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

Multi-Agent Coordination of Thermostatically Controlled Loads by Smart Power Sockets for Electric Demand Side Management