Existing technical issues related to biomass gasification process efficiency and environmental standards are preventing the technology to become more economically viable. In order to tackle those issues a lot of attention has been given to biomass gasification process predictive modelling. These models should be robust enough to predict process parameters during variable operating conditions. This could be accomplished either by changes of model input variables or by changes in model structure. This paper analyses the potential of neural network based modelling to predict process parameters during plant operation with variable operating conditions. Dynamic neural network based model for gasification purposes will be developed and its performance will be analysed based on measured data derived from a fixed bed biomass gasification plant operated by Technical University Dresden (TU Dresden). Dynamic neural network can predict process temperature with an average error less than 10% and in those terms performs better than multiple linear regression models. Average prediction error of syngas quality is lower than 30%. Developed model is applicable for online analysis of biomass gasification process under variable operating conditions. The model is automatically modified when new operating conditions occur.
15Advanced control solutions are a developing technology which represent a promising approach to tackle problems 16 related to efficiency and environmental aspects of biomass gasification process in a cost effective way. In this paper 17 the potential of advanced control concept to improve gasification process efficiency and to reduce negative 18 environmental effects of the process has been analysed. Advanced control solution, based on feedforward-feedback 19 control approach has been developed using collected operation data and the effects of control concept on 20 gasification process have been analysed using developed artificial neural network based prediction model. 21Measurement data for the controller and simulation model development has been extracted from a 75 MW th co-22 current, fixed bed biomass gasification plant operated by Technical University Dresden. The effects of 6 different 23 process improvement goals for controller algorithms development have been analysed during 20 hours of plant 24 operation. The analysis has shown that with introduction of advanced control solutions process efficiency could be 25 improved up to 20%, together with reduction of negative environmental aspects of the process. 26 33 34The process of biomass gasification is a high-temperature partial oxidation process in which a solid carbon based 35 feedstock is converted into a gaseous mixture (H 2 , CO, CO 2 , CH 4 , light hydrocarbons, tar, char, ash and minor 36 contaminates) called 'syngas', using gasifying agents [1]. Products of the gasification are mostly used for separately 37 or combined heat and power generation [2] such as in dry-grind ethanol facilities [3] or in autothermal biomass 38 gasification facilities with micro gas turbine or solid oxide fuel cells [4]. Utilisation of syngas for hydrogen 39 production through various available thermal processes is described in [5]. Hydrogen production potential from oil 40 palm shells through gasification has been analysed in [6]. Gasification systems integrated with methanol synthesis 41 have potential for a cleaner methanol production [7]. Other application of gasification systems for chemical 42 production are described in [8]. Besides chemical production, gasification systems could be utilised for building 43 material production using gasification residues [9]. A more detailed overview of biomass gasification technologies 44 could be found in [10]. For power generation purposes, syngas should meet some technical and environmental 45 requirements related to a certain percentage of particular gases (>20% CO and >10% H 2 ) and low tar content (<100 46 mg Nm -3 ) and it needs to be free of poisonous and carcinogenic gases [11]. 48Gasification is relatively well known technology, however, the share of gasification in meeting overall energy 49 demand is small due to current barriers concerning biomass pre-treatment (drying, grinding and densification), gas 50 cleaning (physical, thermal or catalytic), process efficiency and syngas quality issues [12]. Although a lot of effo...
Usage of Alternative Fuels in Power PlantsAlternative fuels can substitute standard fuels directly, e.g., in coal-fired power plants, or indirectly, e.g., as gaseous or liquid fuels produced via thermochemical conversion. They range from untreated biomass and biogenic waste to fuels with biogenic components. The efficient use of biogenic alternative fuels is an important pillar in regard to the CO 2 reduction plan of the German Federal Government and its aim for a 100 % renewable electric power supply. Based on a detailed fuel characterization the process specific requirements for co-firing in power plants are analyzed and the energetic efficiencies of various process chains are evaluated.
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