Application of Hybrid Agents to Smart Energy Management of a Prosumer Node

We outline a solution to the problem of intelligent control of energy consumption of a smart building system by a prosumer planning agent that acts on the base of the knowledge of the system state and of a prediction of future states. Predictions are obtained by using a synthetic model of the system as obtained with a machine learning approach. We present case studies simulations implementing different instantiations of agents that control an air conditioner according to temperature set points dynamically chosen by the user. The agents are able of energy saving while trying to keep indoor temperature within a given comfort interval

Editor’s Note

The research works presented in this issue are based on various topics of interest, among which are included: Mobile services, mpeg, agent-based Simulation, complexity, management accounting systems, animal-drawn vehicles, traffic and transport, possibility theory, precautionary saving, MAS, ambient intelligence, gamification, sustainable environments, disaster recovery, DSS, constraint programming and ICT

Application of Hybrid Agents to Smart Energy Management of a Prosumer Node.

We outline a solution to the problem of intelligent control of energy consumption of a smart building system by a prosumer planning agent that acts on the base of the knowledge of the system state and of a prediction of future states. Predictions are obtained by using a synthetic model of the system as obtained with a machine learning approach. We present case studies simulations implementing different instantiations of agents that control an air conditioner according to temperature set points dynamically chosen by the user. The agents are able of energy saving while trying to keep indoor temperature within a given comfort interval