Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves
This paper presents an optimization model for the optimal placement and sizing of wind turbines, considering their reactive power capacity, wind speed, and demand curves. The optimization model is nonlinear and is focused on minimizing power losses in AC distribution networks. Also, paired wind turb...
- Autores:
-
Gil-González, Walter
Montoya, Oscar Danilo
Grisales-Noreña, Luis Fernando
Perea-Moreno, Alberto-Jesus
Hernandez-Escobedo, Quetzalcoatl
- 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:20.500.12585/9521
- Palabra clave:
- Wind power generation
Artificial neural networks
Chargeability factor
Reactive power capacity
Wind speed and demand curves
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves |
| title |
Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves |
| spellingShingle |
Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves Wind power generation Artificial neural networks Chargeability factor Reactive power capacity Wind speed and demand curves |
| title_short |
Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves |
| title_full |
Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves |
| title_fullStr |
Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves |
| title_full_unstemmed |
Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves |
| title_sort |
Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves |
| dc.creator.fl_str_mv |
Gil-González, Walter Montoya, Oscar Danilo Grisales-Noreña, Luis Fernando Perea-Moreno, Alberto-Jesus Hernandez-Escobedo, Quetzalcoatl |
| dc.contributor.author.none.fl_str_mv |
Gil-González, Walter Montoya, Oscar Danilo Grisales-Noreña, Luis Fernando Perea-Moreno, Alberto-Jesus Hernandez-Escobedo, Quetzalcoatl |
| dc.subject.keywords.spa.fl_str_mv |
Wind power generation Artificial neural networks Chargeability factor Reactive power capacity Wind speed and demand curves |
| topic |
Wind power generation Artificial neural networks Chargeability factor Reactive power capacity Wind speed and demand curves |
| description |
This paper presents an optimization model for the optimal placement and sizing of wind turbines, considering their reactive power capacity, wind speed, and demand curves. The optimization model is nonlinear and is focused on minimizing power losses in AC distribution networks. Also, paired wind turbine and power conversion systems are treated via chargeability factor η at the peak hour. This factor represents the percentage of usage of the power conversion system in the nominal wind speed conditions, and allows to support reactive power dynamically during all periods of the day as a function of the distribution system requirements. In addition, an artificial neural network is used for short-term forecasting to deal with uncertainties in wind power generation. We assume that the number of wind power distributed generators could be from zero to three generators integrated into the system, considering unit power factors and reactive power injections to follow up the effect of reactive power compensation in the daily operation. The General Algebraic Modeling System (GAMS) is employed to solve the proposed optimization model. |
| publishDate |
2020 |
| dc.date.accessioned.none.fl_str_mv |
2020-10-30T18:43:19Z |
| dc.date.available.none.fl_str_mv |
2020-10-30T18:43:19Z |
| dc.date.issued.none.fl_str_mv |
2020-04-08 |
| dc.date.submitted.none.fl_str_mv |
2020-10-28 |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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info:eu-repo/semantics/article |
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info:eu-repo/semantics/publishedVersion |
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Artículo |
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publishedVersion |
| dc.identifier.citation.spa.fl_str_mv |
Gil-González, W.; Montoya, O.D.; Grisales-Noreña, L.F.; Perea-Moreno, A.-J.; Hernandez-Escobedo, Q. Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves. Sustainability 2020, 12, 2983. |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/9521 |
| dc.identifier.url.none.fl_str_mv |
https://www.mdpi.com/2071-1050/12/7/2983 |
| dc.identifier.doi.none.fl_str_mv |
10.3390/su12072983 |
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Universidad Tecnológica de Bolívar |
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Repositorio Universidad Tecnológica de Bolívar |
| identifier_str_mv |
