Penetration of advanced building control techniques into the market has been slow since buildings are unique and site-specific controller design is costly. In addition, for medium- to large-sized commercial buildings, HVAC system configurations can be very complex making centralized control infeasible. This paper presents a general multi-agent control methodology that can be applied to building energy system optimization in a "plug-and-play" manner. A multi-agent framework is developed to automate the controller design process and reduce the building-specific engineering efforts. To support distributed decision making, two alternative consensus-based distributed optimization algorithms are adapted and implemented within the framework. The overall multi-agent control approach was tested in simulation with two case studies: optimization of a chilled water cooling plant and optimal control of a direct expansion (DX) air-conditioning system serving a multi-zone building. In both cases, the multi-agent controller was able to find near-optimal solutions and significant energy savings were achieved. (C) 2016 Elsevier B.V. All rights reserved.