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dc.contributor.authorArcos Aviles, Diego Gustavo
dc.contributor.authorPacheco Páramo, Diego Felipe
dc.contributor.authorPereira, Daniela
dc.contributor.authorGarcía Gutiérrez, Gabriel
dc.contributor.authorCarrera, Enrique
dc.contributor.authorIbarra, Alexander
dc.contributor.authorAyala Taco, Paul
dc.contributor.authorMartínez, Wilmar
dc.contributor.authorGuinjoan Gispert, Francisco
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica
dc.date.accessioned2022-02-16T11:17:43Z
dc.date.available2022-02-16T11:17:43Z
dc.date.issued2021-02-12
dc.identifier.citationAviles, D.A. [et al.]. A comparison of fuzzy-based energy management systems adjusted by nature-inspired algorithms. "Applied sciences (Basel)", 12 Febrer 2021, vol. 11, núm. 4, article 1663.
dc.identifier.issn2076-3417
dc.identifier.urihttp://hdl.handle.net/2117/362473
dc.description.abstractThe growing energy demand around the world has increased the usage of renewable energy sources (RES) such as photovoltaic and wind energies. The combination of traditional power systems and RESs has generated diverse problems due especially to the stochastic nature of RESs. Microgrids (MG) arise to address these types of problems and to increase the penetration of RES to the utility network. A microgrid includes an energy management system (EMS) to operate its components and energy sources efficiently. The objectives pursued by the EMS are usually economically related to minimizing the operating costs of the MG or maximizing its income. However, due to new regulations of the network operators, a new objective related to the minimization of power peaks and fluctuations in the power profile exchanged with the utility network has taken great interest in recent years. In this regard, EMSs based on off-line trained fuzzy logic control (FLC) have been proposed as an alternative approach to those based on on-line optimization mixed-integer linear (or nonlinear) programming to reduce computational efforts. However, the procedure to adjust the FLC parameters has been barely addressed. This parameter adjustment is an optimization problem itself that can be formulated in terms of a cost/objective function and is susceptible to being solved by metaheuristic nature-inspired algorithms. In particular, this paper evaluates a methodology for adjusting the FLC parameters of the EMS of a residential microgrid that aims to minimize the power peaks and fluctuations on the power profile exchanged with the utility network through two nature-inspired algorithms, namely particle swarm optimization and differential evolution. The methodology is based on the definition of a cost function to be optimized. Numerical simulations on a specific microgrid example are presented to compare and evaluate the performances of these algorithms, also including a comparison with other ones addressed in previous works such as the Cuckoo search approach. These simulations are further used to extract useful conclusions for the FLC parameters adjustment for off-line-trained EMS based designs.
dc.description.sponsorshipThis work is part of the projects 2019-PIC-003-CTE and 2020-EXT-007 from the Research Group of Propagation, Electronic Control, and Networking (PROCONET) of Universidad de las Fuerzas Armadas ESPE. This work has been developed with the support of VLIR-UOS and the Belgian Development Cooperation (DGD) under the project EC2020SIN322A101. This work has been partially supported by the Spanish Ministry of Industry and Competitiveness under the grant DPI2017-85404 and PID2019-111443RB-100.
dc.language.isoeng
dc.publisherMultidisciplinary Digital Publishing Institute
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectÀrees temàtiques de la UPC::Energies::Recursos energètics renovables
dc.subjectÀrees temàtiques de la UPC::Energies::Energia solar fotovoltaica
dc.subject.lcshRenewable energy sources
dc.subject.lcshSolar energy
dc.subject.otherMicrogrid
dc.subject.otherEnergy management system
dc.subject.otherFuzzy logic control
dc.subject.otherParticle swarm optimization
dc.subject.otherDifferential evolution
dc.subject.otherCuckoo search algorithm
dc.subject.otherNature-inspired algorithms
dc.titleA comparison of fuzzy-based energy management systems adjusted by nature-inspired algorithms
dc.typeArticle
dc.subject.lemacEnergies renovables
dc.subject.lemacEnergia solar
dc.contributor.groupUniversitat Politècnica de Catalunya. EPIC - Energy Processing and Integrated Circuits
dc.identifier.doi10.3390/app11041663
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.mdpi.com/2076-3417/11/4/1663
dc.rights.accessOpen Access
local.identifier.drac32549445
dc.description.versionPostprint (published version)
local.citation.authorAviles, D. Arcos; Pacheco Páramo, Diego Felipe; Pereira, D.; García-Gutiérrez, G.; Carrera, E.; Ibarra, A.; Ayala, P.; Martínez, W.; Guinjoan, F.
local.citation.publicationNameApplied sciences (Basel)
local.citation.volume11
local.citation.number4, article 1663
dc.description.sdgObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant


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