Gil-González, W.; Montoya, O.D.; Grisales-Noreña, L.F.; Perea-Moreno, A.-J.; Hernandez-Escobedo, Q. Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves. Sustainability 2020, 12, 2983. 10.3390/su12072983 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
| url |
https://hdl.handle.net/20.500.12585/9521 https://www.mdpi.com/2071-1050/12/7/2983 |
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eng |
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eng |
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http://purl.org/coar/access_right/c_abf2 |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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info:eu-repo/semantics/openAccess |
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Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://purl.org/coar/access_right/c_abf2 |
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openAccess |
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20 páginas |
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application/pdf |
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Cartagena de Indias |
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Sustainability 2020, 12(7), 2983 |
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Universidad Tecnológica de Bolívar |
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Gil-González, Walterce1f5078-74c6-4b5c-b56a-784f85e52a08Montoya, Oscar Danilo8a59ede1-6a4a-4d2e-abdc-d0afb14d4480Grisales-Noreña, Luis Fernando7c27cda4-5fe4-4686-8f72-b0442c58a5d1Perea-Moreno, Alberto-Jesuse78da438-8ed5-40ab-a12c-74e84e6d691bHernandez-Escobedo, Quetzalcoatl6d13cf66-c5cb-46ae-9a39-26767b00d93d2020-10-30T18:43:19Z2020-10-30T18:43:19Z2020-04-082020-10-28Gil-González, W.; Montoya, O.D.; Grisales-Noreña, L.F.; Perea-Moreno, A.-J.; Hernandez-Escobedo, Q. Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves. Sustainability 2020, 12, 2983.https://hdl.handle.net/20.500.12585/9521https://www.mdpi.com/2071-1050/12/7/298310.3390/su12072983Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThis paper presents an optimization model for the optimal placement and sizing of wind turbines, considering their reactive power capacity, wind speed, and demand curves. The optimization model is nonlinear and is focused on minimizing power losses in AC distribution networks. Also, paired wind turbine and power conversion systems are treated via chargeability factor η at the peak hour. This factor represents the percentage of usage of the power conversion system in the nominal wind speed conditions, and allows to support reactive power dynamically during all periods of the day as a function of the distribution system requirements. In addition, an artificial neural network is used for short-term forecasting to deal with uncertainties in wind power generation. We assume that the number of wind power distributed generators could be from zero to three generators integrated into the system, considering unit power factors and reactive power injections to follow up the effect of reactive power compensation in the daily operation. The General Algebraic Modeling System (GAMS) is employed to solve the proposed optimization model.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_abf2Sustainability 2020, 12(7), 2983Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curvesinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_2df8fbb1Wind power generationArtificial neural networksChargeability factorReactive power capacityWind speed and demand curvesCartagena de IndiasPúblico generalMazhari, S.M.; Monsef, H.; Romero, R. A multi-objective distribution system expansion planning incorporating customer choices on reliability. IEEE Trans. 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Economic Dispatch of BESS and Renewable Generators in DC Microgrids Using Voltage-Dependent Load Models. Energies 2019, 12, 4494.Cisneros, R.; Mancilla-David, F.; Ortega, R. Passivity-Based Control of a Grid-Connected Small-Scale Windmill With Limited Control Authority. IEEE J. Emerg. Sel. Top. Power Electron. 2013, 1, 247–259.Namazi, M.M.; Nejad, S.M.S.; Tabesh, A.; Rashidi, A.; Liserre, M. Passivity-Based Control of Switched Reluctance-Based Wind System Supplying Constant Power Load. IEEE Trans. Ind. Electron. 2018, 65, 9550–9560.Barambones, O. Sliding Mode Control Strategy for Wind Turbine Power Maximization. Energies 2012, 5, 2310–2330.Lee, S.W.; Chun, K.H. Adaptive Sliding Mode Control for PMSG Wind Turbine Systems. Energies 2019, 12, 595.Alrifai, M.; Zribi, M.; Rayan, M. Feedback Linearization Controller for a Wind Energy Power System. Energies 2016, 9, 771.Li, P.; Wang, J.; Xiong, L.; Wu, F. 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