Oxy-fuel coal combustion, together with carbon capture and storage or utilization, is a set of technologies allowing to burn coal without emitting globe warming CO 2. As it is expected that oxy-fuel combustion may be used for a retrofit of existing boilers, development of a novel oxy-burners is very important step. It is expected that these burners will be able to sustain stable flame in oxy-fuel conditions, but also, for start-up and emergency reasons, in conventional, air conditions. The most cost effective way of achieving dual-mode boilers is to introduce dual-mode burners. Numerical simulations allow investigation of new designs and technologies at a relatively low cost, but for the results to be trustworthy they need to be validated. This paper proposes a workflow for design, modeling, and validation of dual-mode burners by combining experimental investigation and numerical simulations. Experiments are performed with semi-industrial scale burners in 0.5 MW t test facility for flame investigation. Novel CFD model based on ANSYS FLUENT solver, with special consideration of coal combustion process, especially regarding devolatilization, ignition, gaseous and surface reactions, NO x formation, and radiation was suggested. The main model feature is its ability to simulate pulverized coal combustion under different combusting atmospheres, and thus is suitable for both air and oxy-fuel combustion simulations. Using the proposed methodology two designs of pulverized coal burners have been investigated both experimentally and numerically giving consistent results. The improved burner design proved to be a more flexible device, achieving stable ignition and combustion during both combustion regimes: conventional in air and oxy-fuel in a mixture of O 2 and CO 2 (representing dry recycled flue gas with high CO 2 content). The proposed framework is expected to be of use for further improvement of multi-mode pulverized fuel swirl burners but can be also used for independent designs evaluation.

The necessity of the reduction of greenhouse gas emissions, as formulated in the Kyoto Protocol, imposes the need for improving environmental aspects of existing thermal power plants operation. Improvements can be reached either by efficiency increment or by implementation of emission reduction measures. Investments in refurbishment of existing plant components or in plant upgrading by flue gas desulphurization, by primary and secondary measures of nitrogen oxides reduction, or by biomass co-firing, are usually accompanied by modernisation of thermal power plant instrumentation and control system including sensors, equipment diagnostics and advanced controls. Impact of advanced control solutions implementation depends on technical characteristics and status of existing instrumentation and control systems as well as on design characteristics and actual conditions of installed plant components. Evaluation of adequacy of implementation of advanced control concepts is especially important in Western Balkan region where thermal power plants portfolio is rather diversified in terms of size, type and commissioning year and where generally poor maintenance and lack of investments in power generation sector resulted in high greenhouse gases emissions and low efficiency of plants in operation. This paper is intended to present possibilities of implementation of advanced control concepts, and particularly those based on artificial intelligence, in selected thermal power plants in order to increase plant efficiency and to lower pollutants emissions and to comply with environmental quality standards prescribed in large combustion plant directive. [Acknowledgements. This paper has been created within WBalkICT - Supporting Common RTD actions in WBCs for developing Low Cost and Low Risk ICT based solutions for TPPs Energy Efficiency increasing, SEE-ERA.NET plus project in cooperation among partners from IPA SA - Romania, University of Zagreb - Croatia and Vinca Institute from Serbia and. The project has initiated a strong scientific cooperation, with innovative approaches, high scientific level, in order to correlate in an optimal form, using ICT last generation solutions, the procedures and techniques from fossil fuels burning processes thermodynamics, mathematical modelling, modern methods of flue gases analysis, combustion control, Artificial Intelligence Systems with focus on Expert Systems category.

This paper presents possibilities of implementation of advanced combustion control concepts in selected Western Balkan thermal power plant, and particularly those based on artificial intelligence as part of primary measures for nitrogen oxide reduction in order to optimise combustion and to increase plant efficiency. Both considered goals comply with environmental quality standards prescribed in large combustion plant directive. Due to specific characterisation of Western Balkan power sector these goals should be reached by low cost and easily implementable solution. Advanced self-learning controller has been developed and the effects of advanced control concept on combustion process have been analysed using artificial neural-network based parameter prediction model.

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