Smart energy use and CO2 reduction
It is becoming more and more important that the industrial sector, responsible for over 40% of the total energy consumption in the Netherlands, pays its share in the current environmental crisis. The use of AI solutions, to improve efficiency in industrial processes, is a promising approach that can contribute significantly to energy and CO2 emission savings in this sector.
Due to the low CO2 and energy prices, the need for improvements to decrease CO2 emissions in the industrial sector is currently still small. However, as these prices are likely to increase in the (near) future, the urgency to implement energy and CO2 saving measures is increasing as well. Specifically the heavy industry is affected by this development, as many processes in this sector require high temperature heat, which makes it difficult to increase the sustainability of these processes. The distribution of this high temperature heat, however, shows great opportunities for improvement in the form of Smart Heat Management (SMEAT).
SMEAT uses AI solutions (like reinforcement learning) to solve complex optimization problems in the heavy industry. As factory premises often consist of many nodes and processes, optimization is complicated and time consuming, especially when the goal is to minimize both costs and CO2 emissions. A SMEAT system is able to provide operators with real-time advice on what decision regarding heat management will lead to the lowest (combination of) costs and CO2 emissions at any given point in time, dependent on the energy demand and supply at that time. By making smarter decisions regarding the distribution of the available energy and heat, significant energy savings can be achieved, lowering both costs and CO2 emissions.
As the savings potential of SMEAT will increase together with the number of nodes included in the system, even greater CO2 reductions can be achieved when energy distribution is optimized for a whole industrial cluster, instead of just one factory.
When optimizing heat distribution for multiple different factories/plants, it is important to make decisions that are equally beneficial for every partner in the cluster. The use of a SMEAT system is essential in this situation, as it is an independent/transparant and open sourced system that is able to advice operators with solving these complex issues.