerical weather prediction models are described and analysed. A unique set of numerical experiments has been carried out in collaboration with the Danish Meteorological Institute to investigate the forecast quality of an operational numerical weather prediction model for this purpose. The results of this investigation revealed that the accuracy requirements for wind speed and wind power forecasts from today’s numerical weather prediction models can only be met at certain times. This means that the uncertainty of the forecast quality becomes a parameter that is as important as the wind speed and wind power itself. To quantify the uncertainty of a forecast valid for tomorrow requires an ensemble of forecasts. In the second part of this work such an ensemble of forecasts was designed and verified for its ability to quantify the forecast error. This was accomplished by correlating the measured error and the forecasted uncertainty on area integrated wind speed and wind power in Denmark and Ireland. A correlation of 93% was achieved in these areas. This method cannot solve the accuracy requirements of the energy sector. By knowing the uncertainty of the forecasts, the focus can however be put on the accuracy requirements at times when it is possible to accurately predict the weather. Thus, this result presents a major step forward in making wind energy a compatible energy source in the future.

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The thesis initially gives an overview of the wave industry and the current state of some of the leading technologies as well as the energy storage systems that are inherently part of the power take-off mechanism. The benefits of electrical energy storage systems for wave energy converters are then outlined as well as the key parameters required from them. The options for storage systems are investigated and the reasons for examining supercapacitors and lithium-ion batteries in more detail are shown. The thesis then focusses on a particular type of offshore wave energy converter in its analysis, the backward bent duct buoy employing a Wells turbine. Variable speed strategies from the research literature which make use of the energy stored in the turbine inertia are examined for this system, and based on this analysis an appropriate scheme is selected. A supercapacitor power smoothing approach is presented in conjunction with the variable speed strategy. As long component lifetime is a requirement for offshore wave energy converters, a computer-controlled test rig has been built to validate supercapacitor lifetimes to manufacturer’s specifications. The test rig is also utilised to determine the effect of temperature on supercapacitors, and determine application lifetime. Cycle testing is carried out on individual supercapacitors at room temperature, and also at rated temperature utilising a thermal chamber and equipment programmed through the general purpose interface bus by Matlab. Application testing is carried out using time-compressed scaled-power profiles from the model to allow a comparison of lifetime degradation. Further applications of supercapacitors in offshore wave energy converters are then explored. These include start-up of the non-self-starting Wells turbine, and low-voltage ride-through examined to the limits specified in the Irish grid code for wind turbines. These applications are investigated with a more complete model of the system that includes a detailed back-to-back converter coupling a permanent magnet synchronous generator to the grid. Supercapacitors have been utilised in combination with battery systems for many applications to aid with peak power requirements and have been shown to improve the performance of these energy storage systems. The design, implementation, and construction of coupling a 5 kW h lithium-ion battery to a microgrid are described. The high voltage battery employed a continuous power rating of 10 kW and was designed for the future EV market with a controller area network interface. This build gives a general insight to some of the engineering, planning, safety, and cost requirements of implementing a high power energy storage system near or on an offshore device for interface to a microgrid or grid.

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The case for energy policy modelling is strong in Ireland, where stringent EU climate targets are projected to be overshot by 2015. Policy targets aiming to deliver greenhouse gas and renewable energy targets have been made, but it is unclear what savings are to be achieved and from which sectors. Concurrently, the growth of personal mobility has caused an astonishing increase in CO2 emissions from private cars in Ireland, a 37% rise between 2000 and 2008, and while there have been improvements in the efficiency of car technology, there was no decrease in the energy intensity of the car fleet in the same period. This thesis increases the capacity for evidenced-based policymaking in Ireland by developing techno-economic transport energy models and using them to analyse historical trends and to project possible future scenarios. A central focus of this thesis is to understand the effect of the car fleet‘s evolving technical characteristics on energy demand. A car stock model is developed to analyse this question from three angles: Firstly, analysis of car registration and activity data between 2000 and 2008 examines the trends which brought about the surge in energy demand. Secondly, the car stock is modelled into the future and is used to populate a baseline “no new policy” scenario, looking at the impact of recent (2008-2011) policy and purchasing developments on projected energy demand and emissions. Thirdly, a range of technology efficiency, fuel switching and behavioural scenarios are developed up to 2025 in order to indicate the emissions abatement and renewable energy penetration potential from alternative policy packages. In particular, an ambitious car fleet electrification target for Ireland is examined. The car stock model‘s functionality is extended by linking it with other models: LEAP-Ireland, a bottom-up energy demand model for all energy sectors in the country; Irish TIMES, a linear optimisation energy system model; and COPERT, a pollution model. The methodology is also adapted to analyse trends in freight energy demand in a similar way. Finally, this thesis addresses the gap in the representation of travel behaviour in linear energy systems models. A novel methodology is developed and case studies for Ireland and California are presented using the TIMES model. Transport Energy

