University buildings, like most public buildings, can be identified as “ownerless” or orphaned buildings. In a significant number of cases, energy management in Mediterranean universities does not involve dedicated staff, and any energy efficiency improvements are achieved through routine maintenance and renovation.

Among the actions proposed in Med-EcoSure to address these challenges is the development of a decision-making tool to help energy management staff, as the primary target group, identify and implement the best building renovation options and improve operational control to achieve significant energy savings while maintaining occupant comfort.

The interactive tool was designed and developed by the University of Seville, a Med-EcoSuRe partner, and serves as a multi-objective decision model for the optimal ranking/trade-off analysis between renovation options, based on relevant decision criteria. The online tool allows you to:

1. Evaluate the building’s performance in its initial state (baseline assessment) by calculating its energy consumption and reviewing all the results obtained;

2. Select a set of energy-saving measures provided through a catalog that includes conventional and innovative technologies and solutions that can be evaluated.

3. Perform a technical-economic optimization to obtain the most suitable renovation combinations for the selected building, and print a report that includes the initial situation and the savings obtained with each of the selected conservation measure combinations.

Using the developed decision-support tool, the most appropriate and cost-effective renovation measures will be identified for the Med-EcoSuRe project’s pilot buildings, among others.

To maximize the use of the tool, a training program has been launched, targeting project partners, as future trainers, and energy managers, primarily within universities.

The Lebanese Center for Energy Management (LCEC), a partner of ESMES, will also benefit from the training to assess the performance of their pilot buildings and optimize their operation using the proposed decision-support tool.