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Design, Implementation and Demonstration of Embedded Agents for Energy Management in Non-Residential Buildings

Institute for Energy Efficient Buildings and Indoor Climate, RWTH Aachen University, Aachen 52074,Germany
Institute for Automation of Complex Power Systems, RWTH Aachen University, Aachen 52074, Germany
Author to whom correspondence should be addressed.
Current address: Gridhound UG, Aachen 52068, Germany.
Energies 2017, 10(8), 1106;
Received: 4 June 2017 / Revised: 18 July 2017 / Accepted: 21 July 2017 / Published: 29 July 2017
(This article belongs to the Special Issue ICT for Energy)
PDF [1277 KB, uploaded 31 July 2017]


With the building sector being responsible for 30% of the total final energy consumption, great interest lies in implementing adequate policies and deploying efficient technologies that would decrease this number. However, building comfort and energy management systems (BCEM) are challenging to manage on account of their increasing complexity with regard to the integration of renewable energy sources or the connection of electrical, thermal and gas grids. Multi-agent~systems (MAS) deal well with such complex issues. This paper presents an MAS for non-residential buildings from the design, implementation and demonstration, both simulation based and in a field test. Starting from an ontology and an attached data model for BCEM application, we elaborated use cases for developing and testing the MAS framework. The building and technical equipment are modeled using the modeling language Modelica under Dymola. The agents are programmed in JADE and communicate with Dymola via TCP/IP and with the real devices via BACnet. Operatively, the~agents can take on different control strategies: normal operation with no optimization, optimization of energy costs, where energy is delivered through the room through the devices that have the lowest operating costs, and relaxation of the comfort constraint, where the costs of the productivity loss under sub-optimal comfort conditions is taken into account during optimization. Comfort is expressed as a function of indoor air temperature. Simulation, including a comparison with a benchmark system, and field test results are presented to demonstrate the features of the proposed BCEM. View Full-Text
Keywords: multi-agent systems; energy management; buildings; simulation multi-agent systems; energy management; buildings; simulation

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Constantin, A.; Löwen, A.; Ponci, F.; Müller, D.; Monti, A. Design, Implementation and Demonstration of Embedded Agents for Energy Management in Non-Residential Buildings. Energies 2017, 10, 1106.

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