This talk will be divided into two parts; the first part will deal with energy efficient building climate control, and the second with shaping the demand response of buildings by using dynamic electricity prices.    Energy efficient management of building systems will play a major role in minimizing overall energy consumption and costs. Worldwide, the residential and commercial sectors use almost 40% of the final energy use in the world; and in European countries, 76% of this energy goes towards comfort control in buildings - Heating Ventilation and Air Conditioning (HVAC). In this talk, a Stochastic Model Predictive Control (SMPC) strategy for building climate control is developed that takes into account the uncertainty in weather predictions and employs chance constraints. The energy savings potential of SMPC is assessed in a large-scale factorial simulation study considering different types of buildings and HVAC systems at four representative European sites. It is found that SMPC outperforms current control practice in terms of both, energy efficiency and occupant comfort.    In the second part of the talk, a method for reducing peak electricity demand in building climate control by using real-time electricity pricing and applying MPC will be investigated. The use of a newly developed time-varying, hourly-based electricity tariff for end-consumers is proposed, that has been designed to truly reflect marginal costs of electricity provision, based on spot market prices as well as on electricity grid load levels, and is directly incorporated into the MPC cost function. Within the proposed tariff regime, grid-friendly behavior is rewarded. It is shown that peak electricity demand of buildings can be significantly reduced. The presented study is an example for the successful implementation of demand response (DR) in the field of building climate control.