Show simple item record

dc.creatorGrisales-Noreña L.F.
dc.creatorMontoya O.D.
dc.creatorGil-González W.
dc.identifier.citationJournal of Energy Storage; Vol. 25
dc.description.abstractThis paper presents a method to find the optimal location, selection, and operation of energy storage systems (ESS- batteries-) and capacitors banks (CB) in distribution systems (DS). A mixed-integer non-linear programming model is proposed to formulate the problem. In this model, the minimization of energy loss in the DS is selected as an objective function. As constraints are considered: the active and reactive energy balance, voltage regulation, the total number energy storage devices that can be installed into network, as well as the operative bounds associated with the ESS (time of charge-discharge and energy capabilities). Three operating scenarios for the DS are analyzed by adopting the method proposed in this work. The first scenario is an evaluation of the base case (without batteries and CB), in which the initial conditions of the DS are determined. The second scenario considers the location of the ESS composed by redox flow batteries. Finally, the third scenario includes the installation of REDOX flow batteries with CB in parallel to correct operating problems generated by battery charging, and improve their impact on the grid. A master-slave strategy is adopted to solve the problem here discussed, implementing a Chu & Beasley genetic algorithm in both stages as an optimization technique. The proposed method is tested in a 69-node test feeder, where numerical results demonstrate its effectiveness. © 2019 Elsevier Ltd
dc.description.sponsorshipUniversidad Nacional de Colombia, UN 727-2015 Universidad Tecnológica de Pereira, UTP: C2018P020 Departamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS), COLCIENCIAS Department of Science, Information Technology and Innovation, Queensland Government, DSITI P17211
dc.format.mediumRecurso electrónico
dc.publisherElsevier Ltd
dc.titleIntegration of energy storage systems in AC distribution networks: Optimal location, selecting, and operation approach based on genetic algorithms
dcterms.bibliographicCitationWong, L.A., Ramachandaramurthy, V.K., Taylor, P., Ekanayake, J., Walker, S.L., Padmanaban, S., Review on the optimal placement, sizing and control of an energy storage system in the distribution network (2019) J. Energy Storage, 21, pp. 489-504
dcterms.bibliographicCitationAwad, A.S.A., EL-Fouly, T.H.M., Salama, M.M.A., Optimal ESS allocation for load management application (2015) IEEE Trans. Power Syst., 30 (1), pp. 327-336
dcterms.bibliographicCitationNick, M., Hohmann, M., Cherkaoui, R., Paolone, M., Optimal location and sizing of distributed storage systems in active distribution networks (2013) 2013 IEEE Grenoble Conference, pp. 1-6
dcterms.bibliographicCitationFalvo, M.C., Martirano, L., Siano, P., Designing a customized electric power storage device for smart grids (2014) 2014 14th International Conference on Environment and Electrical Engineering, pp. 52-57
dcterms.bibliographicCitationGraditi, G., Ippolito, M.G., Telaretti, E., Zizzo, G., An innovative conversion device to the grid interface of combined res-based generators and electric storage systems (2015) IEEE Trans. Indus. Electron., 62 (4), pp. 2540-2550
dcterms.bibliographicCitationGrisales, L.F., Grajales, A., Montoya, O.D., Hincapie, R.A., Granada, M., Castro, C.A., Optimal location, sizing and operation of energy storage in distribution systems using multi-objective approach (2017) IEEE Lat. Am. Trans., 15 (6), pp. 1084-1090
dcterms.bibliographicCitationMontoya, O.D., Grajales, A., Garces, A., Castro, C.A., Distribution systems operation considering energy storage devices and distributed generation (2017) IEEE Lat. Am. Trans., 15 (5), pp. 890-900
