AI for multi energy systems decision-support - Reina Sofia
VEOLIA in this pilot, at building level, is covering the role of facility manager (FM), aiming at generating analytics to improve FM processes.
What is the challenge that is being addressed?
This pilot involves a thermal plant and a distribution network that provides with heating, cooling, steam and domestic hot water to six different buildings of a hospital complex in Córdoba. Its control system manages a high amount of data, allowing the thermal plant to produce energy depending on the real demand at any time. The thermal plant has 4 boilers and 6 chillers, able to produce a total of 10 MW of cooling, 8.5 MW of heating and 4 MW of steam. Such facility needs information coming from each individual building (the energy demand) from a baseline (static data) as well as in operation (real data). The involvement of individual data forms the health sector is crucial to achieve this; on the other hand, the aggregation of such demand (simulated for designing purpose or measured for operational reason) is needed. Finally, the operation of the generation and distribution, how to match the demand to the generation, the prediction considering weather conditions or other kind of social event can contribute to economic benefit.
What is the AI solution the project plans to implement?
The FM, at district level use case, will be in charge of demonstrating how AI analytics can contribute to achieving an economic benefit optimisation as well as the reduction of energy consumption in a DHN. Additionally, the use case in in Laguna de Duero will be in charge of validating how I-NERGY framework will be able to collaborate in the designing activities related to an energy service company. This ESCO case will address an Energy Saving Verification Service (IPMVP based) for increasing the trust on EP Contracts.
Who will help implement this solution?
This pilot is implemented within the framework of the “I-NΕRGΥ: Artificial Intelligence for Next Generation Energy” Project. The I-NERGY Project has received funding from the European Union's Horizon 2020 Research and Innovation programme under grant agreement No. 101016508.
The responsible partner for this Use Case is VEOLIA (https://www.veolia.es/).