It is an irrefutable fact that energy efficiency in buildings is undoubtedly important. For the reason that energy efficiency is strongly dependent on detailed analyses, the state of the art offers a considerable variety of technologies and tools that support building facility managers in energy management matters. What is missing is an integrated approach that links up the strengths of building automation, energy monitoring systems, building simulation and load curve assessment into a secure, user-friendly tool with mobile user feedback and with a focus on the identification of improvement measures. In order to fill this gap the collaborate research and development project COFFEE (Calculating Optimizations and Forecasts For Energy Efficiency) was started in the mid of 2013. The project aims at developing an integrated system which will support building managers in collecting, managing, analyzing and interpreting building energy data by the mid of 2015.
COFFEE supports the ISO 50001
process based on building automation systems, being extended by an advanced data aggregation function for historical data, a simulation server providing thermal simulation services, an integrated monitoring solution that seamlessly integrates different data sources and a user interface for mobile devices. Additionally, the COFFEE project provides recommendations on promising efficiency improvement measures in a semi-automated way. The semi-automated recommendations are based on developing heuristic solution strategies for the combinatorial non-linear optimization problem allowing practically feasible execution.
Since the project connects buildings with components in the public and mobile Internet domain, security concerns, which have been widely neglected in the past, have to be solved. This is done by a defense-in-depth approach. The global energy management and optimization aspect is covered by the central COFFEE database application, using an extended JEVis
open source software core. The backend provides several communication interfaces and acts as a middleware to transfer measurements taken by the mobile app and delegates simulation results, building status and recommendations back to the users.