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Due to growing concerns regarding the anthropogenic interference with the climate system, countries across the world are being challenged to develop effective strategies to mitigate climate change by reducing or preventing greenhouse gas (GHG) emissions. The European Union (EU) is committed to contribute to this challenge by setting a number of climate and energy targets for the years 2020, 2030 and 2050 and then agreeing effort sharing amongst Member States. This thesis focus on one Member State, Ireland, which faces specific challenges and is not on track to meet the targets agreed to date. Before this work commenced, there were no projections of energy demand or supply for Ireland beyond 2020. This thesis uses techno-economic energy modelling instruments to address this knowledge gap. It builds and compares robust, comprehensive policy scenarios, providing a means of assessing the implications of different future energy and emissions pathways for the Irish economy, Ireland’s energy mix and the environment. A central focus of this thesis is to explore the dynamics of the energy system moving towards a low carbon economy. This thesis develops an energy systems model (the Irish TIMES model) to assess the implications of a range of energy and climate policy targets and target years. The thesis also compares the results generated from the least cost scenarios with official projections and target pathways and provides useful metrics and indications to identify key drivers and to support both policy makers and stakeholder in identifying cost optimal strategies. The thesis also extends the functionality of energy system modelling by developing and applying new methodologies to provide additional insights with a focus on particular issues that emerge from the scenario analysis carried out. Firstly, the thesis develops a methodology for soft-linking an energy systems model (Irish TIMES) with a power systems model (PLEXOS) to improve the interpretation of the electricity sector results in the energy system model. The soft-linking enables higher temporal resolution and improved characterisation of power plants and power system operation Secondly, the thesis develops a methodology for the integration of agriculture and energy systems modelling to enable coherent economy wide climate mitigation scenario analysis. This provides a very useful starting point for considering the trade-offs between the energy system and agriculture in the context of a low carbon economy and for enabling analysis of land-use competition. Three specific time scale perspectives are examined in this thesis (2020, 2030, 2050), aligning with key policy target time horizons. The results indicate that Ireland’s short term mandatory emissions reduction target will not be achieved without a significant reassessment of renewable energy policy and that the current dominant policy focus on wind-generated electricity is misplaced. In the medium to long term, the results suggest that energy efficiency is the first cost effective measure to deliver emissions reduction; biomass and biofuels are likely to be the most significant fuel source for Ireland in the context of a low carbon future prompting the need for a detailed assessment of possible implications for sustainability and competition with the agri-food sectors; significant changes are required in infrastructure to deliver deep emissions reductions (to enable the electrification of heat and transport, to accommodate carbon capture and storage facilities (CCS) and for biofuels); competition between energy and agriculture for land-use will become a key issue. The purpose of this thesis is to increase the evidence-based underpinning energy and climate policy decisions in Ireland. The methodology is replicable in other Member States.

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The European Union has set out an ambitious 20% target for renewable energy use by 2020. It is expected that this will be met mainly by wind energy. Looking towards 2050, reductions in greenhouse gas emissions of 80-95% are to be sought. Given the issues securing this target in the transport and agriculture sectors, it may only be possible to achieve this target if the power sector is carbon neutral well in advance of 2050. This has permitted the vast expansion of offshore renewables, wind, wave and tidal energy. Offshore wind has undergone rapid development in recent years however faces significant challenges up to 2020 to ensure commercial viability without the need for government subsidies. Wave energy is still in the very early stages of development so as yet there has been no commercial roll out. As both of these technologies are to face similar challenges in ensuring they are a viable alternative power generation method to fossil fuels, capitalising on the synergies is potentially a significant cost saving initiative. The advent of hybrid solutions in a variety of configurations is the subject of this thesis. A singular wind-wave energy platform embodies all the attributes of a hybrid system, including sharing space, transmission infrastructure, O&M activities and a platform/foundation. This configuration is the subject of this thesis, and it is found that an OWC Array platform with multi-MegaWatt wind turbines is a technically feasible, and potentially an economically feasible solution in the long term. Methods of design and analysis adopted in this thesis include numerical and physical modelling of power performance, structural analysis, fabrication cost modelling, simplified project economic modelling and time domain reliability modelling of a 210MW hybrid farm. The application of these design and analysis methods has resulted in a hybrid solution capable of producing energy at a cost between €0.22/kWh and €0.31/kWh depending on the source of funding for the project. Further optimisation through detailed design is expected to lower this further. This thesis develops new and existing methods of design and analysis of wind and wave energy devices. This streamlines the process of early stage development, while adhering to the widely adopted Concept Development Protocol, to develop a technically and economically feasible, combined wind-wave energy hybrid solution.

