Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids
This paper deals with the problem of optimal location and reallocation of battery energy storage systems (BESS) in direct current (dc) microgrids with constant power loads. The optimization model that represents this problem is formulated with two objective functions. The first model corresponds to...
- Autores:
-
Montoya, Oscar Danilo
Gil-González, Walter
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:20.500.12585/9518
- Palabra clave:
- Battery energy storage system
Economic dispatch problem
Nonlinear programming formulation
Optimal reallocation of batteries
Mathematical optimization
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids |
| title |
Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids |
| spellingShingle |
Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids Battery energy storage system Economic dispatch problem Nonlinear programming formulation Optimal reallocation of batteries Mathematical optimization |
| title_short |
Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids |
| title_full |
Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids |
| title_fullStr |
Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids |
| title_full_unstemmed |
Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids |
| title_sort |
Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids |
| dc.creator.fl_str_mv |
Montoya, Oscar Danilo Gil-González, Walter Rivas-Trujillo, Edwin |
| dc.contributor.author.none.fl_str_mv |
Montoya, Oscar Danilo Gil-González, Walter Rivas-Trujillo, Edwin |
| dc.subject.keywords.spa.fl_str_mv |
Battery energy storage system Economic dispatch problem Nonlinear programming formulation Optimal reallocation of batteries Mathematical optimization |
| topic |
Battery energy storage system Economic dispatch problem Nonlinear programming formulation Optimal reallocation of batteries Mathematical optimization |
| description |
This paper deals with the problem of optimal location and reallocation of battery energy storage systems (BESS) in direct current (dc) microgrids with constant power loads. The optimization model that represents this problem is formulated with two objective functions. The first model corresponds to the minimization of the total daily cost of buying energy in the spot market by conventional generators and the second to the minimization of the costs of the daily energy losses in all branches of the network. Both the models are constrained by classical nonlinear power flow equations, distributed generation capabilities, and voltage regulation, among others. These formulations generate a nonlinear mixed-integer programming (MINLP) model that requires special methods to be solved. A dc microgrid composed of 21-nodes with existing BESS is used for validating the proposed mathematical formula. This system allows to identify the optimal location or reallocation points for these batteries by improving the daily operative costs regarding the base cases. All the simulations are conducted via the general algebraic modeling system, widely known as the General Algebraic Modeling System (GAMS). |
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2020 |
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2020-10-30T16:40:40Z |
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2020-10-30T16:40:40Z |
| dc.date.issued.none.fl_str_mv |
2020-05-05 |
| dc.date.submitted.none.fl_str_mv |
2020-10-29 |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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info:eu-repo/semantics/publishedVersion |
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Artículo |
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publishedVersion |
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Montoya, O.D.; Gil-González, W.; Rivas-Trujillo, E. Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids. Energies 2020, 13, 2289. |
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https://hdl.handle.net/20.500.12585/9518 |
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https://www.mdpi.com/1996-1073/13/9/2289 |
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10.3390/en13092289 |
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Universidad Tecnológica de Bolívar |
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Repositorio Universidad Tecnológica de Bolívar |
| identifier_str_mv |
Montoya, O.D.; Gil-González, W.; Rivas-Trujillo, E. Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids. Energies 2020, 13, 2289. 10.3390/en13092289 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
