Due to deregulations of the energy sector and the setting of targets such as the 20/20/20 in the EU, operators of public buildings are now more exposed to instantaneous (short-term) market conditions. On the other hand, they have gained the opportunity to play a more active role in securing long-term supply, managing demand, and hedging against risk while improving existing buildings' infrastructures. Therefore, there are incentives for the operators to develop and use a Decision Support System to manage their energy sub-systems in a more robust energy-efficient and cost-effective manner. In this paper, a two-stage stochastic model is proposed, where some decisions (so-called first-stage decision) regarding investments in new energy  technologies have to be taken before uncertainties are resolved, and some others (so-called second-stage decisions) on how to use the installed technologies will be taken once values for uncertain parameters become known, thereby providing a trade-off between long- and short-term decisions.