Termosun and Pervasive optimize biomass combustion for industrial boilers

Pervasive Technologies , a company specialized in the development of image recognition solutions through the use of Artificial Intelligence (AI) for different industrial sectors, together with Termosun and Imae, in collaboration with Schneider , have unified resources and knowledge in an innovative research project for the optimization of the combustion of biomass and related byproducts in industrial boilers through the application of Artificial Intelligence (AI) and other disruptive technologies such as Machine Learning and Big Data.

The worrying increase in the costs of fossil gas as a consequence of the current war in Ukraine, as well as the increase in the price of carbon credits, are causing many industries in Spain to begin the path towards the conversion of their thermal plants. , to replace obsolete traditional gas boilers with new boilers that use renewable biofuels, such as forest biomass or agroindustrial byproducts.

As we see, there is a growing demand for biomass boilers in the food, automotive, chemical, etc. industries. , but Termosun has observed that the operators and maintenance personnel of industrial facilities do not have sufficient skills for optimal management of the boilers, so that they do not make the most of their energy efficiency, nor do they manage to reduce polluting emissions as stated. could with current equipment and technology.

The operation and maintenance required by biomass boilers is superior to the simplicity of operation of gas boilers and this evolution must be accompanied by advanced data acquisition and management and more advanced control technologies, to prevent boiler efficiency from It depends solely on the operator. This guarantees efficiency and increases the useful life of the boiler, as well as environmental protection, avoiding overconsumption of biomass or defects that cause emissions into the atmosphere.

The 3BD project, Biomass Boiler Big Data , has been created in order to improve current algorithm models thanks to Artificial Intelligence . Machine Learning, by obtaining twins and creating algorithms, makes it possible to identify patterns in massive Big Data. In this way, predictions are made that give the possibility of digitalizing the operation of the boiler for optimal combustion, performance and minimum emissions.

Under the toolbox concept, the project combines tools that are integrated into the boiler in different scalability and licensing layers, the basic ones being:

• Continuous measurement of the parameters that occur in the different physical-chemical states during the combustion process
• Image capture of combustion grill inside oven
• Exhaust gas inline oxygen and temperature sensor set
• Massive data acquisition and interpretation platform
• training and data-related model
• Operation parameter correction interface

The tools are organized into different layers, starting with 0, also known as field hardware, and progressively escalate towards the acquisition, interpretation, iteration and alteration of operating parameters, to culminate with the corresponding report to the technical assistance service.