EnPROVE · Energy consumption prediction with building usage measurements for software-based decision support

The objective of EnPROVE is to develop a software model for predicting the energy consumption of a specific building, with different scenarios implementing energy-efficient technologies and control solutions, based on actual measured performance and usage data of the building itself.The key hypothesis of EnPROVE is that it is possible, from adequate gathering and assessing data on how a structure performs and is being used from an energy viewpoint, to build highly accurate and specific energy consumption models relevant for prediction of alternative scenarios.The EnPROVE software tools will assess the energy-efficiency impact of alternative technologies for which available investment resources can be directed and, thus, support the decision maker finding the optimised set of energy-efficient solutions to be implemented. These results will be tailored to the actual building itself, through automated measurements of the building usage and energy efficiency. Technological solutions will include energy-reducing, -generating, and –storing options, and with user-defined criteria on resources and restrictions, will identify through new prediction algorithms when the return on investment will be realized.By solving these problems, EnPROVE will be able to develop crucial new tools, interoperable with existing CAD or Facility Management tools, to model the energy consumption from monitored data, predict the performance of alternative scenarios and support the decision maker in finding the optimal point for the investment. Compared to current available energy auditing services and prediction tools, it is foreseen that EnPROVE will increase the cost-effectiveness of renovation investments by 15 to 30%.These services will open new business opportunities for both construction companies that work on building renovation, as well as building management companies on long-term contracts. The application of the tools will be validated in two real buildings.