Optimal Location and Sizing of PV Sources in DC Networks for Minimizing Greenhouse Emissions in Diesel Generators
This paper addresses the problem of the optimal location and sizing of photovoltaic (PV) sources in direct current (DC) electrical networks considering time-varying load and renewable generation curves. To represent this problem, a mixed-integer nonlinear programming (MINLP) model is developed. The...
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| Format: | Article |
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MDPI AG
2020-02-01
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| Series: | Symmetry |
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| Online Access: | https://www.mdpi.com/2073-8994/12/2/322 |
| _version_ | 1818000969139486720 |
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| author | Oscar Danilo Montoya Luis Fernando Grisales-Noreña Walter Gil-González Gerardo Alcalá Quetzalcoatl Hernandez-Escobedo |
| author_facet | Oscar Danilo Montoya Luis Fernando Grisales-Noreña Walter Gil-González Gerardo Alcalá Quetzalcoatl Hernandez-Escobedo |
| author_sort | Oscar Danilo Montoya |
| collection | DOAJ |
| description | This paper addresses the problem of the optimal location and sizing of photovoltaic (PV) sources in direct current (DC) electrical networks considering time-varying load and renewable generation curves. To represent this problem, a mixed-integer nonlinear programming (MINLP) model is developed. The main idea of including PV sources in the DC grid is minimizing the total greenhouse emissions produced by diesel generators in isolated areas. An artificial neural network is employed for short-term forecasting to deal with uncertainties in the PV power generation. The general algebraic modeling system (GAMS) package is employed to solve the MINLP model by using the CONOPT solver that works with mixed and integer variables. Numerical results demonstrate important reductions of harmful gas emissions to the atmosphere when PV sources are optimally integrated (size and location) to the DC grid. |
| first_indexed | 2024-04-14T03:28:04Z |
| format | Article |
| id | doaj.art-57448a1607bb4f1cbf282e68e0483f56 |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-04-14T03:28:04Z |
| publishDate | 2020-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-57448a1607bb4f1cbf282e68e0483f562022-12-22T02:15:04ZengMDPI AGSymmetry2073-89942020-02-0112232210.3390/sym12020322sym12020322Optimal Location and Sizing of PV Sources in DC Networks for Minimizing Greenhouse Emissions in Diesel GeneratorsOscar Danilo Montoya0Luis Fernando Grisales-Noreña1Walter Gil-González2Gerardo Alcalá3Quetzalcoatl Hernandez-Escobedo4Facultad de Ingeniería, Universidad Distrital Francisco José de Caldas, Carrera 7 No. 40B - 53, Bogotá D.C 11021, ColombiaDepartamento de Electromecánica y Mecratrónica, Instituto Tecnológico Metropolitano, Medellín 050012, ColombiaLaboratorio Inteligente de Energía, Universidad Tecnológica de Bolívar, Km 1 vía Turbaco, Cartagena 131001, ColombiaCentro de Investigación en Recursos Energéticos y Sustentables, Universidad Veracruzana, Coatzacoalcos, Veracruz 96535, MexicoEscuela Nacional de Estudios Superiores Juriquilla, UNAM, Queretaro 76230, MexicoThis paper addresses the problem of the optimal location and sizing of photovoltaic (PV) sources in direct current (DC) electrical networks considering time-varying load and renewable generation curves. To represent this problem, a mixed-integer nonlinear programming (MINLP) model is developed. The main idea of including PV sources in the DC grid is minimizing the total greenhouse emissions produced by diesel generators in isolated areas. An artificial neural network is employed for short-term forecasting to deal with uncertainties in the PV power generation. The general algebraic modeling system (GAMS) package is employed to solve the MINLP model by using the CONOPT solver that works with mixed and integer variables. Numerical results demonstrate important reductions of harmful gas emissions to the atmosphere when PV sources are optimally integrated (size and location) to the DC grid.https://www.mdpi.com/2073-8994/12/2/322artificial neural networksdiesel generationdirect current networksgreenhouse emissionsnumerical optimizationmixed-integer nonlinear programming photovoltaic plants |
| spellingShingle | Oscar Danilo Montoya Luis Fernando Grisales-Noreña Walter Gil-González Gerardo Alcalá Quetzalcoatl Hernandez-Escobedo Optimal Location and Sizing of PV Sources in DC Networks for Minimizing Greenhouse Emissions in Diesel Generators Symmetry artificial neural networks diesel generation direct current networks greenhouse emissions numerical optimization mixed-integer nonlinear programming photovoltaic plants |
| title | Optimal Location and Sizing of PV Sources in DC Networks for Minimizing Greenhouse Emissions in Diesel Generators |
| title_full | Optimal Location and Sizing of PV Sources in DC Networks for Minimizing Greenhouse Emissions in Diesel Generators |
| title_fullStr | Optimal Location and Sizing of PV Sources in DC Networks for Minimizing Greenhouse Emissions in Diesel Generators |
| title_full_unstemmed | Optimal Location and Sizing of PV Sources in DC Networks for Minimizing Greenhouse Emissions in Diesel Generators |
| title_short | Optimal Location and Sizing of PV Sources in DC Networks for Minimizing Greenhouse Emissions in Diesel Generators |
| title_sort | optimal location and sizing of pv sources in dc networks for minimizing greenhouse emissions in diesel generators |
| topic | artificial neural networks diesel generation direct current networks greenhouse emissions numerical optimization mixed-integer nonlinear programming photovoltaic plants |
| url | https://www.mdpi.com/2073-8994/12/2/322 |
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