The REMOPTI project aims to develop an innovative decision-making framework for the energy retrofitting of buildings, integrating a holistic approach that goes beyond traditional methods by explicitly managing uncertainty and risk analysis.
Envisioning a building’s future means more than just observing current consumption; it involves understanding how costs, risks, and performance will change over the coming decades. These are variables that can be estimated, but are often influenced by phenomena so complex as to be unpredictable. Just consider how, in recent years, geopolitical tensions or unexpected weather events have sharply impacted energy prices.
Today, when developing energy retrofit strategies, we often rely on static assessments that fail to fully capture the complexity of real-world systems. The risk is making suboptimal decisions, investing with poor returns and results that fall short of expectations, both in terms of energy savings and economic sustainability. The lack of integrated decision-support tools therefore limits the ability to plan the management of the building stock in a strategic, accurate, and reliable manner.
Uncertainty Estimation
The REMOPTI applied research project was created precisely to help make more informed investment decisions, taking into account the uncertainty associated with characterizing a problem where variables of different natures - energy, economic, and environmenta - converge. Funded by Innosuisse, REMOPTI will be developed by SUPSI and AIL SA , in collaboration with the company Energo SA. The goal is to create an advanced decision-support tool for the energy retrofitting of buildings, integrating real-world data, predictive models, and optimization methodologies to help public agencies and real estate operators plan more robust, sustainable, and long-term-oriented investments.
"Today, when evaluating an investment, there is a tendency to adopt a deterministic approach. We base our reasoning on predefined hypothetical scenarios, assuming, for example, constant price growth or stable interest rates. In recent years, despite ourselves, we have all’experienced that this approach is no longer sufficient," begins Domenico Altieri , a researcher at SUPSI’s Institute of Applied Sustainability to the Built Environment (ISAAC) and project lead - "We want to develop an intelligent engine capable of integrating multiple dynamic variables in order to identify the most appropriate renovation and management strategies, whether for a single building or an entire real estate portfolio. We don’t limit ourselves to considering energy consumption; we also include environmental and meteorological factors, fluctuations in energy prices, and real estate market dynamics."
To achieve this goal, REMOPTI will combine building energy simulations, predictive models based on machine learning techniques, probabilistic analyses, and multi-criteria optimization methods. This will make it possible to explore countless scenarios, analyze trade-offs between different objectives (costs, consumption, risks), and generate clear operational guidelines for decision-makers.
Monitoring Helps with Renovation
To shape the future, however, it is essential to understand the present, starting with the monitoring of actual consumption. "REMOPTI will also address this need," emphasizes Giovanni Branca , senior lecturer and researcher at ISAAC, the Mendrisio-based institute of the Department of Environment, Construction, and Design. To reduce energy consumption and achieve the goals set by the Energy Strategy 2050, it is essential to have detailed information on the energy consumption of our buildings. REMOPTI will provide real-time energy monitoring of various energy sources, thereby supporting the renovation process of a single building or an entire building portfolio through the definition of targeted intervention measures. We are talking about both energy regulation and optimization measures, as well as interventions to renovate the building envelope or replace production systems, which allow us to identify optimal solutions based on the set objectives and parameters that may vary over time."
From Data to Decision
The SUPSI research team will be supported by Aziende Industriali di Lugano (AIL SA) . As the project’s operational partner, AIL SA will streamline the process of transferring consumption data, which is essential for the development of REMOPTI. This information will be anonymized, processed, and transmitted in accordance with current data protection and privacy regulations.
"In REMOPTI, AIL serves as the direct link to local entities," explains Michael Nyffeler , Project Manager at AIL. "We provide the information needed to train the model, along with our operational experience and concrete understanding of the needs of the customers we serve every day. Our commitment stems from a desire to go beyond the mere supply of energy and beyond simple meter readings, transforming the information we already collect into useful, interpretable, and decision-oriented value. With REMOPTI, we aim to help build tools that facilitate the planning of more effective energy interventions, reduce waste and costs, improve building efficiency, and support more informed, robust, and sustainable choices. "This project will allow us not only to improve the quality of the services we offer, but also to guide our customers - both public and private - toward a more conscious use of energy and toward a more efficient building stock that is ready for the challenges of the future."
Energo SA, a company specializing in energy optimization throughout Switzerland, will provide support for validating the models developed by the research team.
"REMOPTI introduces an advanced analysis model that improves and innovates the energy retrofit process: it processes and interprets consumption data by correlating it with the building’s characteristics, transforming it into clear and immediately actionable information. Through an intelligent evaluation system based on economic, energy, and environmental criteria, it identifies the most effective intervention solutions, accelerating the decision-making process."
The synergy between the academic institution, the energy utility, and the technical operator will make it possible to combine scientific rigor, contextual knowledge, and access to real-world data. This ecosystem will foster the development of transferable solutions that can be readily applied in the practical management of real estate assets. REMOPTI thus positions itself precisely at the intersection between data collection and monitoring and the making of well-informed strategic decisions.
Looking ahead, the goal is to provide a planning tool aimed not only at property owners but also at policymakers, in order to guide future energy policies with greater precision and concreteness.
The research project began in early 2026 and will conclude in 2029.