Abstract
In this paper we develop and test a distributed algorithm providing Energy Consumption Schedules (ECS) in smart grids for a residential district. The goal is to achieve a given aggregate load profile. The NP-hard constrained optimization problem reduces to a distributed unconstrained formulation by means of Lagrangian Relaxation technique, and a meta-heuristic algorithm based on a Quantum inspired Particle Swarm with Lévy flights. A centralized iterative reputation-reward mechanism is proposed for end-users to cooperate to avoid power peaks and reduce global overload, based on random distributions simulating human behaviors and penalties on the effective ECS differing from the suggested ECS. Numerical results show the protocols effectiveness.
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Acknowledgments
Authours would like to thank Ennio Grasso for the scientific hints on the mathematical modeling and numerical implementation.
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© 2015 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Borra, D., Iori, M., Borean, C., Fagnani, F. (2015). A Reputation-Based Distributed District Scheduling Algorithm for Smart Grids. In: Giaffreda, R., et al. Internet of Things. User-Centric IoT. IoT360 2014. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 150. Springer, Cham. https://doi.org/10.1007/978-3-319-19656-5_11
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DOI: https://doi.org/10.1007/978-3-319-19656-5_11
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