A multi-stage stochastic optimization model for energy systems planning and risk management

•Optimization models are used to support decision making at the building level.•A stochastic model is developed for investments on energy-efficient technologies.•The risk neutral stochastic model takes into account parameters variability.•We add risk measures to the model in order to reduce risks of extreme scenarios.•We demonstrate how variability is reduced along scenarios, hedging against risks.

Strategic decision making at the building level is gaining importance in the context of a more and more deregulated energy market. The increase of the set of available options regarding distributed and renewable energy technologies leads to a complex decision process. Importantly, such decision making process is affected by uncertainties and therefore stochastic models are needed. In this paper, a comprehensive deterministic strategic optimization model for energy systems planning at the building level is extended to a stochastic optimization framework, thereby allowing the decision maker to manage risks in addition to considering the variability of the uncertain parameters. A numerical example shows the importance of taking into account uncertainty and risk in this kind of problems.