This thesis develops optimization based techniques for the control of building heating, ventilation, and air-conditioning (HVAC) systems for the provision of demand response and ancillary services to the electric grid. The first part of the thesis focuses on the development of the open source MATLAB toolbox OpenBuild, developed for modeling of buildings for control applications. The toolbox constructs a first-principles based model of the building thermodynamics using EnergyPlus model data. It also generates the disturbance data affecting the models and allows one to simulate various usage scenarios and building types. It enables co-simulation between MATLAB and EnergyPlus, facilitating model validation and controller testing. OpenBuild streamlines the design and deployment of predictive controllers for control applications. The second part of the thesis introduces the concept of buildings acting as virtual storages in the electric grid and providing ancillary services. The control problem (for the bidding phase) to characterize the flexibility of a building, while also participating in the intraday energy market is formulated as a multi-stage uncertain optimization problem. An approximate solution method based on a novel intraday control policy and two-stage stochastic programming is developed to solve the bidding problem. A closed loop control algorithm based on a stochastic MPC controller is developed for the online operation phase. The proposed control method is used to carry out an extensive simulation study using real data to investigate the financial benefits of office buildings providing secondary frequency control services to the grid in Switzerland. The technical feasibility of buildings providing a secondary frequency control service to the grid is also demonstrated in experiments using the experimental platform (LADR) developed in the Automatic Control Laboratory of EPFL. The experimental results validate the effectiveness of the proposed control method. The third part of the thesis develops a hierarchical method for the control of building HVAC systems for providing ancillary services to the grid. Three control layers are proposed: The local building controllers at the lowest level track the temperature set points received from the thermal flexibility controller that maximizes the flexibility of a building’s thermal consumption. At the highest level, the electrical flexibility controller controls the HVAC system while maximizing the flexibility provided to the grid. The two flexibility control layers are based on robust optimization methods. A control-oriented model of a typical air-based HVAC system with a thermal storage tank is developed and the efficacy of the proposed control scheme is demonstrated in simulations.