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

Ana Constantin, Artur Löwen, Ferdinanda Ponci, Dirk Müller and Antonello Monti
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Ana Constantin: Institute for Energy Efficient Buildings and Indoor Climate, RWTH Aachen University, Aachen 52074,Germany
Artur Löwen: Institute for Automation of Complex Power Systems, RWTH Aachen University, Aachen 52074, Germany
Ferdinanda Ponci: Institute for Automation of Complex Power Systems, RWTH Aachen University, Aachen 52074, Germany
Dirk Müller: Institute for Energy Efficient Buildings and Indoor Climate, RWTH Aachen University, Aachen 52074,Germany
Antonello Monti: Institute for Automation of Complex Power Systems, RWTH Aachen University, Aachen 52074, Germany

Energies, 2017, vol. 10, issue 8, 1-20

Abstract: 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.

Keywords: multi-agent systems; energy management; buildings; simulation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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