Evolutionary framework for multi-dimensional signaling method applied to energy dispatch problems in smart grids
| Main Authors: | Fernando Lezama, Enrique Munoz de Cote, Luis Enrique Sucar, João Soares, Zita Vale |
|---|---|
| Format: | Proceeding Journal |
| Bahasa: | eng |
| Terbitan: |
, 2017
|
| Online Access: |
https://zenodo.org/record/1193313 |
| ctrlnum |
1193313 |
|---|---|
| fullrecord |
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<dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><creator>Fernando Lezama</creator><creator>Enrique Munoz de Cote</creator><creator>Luis Enrique Sucar</creator><creator>João Soares</creator><creator>Zita Vale</creator><date>2017-10-19</date><description>In the smart grid (SG) era, the energy resource management (ERM) in power systems is facing an increase in complexity, mainly due to the high penetration of distributed resources, such as renewable energy and electric vehicles (EVs). Therefore, advanced control techniques and sophisticated planning tools are required to take advantage of the benefits that SG technologies can provide. In this paper, we introduce a new approach called multi-dimensional signaling evolutionary algorithm (MDS-EA) to solve the large-scale ERM problem in SGs. The proposed method uses the general framework from evolutionary algorithms (EAs), combined with a previously proposed rule-based mechanism called multi-dimensional signaling (MDS). In this way, the proposed MDS-EA evolves a population of solutions by modifying variables of interest identified during the evaluation process. Results show that the proposed method can reduce the complexity of metaheuristics implementation while achieving competitive solutions compared with EAs and deterministic approaches in acceptable times.</description><description>The present work was done and funded in the
scope of the projects: Project NetEffiCity (ANI—P2020
18015), and from FEDER Funds through COMPETE
program and from National Funds through FCT under
the project UID/EEA/00760/2013; Sustainability Fund
CONACYT-SENER by Consejo Nacional de Ciencia y Tecnolog´ıa
(CONACYT) and the National Center of Innovation
in Energy (CEMIE-Eolico, Project No. 206842).</description><identifier>https://zenodo.org/record/1193313</identifier><identifier>10.1109/ISAP.2017.8071418</identifier><identifier>oai:zenodo.org:1193313</identifier><language>eng</language><relation>info:eu-repo/grantAgreement/FCT/5876/147448/</relation><rights>info:eu-repo/semantics/openAccess</rights><rights>https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode</rights><title>Evolutionary framework for multi-dimensional signaling method applied to energy dispatch problems in smart grids</title><type>Journal:Proceeding</type><type>Journal:Proceeding</type><recordID>1193313</recordID></dc>
|
| language |
eng |
| format |
Journal:Proceeding Journal Journal:Journal |
| author |
Fernando Lezama Enrique Munoz de Cote Luis Enrique Sucar João Soares Zita Vale |
| title |
Evolutionary framework for multi-dimensional signaling method applied to energy dispatch problems in smart grids |
| publishDate |
2017 |
| url |
https://zenodo.org/record/1193313 |
| contents |
In the smart grid (SG) era, the energy resource management (ERM) in power systems is facing an increase in complexity, mainly due to the high penetration of distributed resources, such as renewable energy and electric vehicles (EVs). Therefore, advanced control techniques and sophisticated planning tools are required to take advantage of the benefits that SG technologies can provide. In this paper, we introduce a new approach called multi-dimensional signaling evolutionary algorithm (MDS-EA) to solve the large-scale ERM problem in SGs. The proposed method uses the general framework from evolutionary algorithms (EAs), combined with a previously proposed rule-based mechanism called multi-dimensional signaling (MDS). In this way, the proposed MDS-EA evolves a population of solutions by modifying variables of interest identified during the evaluation process. Results show that the proposed method can reduce the complexity of metaheuristics implementation while achieving competitive solutions compared with EAs and deterministic approaches in acceptable times. The present work was done and funded in the scope of the projects: Project NetEffiCity (ANI—P2020 18015), and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013; Sustainability Fund CONACYT-SENER by Consejo Nacional de Ciencia y Tecnolog ́ıa (CONACYT) and the National Center of Innovation in Energy (CEMIE-Eolico, Project No. 206842). |
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IOS16997.1193313 |
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ZAIN Publications |
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7213 |
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library:special library |
| library |
Cognizance Journal of Multidisciplinary Studies |
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5267 |
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Cognizance Journal of Multidisciplinary Studies |
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16997 |
| subject_area |
Multidisciplinary |
| city |
Stockholm |
| province |
INTERNASIONAL |
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1 |
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2022-06-06T04:23:20Z |
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