On the use of artificial intelligence for smarter district heating networks-Introduction to Panel discussion
Explore the use of AI in district heating networks to improve efficiency and customer comfort. Learn how to predict heat distribution, enhance temperature control, and optimize the entire energy chain. Discover examples of successful implementations and future possibilities in heat storage and waste utilization.
Download Presentation
Please find below an Image/Link to download the presentation.
The content on the website is provided AS IS for your information and personal use only. It may not be sold, licensed, or shared on other websites without obtaining consent from the author. If you encounter any issues during the download, it is possible that the publisher has removed the file from their server.
You are allowed to download the files provided on this website for personal or commercial use, subject to the condition that they are used lawfully. All files are the property of their respective owners.
The content on the website is provided AS IS for your information and personal use only. It may not be sold, licensed, or shared on other websites without obtaining consent from the author.
E N D
Presentation Transcript
Your Logo On the use of artificial intelligence for smarter district heating networks Introduction to Panel discussion Erik Dahlquist, Malardalen University, Eskilstuna/Vasteras, Sweden The 13thInternational Conference on Applied Energy, Nov 29- Dec 5, 2021, Virtual/Thailand www.applied-energy.org/icae2021
Traditional DH Your Logo Heat from power plant due to experience after weather forecast. Set out (temp and flowrate) and return temperatures. Good margine. Don t really know what result as temperature in buildings as a function of this. Just look at return temp. Don t know more than briefly how the heat is distributed in the net The 13thInternational Conference on Applied Energy, Nov 29- Dec 5, 2021, Virtual/Thailand
Want for the future A possibility to distribute heat an get feed back on temperature in customers buildings. Want to sell a service good comfort! Want to make a possibility to store heat in buildings new business models Want to get better control of how long it takes from the power plant to the different parts of the DHN to distribute more precise to different parts Get better understanding of not only temperature related demand but also hot water demand Want to include not only heat from power plant but also from distributed generation in e.g. buildings and industries. Use DHN also for cooling by absorption heat pumps Use both high and low temperature in the DHN reduce losses Your Logo The 13thInternational Conference on Applied Energy, Nov 29- Dec 5, 2021, Virtual/Thailand
What actions to take? Your Logo Use a combination of physical and statistical models to predict heat(cool) distribution better. Use temperatures in buildings to give feed-back for enhanced prediction (tune load models) Predict heat/cool deamnd long in advance. Can give possibility to load or deload heat in buildings in advance, but normally people don t mind a variation in temp with 2-3 oC if they see an incentive from this like reduced cost. Every customer can make a wish list for what temperatures to strive for and what limits are acceptable. Optimize electricity, heat, cool and possible production of bio-chemicals Optimize the whole chain from fuel source to production, distribution and consumption/use. The 13thInternational Conference on Applied Energy, Nov 29- Dec 5, 2021, Virtual/Thailand
Good examples? Your Logo Stockholm (Vattenfall) have started to contract heat supplies from locals to the grid. Also in Copenhagen and Stoke on Trent. Built load prediction models using combined physical models and ML in Vasteras. Enhanced the grid temperature control significantly Optimization of complete chain for Waste boiler in Vasteras at Malarenergy. Waste from UK by ship + from trucks locally. Waste sorting, CHP for heat and power production. DHN optimization using above. Low temperature systems tested at several sites The 13thInternational Conference on Applied Energy, Nov 29- Dec 5, 2021, Virtual/Thailand
What more can be done? Your Logo How are local conditions affecting the possibilities (giving limitations)? Is low temperature systems always good? How do we address a future decreased heat demand but increased cooling demand in many areas due to global warming? Is it possible to get as effcient DCN as DHN? Under what conditions? Is heat-cool storage of relevance everywhere? The 13thInternational Conference on Applied Energy, Nov 29- Dec 5, 2021, Virtual/Thailand
