Mixed-integer programming model for transmission network expansion planning with Battery Energy Storage Systems (BESS)
This article assesses the costs and benefits of incorporating battery energy storage systems (BESS) in transmission network expansion planning (TEP) over multiple time periods. We propose a mixed-integer programming model (MIP) for joint planning of the installation of battery energy storage systems...
- Autores:
-
Mora, Camilo Andres
Montoya, Oscar Danilo
Rivas Trujillo, Edwin
- Tipo de recurso:
- Fecha de publicación:
- 2020
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/9548
- Palabra clave:
- Mixed-integer linear programming
Transmission expansion planning
Battery energy storage systems
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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|
dc.title.spa.fl_str_mv |
Mixed-integer programming model for transmission network expansion planning with Battery Energy Storage Systems (BESS) |
title |
Mixed-integer programming model for transmission network expansion planning with Battery Energy Storage Systems (BESS) |
spellingShingle |
Mixed-integer programming model for transmission network expansion planning with Battery Energy Storage Systems (BESS) Mixed-integer linear programming Transmission expansion planning Battery energy storage systems |
title_short |
Mixed-integer programming model for transmission network expansion planning with Battery Energy Storage Systems (BESS) |
title_full |
Mixed-integer programming model for transmission network expansion planning with Battery Energy Storage Systems (BESS) |
title_fullStr |
Mixed-integer programming model for transmission network expansion planning with Battery Energy Storage Systems (BESS) |
title_full_unstemmed |
Mixed-integer programming model for transmission network expansion planning with Battery Energy Storage Systems (BESS) |
title_sort |
Mixed-integer programming model for transmission network expansion planning with Battery Energy Storage Systems (BESS) |
dc.creator.fl_str_mv |
Mora, Camilo Andres Montoya, Oscar Danilo Rivas Trujillo, Edwin |
dc.contributor.author.none.fl_str_mv |
Mora, Camilo Andres Montoya, Oscar Danilo Rivas Trujillo, Edwin |
dc.subject.keywords.spa.fl_str_mv |
Mixed-integer linear programming Transmission expansion planning Battery energy storage systems |
topic |
Mixed-integer linear programming Transmission expansion planning Battery energy storage systems |
description |
This article assesses the costs and benefits of incorporating battery energy storage systems (BESS) in transmission network expansion planning (TEP) over multiple time periods. We propose a mixed-integer programming model (MIP) for joint planning of the installation of battery energy storage systems (BESS) and construction of new transmission lines in multiple periods of time. The mathematical formulation of the presented model is based on the strategies of the agents of a transmission network to maximize their benefit, and on the operational restrictions of the power flows in transmission networks. This analysis is performed for the Garver 6 node test system takes into account the power losses in the lines and the restrictions for the energy stored in BESS. The power flows obtained with the MIP model are compared with AC power flows generated with specialized software for flows in power systems. This allows us to demonstrate the potential of models based on DC power flows to achieve approximate results applicable to the behavior and characteristics of real transmission networks. The results show that the BESS increase the net profit in the transmission networks and reduce their power losses. |
publishDate |
2020 |
dc.date.accessioned.none.fl_str_mv |
2020-11-04T21:44:15Z |
dc.date.available.none.fl_str_mv |
2020-11-04T21:44:15Z |
dc.date.issued.none.fl_str_mv |
2020-08-25 |
dc.date.submitted.none.fl_str_mv |
2020-11-04 |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.hasVersion.spa.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.spa.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
status_str |
publishedVersion |
dc.identifier.citation.spa.fl_str_mv |