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https://hdl.handle.net/20.500.12585/9518 https://www.mdpi.com/1996-1073/13/9/2289 |
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eng |
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eng |
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Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
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openAccess |
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20 páginas |
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Cartagena de Indias |
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Cartagena de Indias |
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Energies 2020, 13(9), 2289 |
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Universidad Tecnológica de Bolívar |
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Montoya, Oscar Danilo8a59ede1-6a4a-4d2e-abdc-d0afb14d4480Gil-González, Walterce1f5078-74c6-4b5c-b56a-784f85e52a08Rivas-Trujillo, Edwin0720b1ee-acdc-4aea-b24b-fc319c4dd61cCartagena de Indias2020-10-30T16:40:40Z2020-10-30T16:40:40Z2020-05-052020-10-29Montoya, O.D.; Gil-González, W.; Rivas-Trujillo, E. Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids. Energies 2020, 13, 2289.https://hdl.handle.net/20.500.12585/9518https://www.mdpi.com/1996-1073/13/9/228910.3390/en13092289Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThis paper deals with the problem of optimal location and reallocation of battery energy storage systems (BESS) in direct current (dc) microgrids with constant power loads. The optimization model that represents this problem is formulated with two objective functions. The first model corresponds to the minimization of the total daily cost of buying energy in the spot market by conventional generators and the second to the minimization of the costs of the daily energy losses in all branches of the network. Both the models are constrained by classical nonlinear power flow equations, distributed generation capabilities, and voltage regulation, among others. These formulations generate a nonlinear mixed-integer programming (MINLP) model that requires special methods to be solved. A dc microgrid composed of 21-nodes with existing BESS is used for validating the proposed mathematical formula. This system allows to identify the optimal location or reallocation points for these batteries by improving the daily operative costs regarding the base cases. All the simulations are conducted via the general algebraic modeling system, widely known as the General Algebraic Modeling System (GAMS).20 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(9), 2289Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgridsinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_2df8fbb1Battery energy storage systemEconomic dispatch problemNonlinear programming formulationOptimal reallocation of batteriesMathematical optimizationCartagena de IndiasPúblico generalCouncil, G.W.E. Global Status of Wind Power. 2018. Available online: http://gwec.net/global-figures/ windenergy-global-status (accessed on 20 March 2020).Strunz, K.; Abbasi, E.; Huu, D.N. 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Energies 2019, 12, 4494.Gil-González, W.; Montoya, O.D.; Garces, A. Control of a SMES for mitigating subsynchronous oscillations in power systems: A PBC-PI approach. J. Energy Storage 2018, 20, 163–172.Essallah, S.; Khedher, A.; Bouallegue, A. Integration of distributed generation in electrical grid: Optimal placement and sizing under different load conditions. Comput. Electr. Eng. 2019, 79, 106461.Montoya, O.D.; Gil-González, W.; Garrido, V. Voltage Stability Margin in DC Grids with CPLs: A Recursive Newton–Raphson Approximation. IEEE Trans. Circuits Syst. II Express Briefs 2020, 67, 300–304.Garces, A. Uniqueness of the power flow solutions in low voltage direct current grids. Electr. Power Syst. Res. 2017, 151, 149–153.Lotfi, H.; Khodaei, A. AC versus DC microgrid planning. IEEE Trans. Smart Grid 2015, 8, 296–304.Nojavan, S.; Pashaei-Didani, H.; Mohammadi, A.; Ahmadi-Nezamabad, H. Energy management concept of AC, DC, and hybrid AC/DC microgrids. In Risk-Based Energy Management; Elsevier: Amsterdam, The Netherlands, 2020; pp. 1–10.Gil-González, W.; Montoya, O.D.; Grisales-Noreña, L.F.; Cruz-Peragón, F.; Alcalá, G. Economic Dispatch of Renewable Generators and BESS in DC Microgrids Using Second-Order Cone Optimization. Energies 2020, 13, 1703.Montoya, O.D.; Grisales-Noreña, L.F.; Gil-González, W.; Alcalá, G.; Hernandez-Escobedo, Q. Optimal Location and Sizing of PV Sources in DC Networks for Minimizing Greenhouse Emissions in Diesel Generators. Symmetry 2020, 12, 322.Hu, J.; Shan, Y.; Xu, Y.; Guerrero, J.M. A coordinated control of hybrid ac/dc microgrids with PV-wind-battery under variable generation and load conditions. Int. J. Elec. Power 2019, 104, 583–592.Kazmi, S.A.A.; Shahzad, M.K.; Khan, A.Z.; Shin, D.R. Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective. Energies 2017, 10, 501.Siano, P.; Rigatos, G.; Piccolo, A. Active Distribution Networks and Smart Grids: Optimal Allocation of Wind Turbines by Using Hybrid GA and Multi-Period OPF. In Atlantis Computational Intelligence Systems; Atlantis Press: Paris, France, 2012; pp. 579–599.Becker, D.J.; Sonnenberg, B.J. DC microgrids in buildings and data centers. In Proceedings of the 2011 IEEE 33rd International Telecommunications Energy Conference (INTELEC), Amsterdam, The Netherlands, 9–13 October 2011; pp. 1–7.Noritake, M.; Yuasa, K.; Takeda, T.; Hoshi, H.; Hirose, K. Demonstrative research on DC microgrids for office buildings. In Proceedings of the 2014 IEEE 36th International Telecommunications Energy Conference (INTELEC), Vancouver, BC, Canada, 28 September–2 October 2014; pp. 1–5.Mackay, L.; van der Blij, N.H.; Ramirez-Elizondo, L.; Bauer, P. Toward the Universal DC Distribution System. Electr. Power Compon. Syst. 2017, 45, 1032–1042.Jing,W.; Lai, C.H.;Wong, S.H.W.;Wong, M.L.D. Battery-supercapacitor hybrid energy storage system in standalone DC microgrids: A review. IET Renew. Power Gener. 2017, 11, 461–469.Weaver, W.W.; Robinett, R.D.; Parker, G.G.; Wilson, D.G. Energy storage requirements of dc microgrids with high penetration renewables under droop control. Int. J. Electr. Power Energy Syst. 2015, 68, 203–209.Li, Y.; Meng, K.; Dong, Z.Y.; Zhang,W. Sliding Framework for Inverter-Based Microgrid Control. IEEE Trans. Power Syst. 2020, 35, 1657–1660.Azimi, S.M.; Hamzeh, M. Adaptive Interconnection and Damping Assignment Passivity-Based Control of Interlinking Converter in Hybrid AC/DC Grids. IEEE Syst. J. 2020.Guo, Z.; Li, S.; Zheng, Y. Feedback linearization based distributed model predictive control for secondary control of islanded microgrid. Asian J. Control 2020.Garcés, A. Convex Optimization for the Optimal Power Flow on DC Distribution Systems. In Handbook of Optimization in Electric Power Distribution Systems; Springer: Cham, Switzerland, 2020; pp. 121–137.Chen, C.; Duan, S.; Cai, T.; Liu, B.; Hu, G. Optimal Allocation and Economic Analysis of Energy Storage System in Microgrids. IEEE Trans. Power Electron. 2011, 26, 2762–2773.Gil-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. J. Energy Storage 2019, 21, 1–8.Li, Y.; Wang, C.; Li, G.; Wang, J.; Zhao, D.; Chen, C. Improving operational flexibility of integrated energy system with uncertain renewable generations considering thermal inertia of buildings. Energy Convers. Manag. 2020, 207, 112526.Montoya, O.D.; Grajales, A.; Garces, A.; Castro, C.A. Distribution Systems Operation Considering Energy Storage Devices and Distributed Generation. IEEE Latin Am. Trans. 2017, 15, 890–900.Grisales-Noreña, L.; Montoya, O.D.; Gil-González, W. Integration of energy storage systems in AC distribution networks: Optimal location, selecting, and operation approach based on genetic algorithms.Garcés, A.; Montoya, O.D. A Potential Function for the Power Flow in DC Microgrids: An Analysis of the Uniqueness and Existence of the Solution and Convergence of the Algorithms. J. Control. Autom. Electr. Syst. 2019, 30, 794–801.Zia, M.F.; Elbouchikhi, E.; Benbouzid, M.; Guerrero, J.M. Energy management system for an islanded microgrid with convex relaxation. IEEE Trans. Ind. Appl. 2019, 55, 7175–7185.Montoya, O.D.; Gil-González, W.; Grisales-Noreña, L. Relaxed convex model for optimal location and sizing of DGs in DC grids using sequential quadratic programming and random hyperplane approaches. Int. J. Electr. Power Energy Syst. 2020, 115, 105442.Luna, A.C.; Diaz, N.L.; Andrade, F.; Graells, M.; Guerrero, J.M.; Vasquez, J.C. Economic power dispatch of distributed generators in a grid-connected microgrid. In Proceedings of the 2015 9th International Conference on Power Electronics and ECCE Asia (ICPE-ECCE Asia), Seoul, Korea, 1–5 June 2015; pp. 1161–1168.Montoya, O.D.; Gil-González,W.; Grisales-Noreña, L. An exact MINLP model for optimal location and sizing of DGs in distribution networks: A general algebraic modeling system approach. Ain Shams Eng. 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