Research Article
Optimal Scheduling of On/Off Cycles: A Decentralized IoT-Microgrid Approach
@INPROCEEDINGS{10.1007/978-3-319-49622-1_10, author={Fernando Lezama and Jorge Palominos and Ansel Rodr\^{\i}guez-Gonz\^{a}lez and Alessandro Farinelli and Enrique Cote}, title={Optimal Scheduling of On/Off Cycles: A Decentralized IoT-Microgrid Approach}, proceedings={Applications for Future Internet. International Summit, AFI 2016, Puebla, Mexico, May 25-28, 2016, Revised Selected Papers}, proceedings_a={AFI360}, year={2017}, month={1}, keywords={Multi-agent Smart Grid IoT Microgrid Optimization}, doi={10.1007/978-3-319-49622-1_10} }- Fernando Lezama
Jorge Palominos
Ansel Rodríguez-González
Alessandro Farinelli
Enrique Cote
Year: 2017
Optimal Scheduling of On/Off Cycles: A Decentralized IoT-Microgrid Approach
AFI360
Springer
DOI: 10.1007/978-3-319-49622-1_10
Abstract
The current energy scenario requires actions towards the reduction of energy consumptions and the use of renewable resources. To this end, the energy grid is evolving towards a distributed architecture called Smart Grid (SG). Moreover, new communication paradigms, such as the Internet of Things (IoT), are being applied to the SG providing advanced communication capabilities for management and control. In this context, a microgrid is a self-sustained network that can operate connected to the SG (or in isolation). In such networks, the long-term scheduling of on/off cycles of devices is a problem that has been commonly addressed by centralized approaches. In this paper, we propose a novel IoT-microgrid architecture to model the long-term optimization scheduling problem as a distributed constraint optimization problem (DCOP). We compare different multi-agent DCOP algorithms using different window sizes showing that the proposed architecture can find optimal and near-optimal solutions for a specific case study.