Mora, C.A.; Montoya, O.D.; Trujillo, E.R. Mixed-Integer Programming Model for Transmission Network Expansion Planning with Battery Energy Storage Systems (BESS). Energies 2020, 13, 4386. |
dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/9548 |
dc.identifier.url.none.fl_str_mv |
https://www.mdpi.com/1996-1073/13/17/4386 |
dc.identifier.doi.none.fl_str_mv |
10.3390/en13174386 |
dc.identifier.instname.spa.fl_str_mv |
Universidad Tecnológica de Bolívar |
dc.identifier.reponame.spa.fl_str_mv |
Repositorio Universidad Tecnológica de Bolívar |
identifier_str_mv |
Mora, C.A.; Montoya, O.D.; Trujillo, E.R. Mixed-Integer Programming Model for Transmission Network Expansion Planning with Battery Energy Storage Systems (BESS). Energies 2020, 13, 4386. 10.3390/en13174386 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
url |
https://hdl.handle.net/20.500.12585/9548 https://www.mdpi.com/1996-1073/13/17/4386 |
dc.language.iso.spa.fl_str_mv |
eng |
language |
eng |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.uri.*.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
dc.rights.accessRights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
dc.rights.cc.*.fl_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://purl.org/coar/access_right/c_abf2 |
eu_rights_str_mv |
openAccess |
dc.format.extent.none.fl_str_mv |
21 páginas |
dc.format.mimetype.spa.fl_str_mv |
application/pdf |
dc.publisher.place.spa.fl_str_mv |
Cartagena de Indias |
dc.source.spa.fl_str_mv |
Energies 2020, 13(17), 4386 |
institution |
Universidad Tecnológica de Bolívar |
bitstream.url.fl_str_mv |
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Mora, Camilo Andres847aa9ca-865b-4454-9bc9-796eb3654607Montoya, Oscar Danilo8a59ede1-6a4a-4d2e-abdc-d0afb14d4480Rivas Trujillo, Edwin0720b1ee-acdc-4aea-b24b-fc319c4dd61c2020-11-04T21:44:15Z2020-11-04T21:44:15Z2020-08-252020-11-04Mora, C.A.; Montoya, O.D.; Trujillo, E.R. Mixed-Integer Programming Model for Transmission Network Expansion Planning with Battery Energy Storage Systems (BESS). Energies 2020, 13, 4386.https://hdl.handle.net/20.500.12585/9548https://www.mdpi.com/1996-1073/13/17/438610.3390/en13174386Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThis article assesses the costs and benefits of incorporating battery energy storage systems (BESS) in transmission network expansion planning (TEP) over multiple time periods. We propose a mixed-integer programming model (MIP) for joint planning of the installation of battery energy storage systems (BESS) and construction of new transmission lines in multiple periods of time. The mathematical formulation of the presented model is based on the strategies of the agents of a transmission network to maximize their benefit, and on the operational restrictions of the power flows in transmission networks. This analysis is performed for the Garver 6 node test system takes into account the power losses in the lines and the restrictions for the energy stored in BESS. The power flows obtained with the MIP model are compared with AC power flows generated with specialized software for flows in power systems. This allows us to demonstrate the potential of models based on DC power flows to achieve approximate results applicable to the behavior and characteristics of real transmission networks. The results show that the BESS increase the net profit in the transmission networks and reduce their power losses.21 páginasapplication/pdfenghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2Energies 2020, 13(17), 4386Mixed-integer programming model for transmission network expansion planning with Battery Energy Storage Systems (BESS)info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_2df8fbb1Mixed-integer linear programmingTransmission expansion planningBattery energy storage systemsCartagena de IndiasPúblico generalGbadamosi, S.L.; Nwulu, N.I. A multi-period composite generation and transmission expansion planning model incorporating renewable energy sources and demand response. Sustain. Energy Technol. Assess. 