Low complexity energy management strategy for grid profile smoothing of a residential grid-connected microgrid using generation and demand forecasting
| dc.contributor.author | Arcos Avilés, Diego | |
| dc.contributor.author | Pascual Miqueleiz, Julio María | |
| dc.contributor.author | Guinjoan Gispert, Francesc | |
| dc.contributor.author | Marroyo Palomo, Luis | |
| dc.contributor.author | Sanchis Gúrpide, Pablo | |
| dc.contributor.department | Ingeniería Eléctrica y Electrónica | es_ES |
| dc.contributor.department | Ingeniaritza Elektrikoa eta Elektronikoa | eu |
| dc.date.accessioned | 2020-10-14T10:56:00Z | |
| dc.date.available | 2020-10-14T10:56:00Z | |
| dc.date.issued | 2017 | |
| dc.description.abstract | This paper presents the design of an energy management strategy based on a low complexity Fuzzy Logic Control (FLC) for grid power profile smoothing of a residential grid-connected microgrid including Renewable Energy Sources (RES) and battery Energy Storage System (ESS). The proposed energy management strategy uses generation and demand forecasting to anticipate the future behavior of the microgrid. Accordingly to the microgrid power forecast error and the Battery State-of-Charge (SOC) the proposed strategy performs the suitable control of the grid power. A simulation comparison with previous energy management strategies highlights the advantages of the proposed work minimizing fluctuations and power peaks in the power profile exchanged with the grid while keeping the energy stored in the battery between secure limits. Finally, the experimental validation in a real residential microgrid implemented at Public University of Navarre (UPNA, Spain) demonstrates the proper operation of the proposed strategy achieving a smooth grid power profile and a battery SOC center close to the 75% of the rated battery capacity. | en |
| dc.description.sponsorship | This work is part of the project 2016-PIC-044 from the Universidad de las Fuerzas Armadas ESPE. This work was partially supported by the Spanish State Research Agency (AEI) and FEDER-UE under grants: DPI2015-67292, DPI2013-41224-P, DPI2013-42853-R and DPI2016-80641-R. | en |
| dc.format.extent | 25 p. | |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.doi | 10.1016/j.apenergy.2017.07.123 | |
| dc.identifier.issn | 0306-2619 | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/38382 | |
| dc.language.iso | eng | en |
| dc.publisher | Elsevier | en |
| dc.relation.ispartof | Applied Energy, 2017, 205, 69-84 | en |
| dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//DPI2015-67292-R/ES/ | |
| dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//DPI2013-41224-P/ES/ | |
| dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//DPI2013-42853-R/ES/ | |
| dc.relation.projectID | info:eu-repo/grantAgreement/ES/1PE/DPI2016-80641-R/ | |
| dc.relation.publisherversion | https://doi.org/10.1016/j.apenergy.2017.07.123 | |
| dc.rights | © 2017 Elsevier Ltd. This manuscript version is made available under the CC-BY-NC-ND 4.0 | en |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | Distributed power generation | en |
| dc.subject | Energy management | en |
| dc.subject | Power forecasting | en |
| dc.subject | Fuzzy control | en |
| dc.subject | Microgrid | en |
| dc.subject | Power smoothing | en |
| dc.title | Low complexity energy management strategy for grid profile smoothing of a residential grid-connected microgrid using generation and demand forecasting | en |
| dc.type | info:eu-repo/semantics/article | |
| dc.type.version | info:eu-repo/semantics/acceptedVersion | |
| dspace.entity.type | Publication | |
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