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Open AccessArticle

MPC for Optimized Energy Exchange between Two Renewable-Energy Prosumers

Department of Electrical and Computer Engineering, University of Dayton, Dayton, OH 45440, USA
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Appl. Sci. 2019, 9(18), 3709; https://doi.org/10.3390/app9183709
Received: 27 July 2019 / Revised: 3 September 2019 / Accepted: 4 September 2019 / Published: 6 September 2019
(This article belongs to the Special Issue Advanced Solar–Wind–Hydro Hybrid Energy System)
Renewable energy and information technologies are changing electrical energy distribution, favoring a move towards distributed production and trading between many buyers and sellers. There is new potential for trading between prosumers, entities which both consume and produce energy in small quantities. This work explores the optimization of energy trading between two prosumers, each of which consists of a load, renewable supply, and energy storage. The problem is described within a model predictive control (MPC) framework, which includes a single objective function to penalize undesirable behavior, such as the use of energy from a utility company. MPC integrates future predictions of supply and demand into current dispatch decisions. The control system determines energy flows between each renewable supply and load, battery usage, and transfers between the two prosumers. At each time step, future predictions are used to create an optimized power dispatch strategy between the system prosumers, maximizing renewable energy use. Modeling results indicate that this coordinated energy sharing between a pair of prosumers can improve their overall renewable energy penetration. For one specific choice of prosumers (mixed residential–commercial) penetration is shown to increase from 71% to 84%. View Full-Text
Keywords: model predictive control; renewable energy; prosumer; microgrid; energy storage; renewable penetration; blockchain technology model predictive control; renewable energy; prosumer; microgrid; energy storage; renewable penetration; blockchain technology
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Aldaouab, I.; Daniels, M.; Ordóñez, R. MPC for Optimized Energy Exchange between Two Renewable-Energy Prosumers. Appl. Sci. 2019, 9, 3709.

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