2020, 39, 100726.Maghouli, P.; Hosseini, S.H.; Buygi, M.O.; Shahidehpour, M. A multi-objective framework for transmission expansion planning in deregulated environments. IEEE Trans. Power Syst. 2009, 24, 1051–1061.Rosellón, J. Different Approaches Towards Electricity Transmission Expansion. Rev. Netw. Econ. 2009, 2.Lumbreras, S.; Ramos, A. The new challenges to transmission expansion planning. Survey of recent practice and literature review. Electr. Power Syst. Res. 2016, 134, 19–29Aguado, J.A.; de la Torre, S.; Triviño, A. Battery energy storage systems in transmission network expansion planning. Electr. Power Syst. Res. 2017, 145, 63–72.Castro, T.E.G.; Jesus, L.L.M.; Trujillo, E.R. Literature review of BESS implementation in DER. Rev. Vínculos Cienc. Tecnol. Y Soc. 2019, 16, 321–326.Mazaheri, H.; Abbaspour, A.; Fotuhi-Firuzabad, M.; Farzin, H.; Moeini-Aghtaie, M. Investigating the impacts of energy storage systems on transmission expansion planning. In Proceedings of the 2017 25th Iranian Conference on Electrical Engineering, ICEE 2017, Tehran, Iran, 2–4 May 2017; pp. 1199–1203.Denholm, P.; Sioshansi, R. The value of compressed air energy storage with wind in transmission-constrained electric power systems. Energy Policy 2009, 37, 3149–3158.Wogrin, S.; Gayme, D.F. Optimizing Storage Siting, Sizing, and Technology Portfolios in TransmissionConstrained Networks. IEEE Trans. Power Syst. 2015, 30, 3304–3313.Zhang, F.; Hu, Z.; Song, Y. Mixed-integer linear model for transmission expansion planning with line losses and energy storage systems. IET Gener. Transm. Distrib. 2013, 7, 919–928Worighi, I.; Maach, A.; Hafid, A.; Hegazy, O.; van Mierlo, J. Integrating renewable energy in smart grid system: Architecture, virtualization and analysis. Sustain. Energy Grids Netw. 2019, 18, 100226.Nwulu, N.I.; Xia, X. Multi-objective dynamic economic emission dispatch of electric power generation integrated with game theory based demand response programs. Energy Convers. Manag. 2015, 89, 963–974.Aguado, J.A.; de la Torre, S.; Contreras, J.; Conejo, A.J.; Martínez, A. Market-driven dynamic transmission expansion planning. Electr. Power Syst. Res. 2012, 82, 88–94.de la Torre, S.; Conejo, A.J.; Contreras, J. Transmission expansion planning in electricity markets. IEEE Trans. Power Syst. 2008, 23, 238–248.Latorre, G.; Cruz, R.D.; Areiza, J.M.; Villegas, A. Classification of publications and models on transmission expansion planning. IEEE Trans. Power Syst. 2003, 18, 938–946.Garzillo, A.; Cazzol, M.V.; L’Abbate, A.; Migliavacca, G.; Mansoldox, A.; Riverax, A.; Nortonx, M. Offshore grids in Europe: The strategy of Ireland for 2020 and beyond. In Proceedings of the 9th IET International Conference on AC and DC Power Transmission (ACDC 2010), London, UK, 19–21 October 2010; Volume 2010, p. O64.Alguacil, N.; Motto, A.L.; Conejo, A.J. Transmission expansion planning: A mixed-integer LP approach. IEEE Trans. Power Syst. 2003, 18, 1070–1077.Zhang, H.; Heydt, G.T.; Vittal, V.; Quintero, J. An improved network model for transmission expansion planning considering reactive power and network losses. IEEE Trans. Power Syst. 2013, 28, 3471–3479.Youssef, H.K.; Hackam, R. New transmission planning model. IEEE Trans. Power Syst. 1989, 4, 9–18.Rahmani, M.; Rashidinejad, M.; Carreno, E.M.; Romero, R. Efficient method for AC transmission network expansion planning. Electr. Power Syst. Res. 2010, 80, 1056–1064.Qiu, T.; Xu, B.; Wang, Y.; Dvorkin, Y.; Kirschen, D.S. Stochastic Multistage Coplanning of Transmission Expansion and Energy Storage. IEEE Trans. Power Syst. 2017, 32, 643–651.Mexis, I.; Todeschini, G. Battery Energy Storage Systems in the United Kingdom: A Review of Current State-of-the-Art and Future Applications. Energies 2020, 13, 3616.Tsianikas, S.; Zhou, J.; Iii, D.P.B.; Coit, D.W. Economic trends and comparisons for optimizing grid-outage resilient photovoltaic and battery systems. Appl. Energy 2019.Marnell, K.; Obi, M.; Bass, R. Transmission-Scale Battery Energy Storage Systems: A Systematic Literature Review. Energies 2019, 12, 4603Villasana, R.; Salon, S.J.; Garver, L.L. Transmission network planning using linear programming. IEEE Trans. Power Appar. 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