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research tools & methods 7www.iiasa.ac.at summer 2017 ◼ options C onstructing or operating the energy system of a public building like a hospital or university campus involves making many complicated decisions. In order to achieve a robust energy supply, maximize energy efficiency, and minimize environmental impact, the stakeholders—including representatives of central and local governments, building managers and users, consultants, and decision-support system developers—need to agree on which technologies to invest in, decommission, or refurbish. The recent global deregulation of energy sectors and new efficiency targets in Europe mean that stakeholders are more exposed to energy and financial market risks, which can be further exacerbated by extreme weather events. However, stakeholders also gained the opportunity to play a more active role in energy security and managing demand and risk. For example, building managers now have more flexibility in decisions about energy sources, with incentives to invest in renewable energy technologies such as wind, solar, geothermal, and the possibility of participating in the energy market. However this flexibility can lead to new systemic risks and potentially irreversible problems if the decisions are inappropriate for the situation that occurs. In the face of these rising uncertainties and risks, IIASA researchers have developed a strategic Decision Support System (DSS) for energy-efficient technology investments, in collaboration with nine other research institutes and energy companies. This system can help design decisions that are robust, ensuring stable system performance no matter what the future may bring. “The key methodological advance of the new DSS is its underlying model, which has a random horizon defined by a ‘stopping time,’” says IIASA researcher Yurii Yermoliev. “The stopping time represents new conditions such as a natural disaster, a market shock, or new policies, which can lead to a system failure. The time horizons of the model can also be determined by the possible outcomes of stakeholder discussion.” The design of robust solutions has to be based on analysis of complex systemic interactions and risk exposure, evaluated with respect to the goals and constraints of the people involved. That requires a method called stochastic optimization, incorporating probabilistic constraints for safety and security, which guarantee that stakeholders’ requirements could be met under all circumstances. “Most existing DSSs are based on a deterministic optimization approach that is unable to provide decisions robust against uncertainties and risks. The deterministic approach performs analysis of ‘what-if’ cases and derives scenario-specific solutions. This can lead to system failure if something unexpected happens,” says IIASA researcher Tatiana Ermolieva, who also worked on the project. “Contrary to the deterministic approach, this DSS allows stakeholders to analyze a portfolio of interdependent, strategic long-term, and operational short-term decisions involving standard technological as well as market- oriented financial options, which ensures robust performance of energy systems.” In today’s world, stakeholders often have conflicting goals and have to make decisions with incomplete and uncertain information. The principles behind this DSS can also be applied to other problems in which people want to evaluate the long-term performance of systems in such a way that the negative impacts of policy alterations like removal of subsidies, or external events like weather or market conditions, are minimized. NL How to make decisions under uncertainty? Advanced methodology delivers robust solutions for improving energy efficiency in large buildings The DSS can be used to plan robust energy portfolios for buildings, districts or countries, and has been applied at several test sites in Europe, including the University of Applied Sciences Burgenland in Austria (pictured), and at the experimental KUBIK building in Spain. Further info Energy Efficiency and Risk Management in Public Buildings (EnRiMa) EU FP7 project §  www.iiasa.ac.at/Enrima Cano EL, Moguerza JM, Ermolieva T, & Yermoliev Y (2016). A strategic decision support system framework for energy-efficient technology investments. TOP: 1-22. [pure.iiasa.ac.at/13386] Tatiana Ermolieva ermol@iiasa.ac.at Yurii Yermoliev yermoliev@iiasa.ac.at iiasa research