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Volume 6 Issue 3
May  2019

IEEE/CAA Journal of Automatica Sinica

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Raffaele Carli and Mariagrazia Dotoli, "Decentralized Control for Residential Energy Management of a Smart Users' Microgrid with Renewable Energy Exchange," IEEE/CAA J. Autom. Sinica, vol. 6, no. 3, pp. 641-656, May 2019. doi: 10.1109/JAS.2019.1911462
Citation: Raffaele Carli and Mariagrazia Dotoli, "Decentralized Control for Residential Energy Management of a Smart Users' Microgrid with Renewable Energy Exchange," IEEE/CAA J. Autom. Sinica, vol. 6, no. 3, pp. 641-656, May 2019. doi: 10.1109/JAS.2019.1911462

Decentralized Control for Residential Energy Management of a Smart Users' Microgrid with Renewable Energy Exchange

doi: 10.1109/JAS.2019.1911462
Funds:  This work was supported by European Regional Development Fund in the "Apulian Technology Clusters SMARTPUGLIA 2020" Program
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  • This paper presents a decentralized control strategy for the scheduling of electrical energy activities of a microgrid composed of smart homes connected to a distributor and exchanging renewable energy produced by individually owned distributed energy resources. The scheduling problem is stated and solved with the aim of reducing the overall energy supply from the grid, by allowing users to exchange the surplus renewable energy and by optimally planning users' controllable loads. We assume that each smart home can both buy/sell energy from/to the grid taking into account time-varying non-linear pricing signals. Simultaneously, smart homes cooperate and may buy/sell locally harvested renewable energy from/to other smart homes. The resulting optimization problem is formulated as a non-convex non-linear programming problem with a coupling of decision variables in the constraints. The proposed solution is based on a novel heuristic iterative decentralized scheme algorithm that suitably extends the Alternating Direction Method of Multipliers to a non-convex and decentralized setting. We discuss the conditions that guarantee the convergence of the presented algorithm. Finally, the application of the proposed technique to a case study under several scenarios shows its effectiveness.


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