@conference {31830,
	title = {MPCPy: An Open-Source Software Platform for Model Predictive Control in Buildings},
	booktitle = {Proceedings of the 15th IBPSA Conference: Building Simulation 2017},
	year = {2017},
	month = {08/2017},
	address = {San Francisco},
	abstract = {<p class="Body">Within the last decade, needs for building control systems that reduce cost, energy, or peak demand, and that facilitate building-grid integration, district-energy system optimization, and occupant interaction, while maintaining thermal comfort and indoor air quality, have come about.\&nbsp; Current PID and schedule-based control systems are not capable of fulfilling these needs, while Model Predictive Control (MPC) could.\&nbsp; Despite the critical role MPC-enabled buildings can play in future energy infrastructures, widespread adoption of MPC within the building industry has yet to occur.\&nbsp; To address barriers associated with system setup and configuration, this paper introduces an open-source software platform that emphasizes use of self-tuning adaptive models, usability by non-experts of MPC, and a flexible architecture that enables application across projects.</p>},
	keywords = {Model predictive control (MPC)},
	url = {http://www.ibpsa.org/proceedings/BS2017/BS2017_351.pdf},
	author = {David Blum and Michael Wetter}
}
