Building the DeNOx System: Experience from a Real-World Application of Machine Learning

Abstract

Hogdalenverket is a combined heating and power station located in Stockholm, Sweden. At Hogdalenverket, waste from Stockholm households is burned to produce heat and power for the Stockholm area. Hogdalenverket has been instructed by the Swedish National Environment Protection Board to reduce its emissions of nitrogen oxides (NO x ). One way to achieve such a reduction is by injecting ammonia (NH 3 ) into the combustion chamber. The optimal amount of ammonia is affected by factors such as the temperature at the place of injection and the presence of various substances in the flue gasses. Machine learning has been applied to produce control rules for the injection of ammonia. In this paper we present the experience gained from developing this control system. We describe and characterize the different steps involved in the development of the system. We also give a characterization of the domain and the learning problem together with a motivation for the choice of l..