dcterms.bibliographicCitationOsório, G., Rodrigues, E., Lujano-Rojas, J., Matias, J., Catalão, J., New control strategy for the weekly scheduling of insular power systems with a battery energy storage system (2015) Appl. Energy, 154, pp. 459-470
dcterms.bibliographicCitationMay, G.J., Davidson, A., Monahov, B., Lead batteries for utility energy storage: a review (2018) J. Energy Storage, 15, pp. 145-157
dcterms.bibliographicCitationGil-González, W., Montoya, O.D., Holguín, E., Garces, A., Grisales-Noreña, L.F., Economic dispatch of energy storage systems in dc microgrids employing a semidefinite programming model (2019) J. Energy Storage, 21, pp. 1-8
dcterms.bibliographicCitationSaif, A., Pandi, V.R., Zeineldin, H., Kennedy, S., Optimal allocation of distributed energy resources through simulation-based optimization (2013) Electr. Power Syst. Res., 104, pp. 1-8
dcterms.bibliographicCitationZeh, A., Witzmann, R., Operational strategies for battery storage systems in low-voltage distribution grids to limit the feed-in power of roof-mounted solar power systems (2014) Energy Proc., 46, pp. 114-123. , 8th International Renewable Energy Storage Conference and Exhibition (IRES 2013)
dcterms.bibliographicCitationTeng, J., Luan, S., Lee, D., Huang, Y., Optimal charging/discharging scheduling of battery storage systems for distribution systems interconnected with sizeable PV generation systems (2013) IEEE Trans. Power Syst., 28 (2), pp. 1425-1433
dcterms.bibliographicCitationXiao, J., Zhang, Z., Bai, L., Liang, H., Determination of the optimal installation site and capacity of battery energy storage system in distribution network integrated with distributed generation (2016) IET Gener. Transm. Distrib., 10 (3), pp. 601-607
dcterms.bibliographicCitationCelli, G., Mocci, S., Pilo, F., Loddo, M., Optimal integration of energy storage in distribution networks (2009) 2009 IEEE Bucharest PowerTech, pp. 1-7
dcterms.bibliographicCitationCapizzi, G., Bonanno, F., Napoli, C., Recurrent neural network-based control strategy for battery energy storage in generation systems with intermittent renewable energy sources (2011) 2011 International Conference on Clean Electrical Power (ICCEP), pp. 336-340
dcterms.bibliographicCitationBarnes, A.K., Balda, J.C., Escobar-Mejía, A., Geurin, S.O., Placement of energy storage coordinated with smart PV inverters (2012) 2012 IEEE PES Innovative Smart Grid Technologies (ISGT), pp. 1-7
dcterms.bibliographicCitationKaranki, S.B., Xu, D., Venkatesh, B., Singh, B.N., Optimal location of battery energy storage systems in power distribution network for integrating renewable energy sources (2013) 2013 IEEE Energy Conversion Congress and Exposition, pp. 4553-4558
dcterms.bibliographicCitationSomma, M.D., Graditi, G., Heydarian-Forushani, E., Shafie-khah, M., Siano, P., Stochastic optimal scheduling of distributed energy resources with renewables considering economic and environmental aspects (2018) Renew. Energy, 116, pp. 272-287. ,
dcterms.bibliographicCitationMoradi, M., Abedini, M., A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems (2012) Int. J. Electr. Power Energy Syst., 34 (1), pp. 66-74
dcterms.bibliographicCitationWei, C., Fadlullah, Z.M., Kato, N., Stojmenovic, I., On optimally reducing power loss in micro-grids with power storage devices (2014) IEEE J. Sel. Areas Commun., 32 (7), pp. 1361-1370
dcterms.bibliographicCitationChu, P., Beasley, J., A genetic algorithm for the generalised assignment problem (1997) Comput. Oper. Res., 24 (1), pp. 17-23
dcterms.bibliographicCitationGrisales-Noreña, L.F., Gonzalez Montoya, D., Ramos-Paja, C.A., Optimal sizing and location of distributed generators based on pbil and pso techniques (2018) Energies, 11 (4)
dcterms.bibliographicCitationJaved, M.S., Song, A., Ma, T., Techno-economic assessment of a stand-alone hybrid solar-wind-battery system for a remote island using genetic algorithm (2019) Energy, 176, pp. 704-717
