Modern methods of monitoring and controlling combustion of solid fuels in order to reduce its environmental impact

Polska energetyka zawodowa, stoi przed problemem efektywnego prowadzenia procesu spalania w blokach, które w dużej mierze pochodzą sprzed 50 lat. Z drugiej strony należy zaznaczyć, że pojęcie efektywności takiego procesu należy rozumieć nie tylko w sensie parametrów techniczno-ekonomicznych, ale również ekologicznych Jest tak za sprawą wytycznych Komisji Europejskiej, ograniczających graniczne wartości emisji (ELV) NOx, CO oraz SO2 do atmosfery, ustawicznie zaostrzanych w ramach dyrektyw IIPC (Integrated Pollution Prevention and Control) oraz LCP (Large Combustion Plants). Dla przykładu, bloki o mocy powyżej 500 MWth, używające paliw stałych mają od roku 2008 ograniczoną wartość stężenia emisji tlenków azotu w wysokości 500 mg/Nm3, która po roku 2016 ma wynosić 200 mg/Nm3. Przy wytwarzaniu energii opartym głównie na spalaniu węgla kamiennego, brunatnego oraz współspalaniu biomasy, dużo uwagi poświęca się metodom pierwotnym. Szacunki mówią, że innowacyjne technologie oparte na metodach pierwotnych pozwolą spełnić rygory ELV przy połowie kosztów odpowiadających metodom redukcji katalitycznej [4]. Do istotnego aspektu ekologicznego, przeciwwagę stanowią obciążenia związane z kosztami oraz trudności i opóźnienia w uzyskiwaniu pozwoleń również w kontekście nowych inwestycji. Zatem istotnym zagadnieniem w obliczu zaistniałej sytuacji jest tania redukcja tlenków azotu (NOx). Liczne publikacje, np. [2÷4], jak i konferencje i sympozja naukowe, poruszają problemy niskoemisyjnych technik spalania.Polish power industry, faces the challenge of efficient management of the combustion process in power units, built largely 50 years ago. The concept of the effectiveness of such a process should be understood not only in terms of technical and economic parameters, but also environmental, due to the directives of the European Commission, continually tightening emissions limits. For example, solid fuel power units with a capacity above 500 MWth, had to reduce the nitrogen oxide emissions to 500 mg/Nm3 since 2008, which after the year 2016 is expected to be only 200 mg/Nm3. In power generation, mainly based on the combustion of coal, lignite, and cocombustion with biomass, much attention is drawn to the primary methods. It is estimated that innovative technologies based on primary methods will meet the rigours of the directives at half the costs of the catalytic reduction methods. In addition, new investments are burdened with additional costs as well as difficulties and delays in obtaining permits. Thus, in the face of this situation, relatively cheap reduction of nitrogen oxides (NOx) is an important issue, The complexity, nonlinearity of the combustion process, delays and disturbances as well as security issues makes that the nature of most discussed and implemented solutions is usually of modernization. The basic measures available to the engineer of low-emission combustion systems are limited to: reducing the combustion temperature, air redistribution, fuel staging (combustion aero-dynamics and reburning), and the reducing properties of the rich flame. Assistive technologies like process control optimization may be complementary to these technological improvements. Controlling the combustion process is a very complex issue. The difficulty of operation of such process consists in the mutual interference effects of chemical, physical (mainly energy and mechanical) on one hand and risks existing if its course becomes unpredictable. In addition, there are restrictions on the control due to the unavailability of certain process signals (input or output) and incomplete knowledge about them. Current availability of high-speed measuring and computing devices allows to extract the hidden relationships between the elements of such complex process and the use them in control. The paper presents the technologies being developed in the Department of Electronics Lublin University of Technology. They use optical diagnostic methods, modern methods of control and artificial intelligence methods. Among optical methods, those based on image processing become particularly important. They are shown in the first part of this article. Apparent motionlessness of a flame is the result of dynamic balance between the local flame propagation speed and the speed of the incoming fuel-oxidizer mixture. Change the flame front location in space, perceived as a change in the shape of a flame, is the result of disruption of this balance. This allows to assume that the flame shape can be an indicator of the status of a combustion process taking place in certain conditions. It was shown that even on the basis of simple geometrical indicators, such as the flame surface area and contour length of the flame area, one can determine the changes of important parameters such as change in the flame of air-fuel ratio. They can be determined in real time at a speed of 50 images per second. The second part of the article is devoted to the diagnosis of an individual burner with the use of optical methods and artificial intelligence. Research is aimed to develop a system allowing a parametric evaluation of the quality of pulverized coal burner operation. It is based on an analysis of local variability of the brightness of the flame. Due to the highly nonlinear nature of dependency and lack of an analytical model, parameter neural networks were used to estimate the selected parameter. For example, the neuronal estimator error of nitric oxide emissions on the basis of optical measurements does not exceed 10% and its average value is about 3%. Optoneural system for estimation of combustion process parameters was used in the control system stabilizing emissions of nitrogen oxides from a single burner. Studies have shown that using such system can significantly reduce the disturbance response time, which reduce the total amount of pollutants emitted. The third part describes the combustion chamber identification with three different types of low-emission burners. The achieved models were used for Model Predictive Controller design, which allows to implement appropriate borders for input, output and control signals. Achieved models and controllers were verified regarding to normative limitations of NOx emission. Performed activities allowed for conclusions formulation in reference to pollution control policy