AVKVIN Abfallverbrennungskessel 4.0 - Digitalisierung und ganzheitliche Betriebscharakterisierung von Dampferzeugern in Abfallverbrennungskraftwerken


Efficient waste incineration makes a significant contribution to increasing sustainability in the use of resources by recovering raw materials and the chemical energy bound in the waste, as well as avoiding soil contamination and methane emissions from landfills. However, energy- and resource-efficient operation of a waste-to-energy plant is a complex task. Various target parameters are in tension with each other. At the same time, the inhomogeneous fuel (waste) makes operation more difficult. Against this background, the project 'Waste Combustion Boiler 4.0' (AVKVIN) is concerned with the digitalization and holistic operational characterization of steam generators in waste incineration power plants.


The goal of the project is to develop digitized methods for the optimized operation of steam generators in waste incineration power plants as a multi-criteria optimization to maximize throughput, electricity and heat production as well as the service life of the power plant components while taking emission limits into account. For this purpose, new data-based methods for determining the operating condition of the steam generators of waste incineration power plants are to be developed, analyses of the effects of different operating modes on the plants are to be carried out, and the testing of the developed methods in pilot operation is to be carried out.



Methods from the fields of machine learning, image recognition and physical-statistical models are used. Hereby two projects are pursued: On the one hand, the development of a better operating point estimation for the steam generator of waste incineration power plants and, on the other hand, the development of methods to optimize the steam generator operation holistically.


OFFIS is involved in this project as a subcontractor.


External Leader

Henriette Garmatter (IKW, Uni Hannover)
Einsatz von Künstlicher Intelligenz in der Digitalisierung von Abfallverbrennungskraftwerken

Alexandra Pehlken, Patrick Eschemann, Henriette Garmatter, Fabian Cyris, Astrid Nieße; INFORMATIK 2021 - Computer Science & Sustainability; 009 / 2021

How can machine learning improve waste-to-energy plant operation

Alexandra Pehlken, Henriette Garmatter, Lisa Dawel, Fabian Cyris, Hendrik Beck, Fenja Schwark, Roland Scharf, Astrid Nieße; ICE IEEE; 2022

The application of image recognition methods to improve the performance of waste-to-energy plants

Fenja Schwark, Henriette Garmatter, Maria Davila, Lisa Dawel, Alexandra Pehlken, Fabian Cyris, Roland Scharf; EnviroInfo 2022; 009 / 2022

Institut für Kraftwerkstechnik und Wärmeübertragung