The operation and maintenance required by biomass boilers must be accompanied by advanced data acquisition and management and more advanced control technologies to ensure efficiency and increase boiler lifetime. The 3BD project, Biomass Boiler Big Data, by Pervasive Technologies, Termosun Imae, and Schneider aims to improve the current algorithm models thanks to Artificial Intelligence to elaborate predictions that give the possibility to digitize the boiler operation for optimal combustion, performance and minimum emissions.
The growing demand for biomass boilers in the food, automotive and chemical industries, etc., means that operators and maintenance personnel of industrial facilities cannot take full advantage of their energy efficiency, nor can they reduce pollutant emissions as much as they 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 the efficiency of the boiler from depending solely on the operator. This guarantees efficiency and increases the boiler’s useful life, as well as protecting the environment by avoiding overconsumption of biomass or defects that cause emissions into the atmosphere.
For this reason, 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 biomass combustion and related by-products in industrial boilers through the application of Artificial Intelligence (AI) and other disruptive technologies such as Machine Learning and Big Data. The 3BD project, Biomass Boiler Big Data, has been created in order to improve the current algorithm models thanks to Artificial Intelligence. Machine Learning, with twin elicitation and the creation of algorithms, makes it possible to identify patterns in massive Big Data. In this way, predictions are made that make it possible to digitize boiler operation for optimum 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 tools are arranged in different layers, starting with layer 0, also known as field hardware, and progressively scale up to the acquisition, interpretation, iteration and alteration of operating parameters, culminating with the corresponding report to the helpdesk. The basic tools are:
– Continuous measurement of the parameters that occur in the different physico-chemical states during the combustion process.
– Image capture of the combustion grate inside the furnace.
– Set of oxygen and temperature probes in exhaust gas line.
– Massive data acquisition and interpretation platform
– Digital training and data affine and self-learning model
– Operating parameters correction interface
Rodolfo Lomascolo, CEO and co-founder of Pervasive Technologies, comments that “participating in such an innovative project that also helps to improve the environment is a source of pride for us. Providing the biomass boiler market with a solution to ensure optimal performance in terms of energy efficiency, reduced impact and reduced operation and maintenance costs has been a challenge and together with Termosun and Imae, we have achieved it”. For his part, Antonio Pont, CEO and co-founder of Termosun, adds: “We thank Pervasive and Imae for the high involvement of their technical teams who are applying their high level of knowledge with great commitment and diligence for the success of this project, a common good for the environment and for the industry”.
Source: Energías Renovables (2022)