Optimal Scheduling of Energy Storage Using A New Priority-Based Smart Grid Control Method
Luis Galván,
Juan M. Navarro,
Eduardo Galván,
Juan M. Carrasco and
Andrés Alcántara
Additional contact information
Luis Galván: Electronical Engineering Department, University of Seville, 41092 Seville, Spain
Juan M. Navarro: Electronical Engineering Department, University of Seville, 41092 Seville, Spain
Eduardo Galván: Electronical Engineering Department, University of Seville, 41092 Seville, Spain
Juan M. Carrasco: Electronical Engineering Department, University of Seville, 41092 Seville, Spain
Andrés Alcántara: Electronical Engineering Department, University of Seville, 41092 Seville, Spain
Energies, 2019, vol. 12, issue 4, 1-17
Abstract:
This paper presents a method to optimally use an energy storage system (such as a battery) on a microgrid with load and photovoltaic generation. The purpose of the method is to employ the photovoltaic generation and energy storage systems to reduce the main grid bill, which includes an energy cost and a power peak cost. The method predicts the loads and generation power of each day, and then searches for an optimal storage behavior plan for the energy storage system according to these predictions. However, this plan is not followed in an open-loop control structure as in previous publications, but provided to a real-time decision algorithm, which also considers real power measures. This algorithm considers a series of device priorities in addition to the storage plan, which makes it robust enough to comply with unpredicted situations. The whole proposed method is implemented on a real-hardware test bench, with its different steps being distributed between a personal computer and a programmable logic controller according to their time scale. When compared to a different state-of-the-art method, the proposed method is concluded to better adjust the energy storage system usage to the photovoltaic generation and general consumption.
Keywords: batteries; energy storage; microgrids; optimal scheduling; particle swarm optimization; power system management; smart grid; supply and demand; trade agreements (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (4)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:12:y:2019:i:4:p:579-:d:205346
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