A Distortion-Based Potential Game for Secondary Voltage Control in Micro-Grids
In this work, we present a multi-agent learning model based on the maximum entropy (MAXEnt) and the rate distortion function to define, respectively, the environment of the agents and their understanding about it. The avoidance of redundant information under distortion conditions is used to define a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9117110/ |
| _version_ | 1819276502507716608 |
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| author | David Alejandro Martinez Eduardo Mojica-Nava Ameena Saad Al-Sumaiti Sergio Rivera |
| author_facet | David Alejandro Martinez Eduardo Mojica-Nava Ameena Saad Al-Sumaiti Sergio Rivera |
| author_sort | David Alejandro Martinez |
| collection | DOAJ |
| description | In this work, we present a multi-agent learning model based on the maximum entropy (MAXEnt) and the rate distortion function to define, respectively, the environment of the agents and their understanding about it. The avoidance of redundant information under distortion conditions is used to define a distortion-based potential function that is minimized in order to find an equilibrium point in a potential game setting, in which the Lagrange multiplier β, used as input in the Blahut-Arimoto algorithm, determines the rationality in the learning process. The model performance is evaluated in a secondary voltage controller in order to achieve reactive power sharing between distributed generators (DGs) in a micro-grid. Simulation results demonstrate a good response in terms of reactive power distribution when the load is increased in a DG without considerable affectations in the voltage stability. |
| first_indexed | 2024-12-23T23:41:14Z |
| format | Article |
| id | doaj.art-5e58b885cb074c3ba781d04cb9ab18eb |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-23T23:41:14Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-5e58b885cb074c3ba781d04cb9ab18eb2022-12-21T17:25:40ZengIEEEIEEE Access2169-35362020-01-01811061111062210.1109/ACCESS.2020.30027139117110A Distortion-Based Potential Game for Secondary Voltage Control in Micro-GridsDavid Alejandro Martinez0https://orcid.org/0000-0001-9750-2653Eduardo Mojica-Nava1Ameena Saad Al-Sumaiti2https://orcid.org/0000-0002-7742-8596Sergio Rivera3https://orcid.org/0000-0002-2995-1147Department of Electrical and Electronics Engineering, Universidad Nacional de Colombia, Bogotá, ColombiaDepartment of Electrical and Electronics Engineering, Universidad Nacional de Colombia, Bogotá, ColombiaDepartment of Electrical Engineering and Computer Science, Khalifa University, Abu Dhabi, United Arab EmiratesDepartment of Electrical and Electronics Engineering, Universidad Nacional de Colombia, Bogotá, ColombiaIn this work, we present a multi-agent learning model based on the maximum entropy (MAXEnt) and the rate distortion function to define, respectively, the environment of the agents and their understanding about it. The avoidance of redundant information under distortion conditions is used to define a distortion-based potential function that is minimized in order to find an equilibrium point in a potential game setting, in which the Lagrange multiplier β, used as input in the Blahut-Arimoto algorithm, determines the rationality in the learning process. The model performance is evaluated in a secondary voltage controller in order to achieve reactive power sharing between distributed generators (DGs) in a micro-grid. Simulation results demonstrate a good response in terms of reactive power distribution when the load is increased in a DG without considerable affectations in the voltage stability.https://ieeexplore.ieee.org/document/9117110/Maximum entropymicro-gridspotential gamesrate distortion function |
| spellingShingle | David Alejandro Martinez Eduardo Mojica-Nava Ameena Saad Al-Sumaiti Sergio Rivera A Distortion-Based Potential Game for Secondary Voltage Control in Micro-Grids IEEE Access Maximum entropy micro-grids potential games rate distortion function |
| title | A Distortion-Based Potential Game for Secondary Voltage Control in Micro-Grids |
| title_full | A Distortion-Based Potential Game for Secondary Voltage Control in Micro-Grids |
| title_fullStr | A Distortion-Based Potential Game for Secondary Voltage Control in Micro-Grids |
| title_full_unstemmed | A Distortion-Based Potential Game for Secondary Voltage Control in Micro-Grids |
| title_short | A Distortion-Based Potential Game for Secondary Voltage Control in Micro-Grids |
| title_sort | distortion based potential game for secondary voltage control in micro grids |
| topic | Maximum entropy micro-grids potential games rate distortion function |
| url | https://ieeexplore.ieee.org/document/9117110/ |
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