This paper presents a decentralized control strategy for the scheduling of energy activities of interconnected smart homes that purchase energy from a supplier while exchanging renewable energy produced by individually owned distributed energy resources. The scheduling problem is solved with a twofold design objective. First, the model aims at reducing the overall energy supply from the grid, by allowing users to borrow/lend some amount of renewable energy from/to other users. Second, the problem is formulated to optimally plan users' controllable loads. We assume a time-varying quadratic pricing of the energy purchased from the distribution network. The proposed solution is based on a decentralized optimization algorithm combining parametric optimization with the proximal Jacobian Alternating Direction Method of Multipliers. The application of the proposed technique to a simulated case study under several scenarios shows its effectiveness.
A Decentralized Control Strategy for the Energy Management of Smart Homes with Renewable Energy Exchange / Carli, Raffaele; Dotoli, Mariagrazia. - ELETTRONICO. - (2018), pp. 1662-1667. (Intervento presentato al convegno IEEE Conference on Control Technology and Applications, CCTA 2018 tenutosi a Copenhagen, Denmark nel August 21-24, 2018) [10.1109/CCTA.2018.8511617].
A Decentralized Control Strategy for the Energy Management of Smart Homes with Renewable Energy Exchange
Raffaele Carli;Mariagrazia Dotoli
2018-01-01
Abstract
This paper presents a decentralized control strategy for the scheduling of energy activities of interconnected smart homes that purchase energy from a supplier while exchanging renewable energy produced by individually owned distributed energy resources. The scheduling problem is solved with a twofold design objective. First, the model aims at reducing the overall energy supply from the grid, by allowing users to borrow/lend some amount of renewable energy from/to other users. Second, the problem is formulated to optimally plan users' controllable loads. We assume a time-varying quadratic pricing of the energy purchased from the distribution network. The proposed solution is based on a decentralized optimization algorithm combining parametric optimization with the proximal Jacobian Alternating Direction Method of Multipliers. The application of the proposed technique to a simulated case study under several scenarios shows its effectiveness.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.