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This work illustrates the influence of wind forecast errors on system costs, wind curtailment and generator dispatch in a system with high wind penetration. Realistic wind forecasts of different specified accuracy levels are created using an auto-regressive moving average model and these are then used in the creation of day-ahead unit commitment schedules. The schedules are generated for a model of the 2020 Irish electricity system with 33% wind penetration using both stochastic and deterministic approaches. Improvements in wind forecast accuracy are demonstrated to deliver: (i) clear savings in total system costs for deterministic and, to a lesser extent, stochastic scheduling; (ii) a decrease in the level of wind curtailment, with close agreement between stochastic and deterministic scheduling; and (iii) a decrease in the dispatch of open cycle gas turbine generation, evident with deterministic, and to a lesser extent, with stochastic scheduling.

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This paper examines 'availability' and the input metrics of operational expenditure (OPEX) for wave energy projects and reports on a case study which assesses the impact of these inputs on project profit returns. Case study simulations modelled a 75 MW wave energy project at two locations; the west coast of Ireland and the north coast of Portugal. Access and availability with respect to weather windows at both locations are discussed and their impact on energy output and wave farm operations is quantified. The input metrics used to calculate OPEX of wave energy projects are defined as well as the impact of OPEX on project net present value (NPV) and internal rate of return (IRR). Results indicate that access and resultant availability factors have a significant impact on case study results by reducing energy output and correspondingly financial returns. Furthermore, the technology maturity level designated for a project also impacts on availability factors and consequently energy output and NPV. Case study profits proved to be very sensitive to annual OPEX, especially if overhaul and replacement costs were accounted for. As a result of the impact of 'availability' on project profit returns. Feed-in tariffs will need to be tailored to the location in question as well as the device technology maturity level, with case study simulations indicating that high FIT will be required to support early stage WEC projects. (C) 2012 Elsevier Ltd. All rights reserved.

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Wave energy converters are currently proposed to be deployed near coastal area for the closeness to the infrastructure and for ease of maintenance in order to reduce operational costs. The motivation behind this work is the fact that the deployment depths during the highest and lowest tides will have a significant effect on the mooring system of WECs. In this paper, the issue will be investigated by numerical modelling (using ANSYS AQWA) for both catenary and taut moorings to examine the performance of the mooring system in varying tides. The case study being considered is the ¼- scale wave energy test site in Galway Bay off the west coast of Ireland where some marine renewable energy devices can be tested. In this test site, the tidal range is macro-tidal with a range of approximately 6 m which is a large value relative to the water depth. In the numerical analysis, ANSYS AQWA suite has been used to simulate moored devices under wave excitation at varying tidal ranges. Results show that the highest tide will give rise to larger forces. While at lower depths, slackening of the mooring occurs. Therefore, the mooring lines must be designed to accommodate both situations.

