Thermal demand prediction models for district heating networks
Do you want to anticipate the heating needs of your industrial or district heating network? With these thermal demand forecasting models, based on neural networks and meteorological data, you will obtain accurate and reliable predictions. Optimize the management of your district heating system for greater profitability and operational efficiency, taking advantage of advanced technology and our experience in large-scale projects.
Description of the service
At CIRCE-Technological Center we perform thermal demand prediction models in industrial heating networks.
Through the use of neural networks and based on historical consumption and meteorological variables, we offer accurate and reliable predictions.
These models are essential to understand and anticipate the heating needs of users in industrial and district heating environments. Thanks to them, it is possible to know the thermal demand of users and helps to better plan the management of a district heating system, so that management can be optimized and greater profitability can be achieved.
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Value proposition
Optimizing district heating management
Accurate knowledge of users' thermal demand enables more effective planning in district heating system management. This leads to significant optimization of resources, resulting in greater cost-effectiveness and operational efficiency.
Use of advanced technology
The use of neural networks to analyze and predict thermal demand ensures a high level of accuracy. These models can be adapted and continuously improved as more historical data becomes available and adjusted to weather variations.
Application in large-scale projects
Our experience has been demonstrated in European projects, such as ACCEPT, highlighting our ability to implement these solutions in various contexts and on a large scale.
Frequently Asked Questions (FAQs)
These models can be adapted and continuously improved as more historical data becomes available and adjusted to weather variations.
