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dc.contributor.author
Feroldi, Diego Hernán  
dc.contributor.author
Rullo, Pablo Gabriel  
dc.date.available
2023-11-15T19:03:36Z  
dc.date.issued
2022-12  
dc.identifier.citation
Feroldi, Diego Hernán; Rullo, Pablo Gabriel; Day-ahead optimal operation of active distribution networks with distributed generation and energy storage; De Gruyter; International Journal of Emerging Electric Power Systems; 12-2022; 1-14  
dc.identifier.issn
2194-5756  
dc.identifier.uri
http://hdl.handle.net/11336/218253  
dc.description.abstract
In this work we address the optimal operation in active distribution networks (ADNs) with high penetration of renewable energies and energy storage. The optimal performance of ADNs can include two different optimization problems: Unit Commitment (UC) and Economic Dispatch (ED). The UC problem determines the start-up and shutdown planning of all the dispatchable generation units to supply the electricity demand, minimizing the total cost of operation, while the ED problem determines the active output power of each of the committed units for each hour of the planning horizon. Both problems have the objectives of minimizing the total cost, supplying the demand and complying with the restrictions of the main network. Here the two problems are solved together to achieve the day-ahead optimal operation of active distribution networks with distributed generation and energy storage. A test system based on the IEEE 33-bus distribution network was proposed. The optimal operation problem presented here is analyzed using four scenarios with different renewable generation and load conditions and a time-varying profile for the purchase price of energy from the network. The results reveal that the proposed network together with the optimization methodology can face diverse and highly demanding load situations, with the full use of renewable energies and complying with all the restrictions imposed. The proposed methodology is suitable for use in other optimization problems such as determining the sizing of storage units and distributed generation.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
De Gruyter  
dc.rights
info:eu-repo/semantics/restrictedAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
ACTIVE DISTRIBUTION NETWORKS  
dc.subject
DISTRIBUTED GENERATION  
dc.subject
ECONOMIC DISPATCH  
dc.subject
MIXED INTEGER LINEAR PROGRAMMING (MILP)  
dc.subject
UNIT COMMITMENT  
dc.subject.classification
Ingeniería Eléctrica y Electrónica  
dc.subject.classification
Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información  
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS  
dc.title
Day-ahead optimal operation of active distribution networks with distributed generation and energy storage  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2023-11-15T15:47:21Z  
dc.identifier.eissn
1553-779X  
dc.journal.pagination
1-14  
dc.journal.pais
Alemania  
dc.journal.ciudad
Berlín  
dc.description.fil
Fil: Feroldi, Diego Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina  
dc.description.fil
Fil: Rullo, Pablo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Tecnológica Nacional. Facultad Regional San Nicolás; Argentina  
dc.journal.title
International Journal of Emerging Electric Power Systems  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.degruyter.com/document/doi/10.1515/ijeeps-2022-0222/html  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1515/ijeeps-2022-0222