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This thesis is focused on the design and development of an integrated magnetic (IM) structure for use in high-power high-current power converters employed in renewable energy applications. These applications require low-cost, high efficiency and high-power density magnetic components and the use of IM structures can help achieve this goal. A novel CCTT-core split-winding integrated magnetic (CCTT IM) is presented in this thesis. This IM is optimized for use in high-power dc-dc converters. The CCTT IM design is an evolution of the traditional EE-core integrated magnetic (EE IM). The CCTT IM structure uses a split-winding configuration allowing for the reduction of external leakage inductance, which is a problem for many traditional IM designs, such as the EE IM. Magnetic poles are incorporated to help shape and contain the leakage flux within the core window. These magnetic poles have the added benefit of minimizing the winding power loss due to the airgap fringing flux as they shape the fringing flux away from the split-windings. A CCTT IM reluctance model is developed which uses fringing equations to accurately predict the most probable regions of fringing flux around the pole and winding sections of the device. This helps in the development of a more accurate model as it predicts the dc and ac inductance of the component. A CCTT IM design algorithm is developed which relies heavily on the reluctance model of the CCTT IM. The design algorithm is implemented using the mathematical software tool Mathematica. This algorithm is modular in structure and allows for the quick and easy design and prototyping of the CCTT IM. The algorithm allows for the investigation of the CCTT IM boxed volume with the variation of input current ripple, for different power ranges, magnetic materials and frequencies. A high-power 72 kW CCTT IM prototype is designed and developed for use in an automotive fuelcell-based drivetrain. The CCTT IM design algorithm is initially used to design the component while 3D and 2D finite element analysis (FEA) software is used to optimize the design. Low-cost and low-power loss ferrite 3C92 is used for its construction, and when combined with a low number of turns results in a very efficient design. A paper analysis is undertaken which compares the performance of the high-power CCTT IM design with that of two discrete inductors used in a two-phase (2L) interleaved converter. The 2L option consists of two discrete inductors constructed from high dc-bias material. Both topologies are designed for the same worst-case phase current ripple conditions and this ensures a like-for-like comparison. The comparison indicates that the total magnetic component boxed volume of both converters is similar while the CCTT IM has significantly lower power loss. Experimental results for the 72 kW, (155 V dc, 465 A dc input, 420 V dc output) prototype validate the CCTT IM concept where the component is shown to be 99.7 % efficient. The high-power experimental testing was conducted at General Motors advanced technology center in Torrence, Los Angeles. Calorific testing was used to determine the power loss in the CCTT IM component. Experimental 3.8 kW results and a 3.8 kW prototype compare and contrast the ferrite CCTT IM and high dc-bias 2L concepts over the typical operating range of a fuelcell under like-for-like conditions. The CCTT IM is shown to perform better than the 2L option over the entire power range. An 8 kW ferrite CCTT IM prototype is developed for use in photovoltaic (PV) applications. The CCTT IM is used in a boost pre-regulator as part of the PV power stage. The CCTT IM is compared with an industry standard 2L converter consisting of two discrete ferrite toroidal inductors. The magnetic components are compared for the same worst-case phase current ripple and the experimental testing is conducted over the operation of a PV panel. The prototype CCTT IM allows for a 50 % reduction in total boxed volume and mass in comparison to the baseline 2L option, while showing increased efficiency.

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Countries across the world are being challenged to decarbonise their energy systems in response to diminishing fossil fuel reserves, rising GHG emissions and the dangerous threat of climate change. There has been a renewed interest in energy efficiency, renewable energy and low carbon energy as policy‐makers seek to identify and put in place the most robust sustainable energy system that can address this challenge. This thesis seeks to improve the evidence base underpinning energy policy decisions in Ireland with a particular focus on natural gas, which in 2011 grew to have a 30% share of Ireland’s TPER. Natural gas is used in all sectors of the Irish economy and is seen by many as a transition fuel to a low-carbon energy system; it is also a uniquely excellent source of data for many aspects of energy consumption. A detailed decomposition analysis of natural gas consumption in the residential sector quantifies many of the structural drives of change, with activity (R2 = 0.97) and intensity (R2 = 0.69) being the best explainers of changing gas demand. The 2002 residential building regulations are subject to an ex-post evaluation, which using empirical data finds a 44 ±9.5% shortfall in expected energy savings as well as a 13±1.6% level of non-compliance. A detailed energy demand model of the entire Irish energy system is presented together with scenario analysis of a large number of energy efficiency policies, which show an aggregate reduction in TFC of 8.9% compared to a reference scenario. The role for natural gas as a transition fuel over a long time horizon (2005-2050) is analysed using an energy systems model and a decomposition analysis, which shows the contribution of fuel switching to natural gas to be worth 12 percentage points of an overall 80% reduction in CO2 emissions. Finally, an analysis of the potential for CCS in Ireland finds gas CCS to be more robust than coal CCS for changes in fuel prices, capital costs and emissions reduction and the cost optimal location for a gas CCS plant in Ireland is found to be in Cork with sequestration in the depleted gas field of Kinsale.

