Algorithms for Optimal Power Flow Extended to Controllable Renewable Systems and Loads
In an effort to quantify and manage uncertainties inside power systems with penetration of renewable energy, uncertainty costs have been defined and different uncertainty cost functions have been calculated for different types of generators and electric vehicles. This article seeks to use the uncert...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-09-01
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| Series: | Algorithms |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-4893/14/10/276 |
| _version_ | 1797515590847430656 |
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| author | Elkin D. Reyes Sergio Rivera |
| author_facet | Elkin D. Reyes Sergio Rivera |
| author_sort | Elkin D. Reyes |
| collection | DOAJ |
| description | In an effort to quantify and manage uncertainties inside power systems with penetration of renewable energy, uncertainty costs have been defined and different uncertainty cost functions have been calculated for different types of generators and electric vehicles. This article seeks to use the uncertainty cost formulation to propose algorithms and solve the problem of optimal power flow extended to controllable renewable systems and controllable loads. In a previous study, the first and second derivatives of the uncertainty cost functions were calculated and now an analytical and heuristic algorithm of optimal power flow are used. To corroborate the analytical solution, the optimal power flow was solved by means of metaheuristic algorithms. Finally, it was found that analytical algorithms have a much higher performance than metaheuristic methods, especially as the number of decision variables in an optimization problem grows. |
| first_indexed | 2024-03-10T06:47:32Z |
| format | Article |
| id | doaj.art-a991338f97e4447e85fe175fa5755064 |
| institution | Directory Open Access Journal |
| issn | 1999-4893 |
| language | English |
| last_indexed | 2024-03-10T06:47:32Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj.art-a991338f97e4447e85fe175fa57550642023-11-22T17:08:11ZengMDPI AGAlgorithms1999-48932021-09-01141027610.3390/a14100276Algorithms for Optimal Power Flow Extended to Controllable Renewable Systems and LoadsElkin D. Reyes0Sergio Rivera1Electrical and Electronic Engineering, Universidad Nacional de Colombia, Sede Bogotá, Bogotá 111321, ColombiaElectrical and Electronic Engineering, Universidad Nacional de Colombia, Sede Bogotá, Bogotá 111321, ColombiaIn an effort to quantify and manage uncertainties inside power systems with penetration of renewable energy, uncertainty costs have been defined and different uncertainty cost functions have been calculated for different types of generators and electric vehicles. This article seeks to use the uncertainty cost formulation to propose algorithms and solve the problem of optimal power flow extended to controllable renewable systems and controllable loads. In a previous study, the first and second derivatives of the uncertainty cost functions were calculated and now an analytical and heuristic algorithm of optimal power flow are used. To corroborate the analytical solution, the optimal power flow was solved by means of metaheuristic algorithms. Finally, it was found that analytical algorithms have a much higher performance than metaheuristic methods, especially as the number of decision variables in an optimization problem grows.https://www.mdpi.com/1999-4893/14/10/276solarhydraulic and wind energy generationelectric vehiclesuncertainty cost functionmarginal costsuncertainty and risk analysis |
| spellingShingle | Elkin D. Reyes Sergio Rivera Algorithms for Optimal Power Flow Extended to Controllable Renewable Systems and Loads Algorithms solar hydraulic and wind energy generation electric vehicles uncertainty cost function marginal costs uncertainty and risk analysis |
| title | Algorithms for Optimal Power Flow Extended to Controllable Renewable Systems and Loads |
| title_full | Algorithms for Optimal Power Flow Extended to Controllable Renewable Systems and Loads |
| title_fullStr | Algorithms for Optimal Power Flow Extended to Controllable Renewable Systems and Loads |
| title_full_unstemmed | Algorithms for Optimal Power Flow Extended to Controllable Renewable Systems and Loads |
| title_short | Algorithms for Optimal Power Flow Extended to Controllable Renewable Systems and Loads |
| title_sort | algorithms for optimal power flow extended to controllable renewable systems and loads |
| topic | solar hydraulic and wind energy generation electric vehicles uncertainty cost function marginal costs uncertainty and risk analysis |
| url | https://www.mdpi.com/1999-4893/14/10/276 |
| work_keys_str_mv | AT elkindreyes algorithmsforoptimalpowerflowextendedtocontrollablerenewablesystemsandloads AT sergiorivera algorithmsforoptimalpowerflowextendedtocontrollablerenewablesystemsandloads |