Biomass Gasification - The characteristics of technology development and the rate of learning
Abstract: Gasification is considered one of the most promising technologies in biomass applications. The higher efficiency compared to boiler power systems, the perspectives in fuel synthesis and its environmental friendly features are some examples of its potential. Biomass gasification has evolved since its first applications, but it has not been possible to reach a solid commercial stage, except during periods of crises and only for some specific applications. Meanwhile, other gasification technologies, fed by fossil fuels, are currently widely used on industrial scales.This thesis aims to analyze the knowledge development and diffusion patterns of the biomass gasification technology since 1970’s in Austria, Finland, Germany and Sweden. Additionally, it seeks to identify the factors that strengthen and weaken the learning process. Finally, the concept of learning curve will be used to numerically assess the rate of learning in small scale biomass gasification for electricity generation. The feasibility of various future scenarios will be evaluated in order to know what is the likelihood for the technology to become competitive in the short term.To do so, the historical evolution of biomass gasification in Austria, Finland, Germany and Sweden has been analyzed. These countries have been selected due to the increasing number of ongoing projects and initiatives since 1970. Subsequently, the development of this technology has been encouraged by two historical facts. Initially, the price of fossil fuels grew in 1973 and 1979 enhancing the interest for biomass gasification as a future alternative. Afterwards, the willigness, shown by the mentioned countries, to reduce greenhouse gases emissions following the Kyoto protocol has revived the interest in biomass gasification. However, none of these two events has driven this technology sufficiently to achieve a sustainable commercial status. In addition, small and large scale projects have followed different development processes. In the case of large scale, interest has shifted from electricity generation to biofuel production, primarily due to the failed demonstration projects of the technology coupled with combined cycle for electricity generation. On the other hand, in small scale projects, cogeneration applications have gained interest over heat production. However, there are fewer actors involved in small scale experimentation than in large scale.Once the specific situation of each country has been analyzed, and the main characteristics of the development process have been identified, one of the causes which have hindered the technology to reach the expected commercial stage has been the lack of resources to demonstrate its competitiveness. So far, a significant number of experimentation activities, based on demonstration projects and pilot plants, have proved the future potential of the technology. Nonetheless, the uncertainty, shown by the great majority of actors, about integrating the biomass gasification in their industrial process has hindered the demonstration of its operational feasibility. Following this, further efforts should focus on the creation of incentives for the construction of new plants which integrate this technology in an industrial process already consolidated in the market. An approximation of the number of new plants needed, could be a good indicator of the economical resources required in order to acquire enough experience to make biomass gasification a competitive technology in the short-term.After simulating various future evolutions for small scale cogeneration applications, the learning rate obtained through the learning curves model predict that, building roughly forty plants in six years, the technology can be consolidated firmly in the market. Considering the decrease in the number of new plants built since 2002, the expectancies are not really optimistic. Nevertheless, it is not an unachievable objective if incentives are created by all administrative levels.
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