Source: Technological Innovation for the Internet of Things Book Series: IFIP Advances in Information and Communication Technology Volume: 394 Pages: 469-476 Published: 2013 Conference: 4th IFIP WG 5.5/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2013 Location: Costa da Caparica, Portugal Date: Apr 15-17, 2013 Sponsor(s): SOCOLNET; Int Federat Informat Process; IEEE Ind Elect Soc Document Type: Proceedings Paper Language: English

This paper presents a distributed model predictive control (DMPC) for indoor thermal comfort that simultaneously optimizes the consumption of a limited shared energy resource. The control objective of each subsystem is to minimize the heating/cooling energy cost while maintaining the indoor temperature and used power inside bounds. In a distributed coordinated environment, the control uses multiple dynamically decoupled agents (one for each subsystem/house) aiming to achieve satisfaction of coupling constraints. According to the hourly power demand profile, each house assigns a priority level that indicates how much is willing to bid in auction for consume the limited clean resource. This procedure allows the bidding value vary hourly and consequently, the agents order to access to the clean energy also varies. Despite of power constraints, all houses have also thermal comfort constraints that must be fulfilled. The system is simulated with several houses in a distributed environment. Author Keywords: DMPC; DSM; Limited resources; Energy auction