Robust Next-Day Scheduling of PV Generation Sources Supplying a Standalone DC Microgrid via a Semi-Definite Programming Model
This study focuses on optimizing the efficient operation of standalone direct-current (DC) microgrids with photovoltaic (PV) sources using semi-definite programming (SDP) optimization. The PV source operation model is formulated as a nonlinear programming (NLP) problem with the objective of minimizi...
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IEEE
2024-01-01
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| Series: | IEEE Open Access Journal of Power and Energy |
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| Online Access: | https://ieeexplore.ieee.org/document/10589696/ |
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| author | Walter Gil-Gonzalez Oscar Danilo Montoya Luis F. Grisales-Norena Fabio Andrade |
| author_facet | Walter Gil-Gonzalez Oscar Danilo Montoya Luis F. Grisales-Norena Fabio Andrade |
| author_sort | Walter Gil-Gonzalez |
| collection | DOAJ |
| description | This study focuses on optimizing the efficient operation of standalone direct-current (DC) microgrids with photovoltaic (PV) sources using semi-definite programming (SDP) optimization. The PV source operation model is formulated as a nonlinear programming (NLP) problem with the objective of minimizing daily energy losses and reducing CO2 emissions compared to diesel generators. Transforming the NLP model into convex optimization involves a linear matrix model that combines positive semi-definite matrices with an affine space. This approach enhances robustness by incorporating uncertainties in demand and PV source power. The robust SDP model employs a min–max strategy for worst-case scenario energy management dispatch (EMD). Evaluating a 27-bus standalone DC microgrid, the SDP model outperforms random-based algorithms by achieving global optima in both objectives. Under uncertainties, the energy loss objective increases by 21.6706% with demand uncertainty, 0.3997% with PV source uncertainty, and 22.2009% with both. Meanwhile, the CO2 emissions objective increases by 11.9184%, 1.8237%, and 14.0045%, respectively. Additional simulations on an 85-node DC network confirm the efficacy of SDP in worst-case scenario EMD. All simulations utilized MATLAB’s Yalmip tool with the Mosek solver. |
| format | Article |
| id | doaj-art-48c145b1333848dd961a94610d35cacb |
| institution | Kabale University |
| issn | 2687-7910 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Access Journal of Power and Energy |
| spelling | doaj-art-48c145b1333848dd961a94610d35cacb2025-01-21T00:03:20ZengIEEEIEEE Open Access Journal of Power and Energy2687-79102024-01-011144645610.1109/OAJPE.2024.342537410589696Robust Next-Day Scheduling of PV Generation Sources Supplying a Standalone DC Microgrid via a Semi-Definite Programming ModelWalter Gil-Gonzalez0https://orcid.org/0000-0001-7609-1197Oscar Danilo Montoya1https://orcid.org/0000-0001-6051-4925Luis F. Grisales-Norena2https://orcid.org/0000-0002-1409-9756Fabio Andrade3https://orcid.org/0000-0002-8859-7336Grupo de Campos Electromagnéticos y Fenómenos Energéticos (CAFE), Facultad de Ingeniería, Universidad Tecnológica de Pereira, Pereira, ColombiaGrupo de Compatibilidad e Interferencia Electromagnética (GCEM), Facultad de Ingeniería, Universidad Distrital Francisco José de Caldas, Bogotá, ColombiaDepartment of Electrical Engineering, Faculty of Engineering, Universidad de Talca, Curico, ChileElectrical and Computer Engineering Department, University of Puerto Rico at Mayagüez, Mayagüez, PR, USAThis study focuses on optimizing the efficient operation of standalone direct-current (DC) microgrids with photovoltaic (PV) sources using semi-definite programming (SDP) optimization. The PV source operation model is formulated as a nonlinear programming (NLP) problem with the objective of minimizing daily energy losses and reducing CO2 emissions compared to diesel generators. Transforming the NLP model into convex optimization involves a linear matrix model that combines positive semi-definite matrices with an affine space. This approach enhances robustness by incorporating uncertainties in demand and PV source power. The robust SDP model employs a min–max strategy for worst-case scenario energy management dispatch (EMD). Evaluating a 27-bus standalone DC microgrid, the SDP model outperforms random-based algorithms by achieving global optima in both objectives. Under uncertainties, the energy loss objective increases by 21.6706% with demand uncertainty, 0.3997% with PV source uncertainty, and 22.2009% with both. Meanwhile, the CO2 emissions objective increases by 11.9184%, 1.8237%, and 14.0045%, respectively. Additional simulations on an 85-node DC network confirm the efficacy of SDP in worst-case scenario EMD. All simulations utilized MATLAB’s Yalmip tool with the Mosek solver.https://ieeexplore.ieee.org/document/10589696/Robust semi-definite programming optimizationdaily energy lossesenergy management dispatchstandalone direct-current microgridsphotovoltaic plantscarbon dioxide emissions |
| spellingShingle | Walter Gil-Gonzalez Oscar Danilo Montoya Luis F. Grisales-Norena Fabio Andrade Robust Next-Day Scheduling of PV Generation Sources Supplying a Standalone DC Microgrid via a Semi-Definite Programming Model IEEE Open Access Journal of Power and Energy Robust semi-definite programming optimization daily energy losses energy management dispatch standalone direct-current microgrids photovoltaic plants carbon dioxide emissions |
| title | Robust Next-Day Scheduling of PV Generation Sources Supplying a Standalone DC Microgrid via a Semi-Definite Programming Model |
| title_full | Robust Next-Day Scheduling of PV Generation Sources Supplying a Standalone DC Microgrid via a Semi-Definite Programming Model |
| title_fullStr | Robust Next-Day Scheduling of PV Generation Sources Supplying a Standalone DC Microgrid via a Semi-Definite Programming Model |
| title_full_unstemmed | Robust Next-Day Scheduling of PV Generation Sources Supplying a Standalone DC Microgrid via a Semi-Definite Programming Model |
| title_short | Robust Next-Day Scheduling of PV Generation Sources Supplying a Standalone DC Microgrid via a Semi-Definite Programming Model |
| title_sort | robust next day scheduling of pv generation sources supplying a standalone dc microgrid via a semi definite programming model |
| topic | Robust semi-definite programming optimization daily energy losses energy management dispatch standalone direct-current microgrids photovoltaic plants carbon dioxide emissions |
| url | https://ieeexplore.ieee.org/document/10589696/ |
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