dcterms.bibliographicCitationBlaifi, S., Moulahoum, S., Colak, I., Merrouche, W., An enhanced dynamic model of battery using genetic algorithm suitable for photovoltaic applications (2016) Appl. Energy, 169, pp. 888-898
dcterms.bibliographicCitationGrisales Noreña, L.F., Restrepo Cuestas, B.J., Jaramillo Ramirez, F.E., Ubicación y dimensionamiento de generación distribuida: Una revisión (2017) Cienc. Ing. Neogranadina, 27 (2), pp. 157-176
dcterms.bibliographicCitationVelasquez, O., Giraldo, O.M., Arevalo, V.G., Noreña, L.G., Optimal power flow in direct-current power grids via black hole optimization (2019) Adv. Electr. Electron. Eng., 17 (1)
dcterms.bibliographicCitationMontoya, O.D., Garcés, A., Espinosa-Pérez, G., A generalized passivity-based control approach for power compensation in distribution systems using electrical energy storage systems (2018) J. Energy Storage, 16, pp. 259-268
dcterms.bibliographicCitationGil-González, W., Montoya, O.D., Garces, A., Direct power control of electrical energy storage systems: a passivity-based PI approach (2019) Electr. Power Syst. Res., 175, p. 105885
dcterms.bibliographicCitationZhu, Q., Azar, A.T., Complex System Modelling and Control Through Intelligent Soft Computations (2015), Springer
dcterms.bibliographicCitationOuyang, W., Cheng, H., Zhang, X., Yao, L., Distribution network planning method considering distributed generation for peak cutting (2010) Energy Convers. Manag., 51 (12), pp. 2394-2401
dcterms.bibliographicCitationBaran, M.E., Wu, F.F., Optimal capacitor placement on radial distribution systems (1989) IEEE Trans. Power Deliv., 4 (1), pp. 725-734
dcterms.bibliographicCitationVenkatesh, B., Chandramohan, S., Kayalvizhi, N., Devi, R.P.K., Optimal reconfiguration of radial distribuion system using artificial intelligence methods (2009) 2009 IEEE Toronto International Conference Science and Technology for Humanity (TIC-STH), pp. 660-665
dcterms.bibliographicCitationSahoo, N., Prasad, K., A fuzzy genetic approach for network reconfiguration to enhance voltage stability in radial distribution systems (2006) Energy Convers. Manag., 47 (18), pp. 3288-3306
dc.subject.keywordsCapacitor banks
dc.subject.keywordsChu & Beasley genetic algorithm
dc.subject.keywordsEnergy storage systems
dc.subject.keywordsMaster-slave algorithm
dc.subject.keywordsOptimal power flow
dc.subject.keywordsRadial distribution networks
dc.subject.keywordsData storage equipment
dc.subject.keywordsElectric energy storage
dc.subject.keywordsElectric load flow
dc.subject.keywordsEnergy dissipation
dc.subject.keywordsGenetic algorithms
dc.subject.keywordsInteger programming
dc.subject.keywordsNonlinear programming
dc.subject.keywordsNumerical methods
dc.subject.keywordsVoltage regulators
dc.subject.keywordsCapacitor bank
dc.subject.keywordsEnergy storage systems
dc.subject.keywordsMaster slave
dc.subject.keywordsOptimal power flows
dc.subject.keywordsRadial distribution networks
dc.subject.keywordsFlow batteries
dc.rights.ccAtribución-NoComercial 4.0 Internacional
dc.identifier.instnameUniversidad Tecnológica de Bolívar
dc.identifier.reponameRepositorio UTB
dc.description.notesThis work was supported in part by the Administrative Department of Science, Technology and Innovation of Colombia ( COLCIENCIAS ) through the National Scholarship Program under Grant 727-2015 , in part by Universidad Nacional de Colombia, and Instituto Tecnológico Metropolitano under project P17211, and in part by the Universidad Tecnológica de Bolívar under grant project C2018P020.

Files in this item


There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record
Except where otherwise noted, this item's license is described as

Universidad Tecnológica de Bolívar - 2017 Institución de Educación Superior sujeta a inspección y vigilancia por el Ministerio de Educación Nacional. Resolución No 961 del 26 de octubre de 1970 a través de la cual la Gobernación de Bolívar otorga la Personería Jurídica a la Universidad Tecnológica de Bolívar.