  This paper presents a multi-agent control architecture and an online
optimization method based on dynamic average consensus to coordinate the power
consumption of a large population of Thermostatically Controlled Loads (TCLs).
Our objective is to penalize peaks of power demand, smooth the load profile and
enable Demand Side Management (DSM). The proposed architecture and methods
exploit only local measurements of power consumption via Smart Power Sockets
(SPSs) with no access to their internal temperature. No centralized aggregator
of information is exploited and agents preserve their privacy by cooperating
anonymously only through consensus-based distributed estimation, robust to
node/link failure. The interactions among devices are designed to occur through
an unstructured peer-to-peer (P2P) network over the internet. The architecture
includes novel methods for parameter identification, state estimation and mixed
logical modelling of TCLs and SPSs. It is designed from a multi-agent and
plug-and-play perspective in which existing household appliances can interact
with each other in an urban environment. Finally, a novel low cost testbed is
proposed along with numerical tests and an experimental validation.