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Wind power generation differs from conventional thermal generation due to the stochastic nature of wind. Thus wind power forecasting plays a key role in dealing with the challenges of balancing supply and demand in any electricity system, given the uncertainty associated with the wind farm power output. Accurate wind power forecasting reduces the need for additional balancing energy and reserve power to integrate wind power. Wind power forecasting tools enable better dispatch, scheduling and unit commitment of thermal generators, hydro plant and energy storage plant and more competitive market trading as wind power ramps up and down on the grid. This paper presents an in-depth review of the current methods and advances in wind power forecasting and prediction. Firstly, numerical wind prediction methods from global to local scales, ensemble forecasting, upscaling and downscaling processes are discussed. Next the statistical and machine learning approach methods are detailed. Then the techniques used for benchmarking and uncertainty analysis of forecasts are overviewed, and the performance of various approaches over different forecast time horizons is examined. Finally, current research activities, challenges and potential future developments are appraised.

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On-farm biogas production is typically associated with forage maize as the biomass source. Digesters are designed and operated with the focus of optimising the conditions for this feedstock. Thus, such systems may not be ideally suited to the digestion of grass. Ireland has ca. 3.85 million ha of grassland. Annual excess grass, surplus to livestock requirements, could potentially fuel an anaerobic digestion industry. Biomethane associated with biomass from 1.1 % of grassland in Ireland, could potentially generate over 10 % renewable energy supply in transport. This study aims to identify and optimise technologies for the production of biomethane from grass silage. Mono-digestion of grass silage and co-digestion with slurry, as would occur on Irish farms, is investigated in laboratory trials. Grass silage was shown to have 7 times greater methane potential than dairy slurry on a fresh weight basis (107 m3 t-1 v 16 m3 t-1). However, comprehensive trace element profiles indicated that cobalt, iron and nickel are deficient in mono-digestion of grass silage at a high organic loading rate (OLR) of 4.0 kg VS m-3 d-1. The addition of a slurry co-substrate was beneficial due to its wealth of essential trace elements. To stimulate hydrolysis of high lignocellulose grass silage, particle size reduction (physical) and rumen fluid addition (biological) were investigated. In a continuous trial, digestion of grass silage of <1 cm particle size achieved a specific methane yield of 371 L CH4 kg-1 VS when coupled with rumen fluid addition. The concept of demand driven biogas was also examined in a two-phase digestion system (leaching with UASB). When demand for electricity is low it is recommended to disconnect the UASB from the system and recirculate rumen fluid to increase volatile fatty acid (VFA) and soluble chemical oxygen demand (SCOD) production whilst minimising volatile solids (VS) destruction. At times of high demand for electricity, connection of the UASB increases the destruction of volatiles and associated biogas production. The above experiments are intended to assess a range of biogas production options from grass silage with a specific focus on maximising methane yields and provide a guideline for feasible design and operation of on-farm digesters in Ireland.

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Biogas production is the conversion of the organic material into methane (CH4) and carbon dioxide (CO2) under anaerobic conditions. Anaerobic digestion (AD) is widely used in continental and Scandinavian communities as both a waste treatment option and a source of renewable energy. Ireland however lags behind this European movement. Numerous feedstocks exist which could be digested and used to fuel a renewable transport fleet in Ireland. An issue exists with the variety of feedstocks; these need to be assessed and quantified to ascertain their potential resource and application to AD. From literature the ideal C:N ratio is between 25 and 30:1. Low levels of C:N (<15) can lead to problems with ammonia inhibition. Within the digester a plentiful supply of nutrients and a balanced C:N is required for stable performance. Feedstocks were sampled from a range of over 100 different substrates in Ireland including for first, second and third generation feedstocks. The C:N ranged from 81:1 (Winter Oats) to 7:1 (Silage Effluent). The BMP yields were recorded ranging from 38 ± 2.0 L CH4 kg−1 VS for pig slurry (weaning pigs) to 805 ± 57 L CH4 kg−1 VS for used cooking oil (UCO). However the selection of the best preforming feedstock in terms of C:N ratio or BMP yield alone is not sufficiently adequate. A total picture has to be created which includes C:N ratio, BMP yield, harvest yield and availability. Potential feedstocks which best meet these requirements include for Grass silage, Milk processing waste (MPW) and Saccharina latissima. MPW has a potential of meeting over 6 times the required energy for Ireland’s 2020 transport in energy targets. S. Latissima recorded a yield of over 10,000 GJ ha-1 yr-1 which out ranks traditional second generation biofuels by a factor of more than 4.