Services and business models aiming at facilitating the design, refurbishment and development of building infrastructure. In particular, focusing at building level design of retrofitting actions, as well as at district level design of networks.
Sustainable building assessment and optimization of refurbishment options
The expected solution will achieve an improved holistic and cost-effective assessment of the performance of a building from and energy and sustainability perspective. The solution proposed will leverage the results of the OptEEmAL project, where a web-based tool was developed to support the design of energy efficient refurbishments at building and district level. The solution proposed will expand the functionalities offered by the platform by allowing their combination with the following: auto-model generation, calibrating the simulation models with real data, expanding the scope of the existing OptEEmAL Energy Conservation Measures catalogue and capability to generate new scenarios, evaluation of new Key Performance Indicators and feeding improved material passports.
Energy Demand Prediction to design and develop DHN and optimize the operation
VEOLIA in this pilot, at a district scale, is covering the role of district heating Facility Manager (FM), aiming at generating analytics to improve FM processes. This pilot involves a District Heating Network (DHN) providing heating and domestic hot water to 1,500 households with 19 distribution substations in Laguna de Duero (Spain). This is a relevant facility where the significance of the data at district level can be easily demonstrated. The DHN needs information coming from individual apartments (energy demand) from a baseline (static data) as well as in operation (real data). The involvement of individual data from the residential sector is crucial to achieve this. The aggregation of such demand (simulated for designing purpose or measured for operational reason) is needed. The operation of the generation and distribution, how to match the demand to the generation, the prediction taking into account weather conditions or other kind of social event can contribute to economic benefit. This pilot will be in charge of applying the MATRYCS framework to optimize the operation of this DHN, in order to create economic and environmental benefits. It will be also in charge of applying the MATRYCS framework to study both the addition of new buildings to the existing DHN and the implementation of new energy conservation measures. Information and data from the current DHN (Veolia Hubgrade) will calibrate new models and simulations of alternative scenarios, which will be created using new components and equipment extracted from e-catalogues. This FM use case will be responsible for demonstrating how analytics based on data will contribute to achieving an economic benefit optimization as well as the reduction of energy consumption in a DHN.