Distribution systems resilience improvement utilizing multiple operational resources
dc.contributor.author | Home-Ortiz, Juan M. | |
dc.contributor.author | Melgar-Dominguez, Ozy D. | |
dc.contributor.author | Javadi, Mohammad S. | |
dc.contributor.author | Santos, Sérgio F. | |
dc.contributor.author | Mantovani, José Roberto Sanches | |
dc.contributor.author | Catalão, João P. S. | |
dc.contributor.author | Santos, Sérgio F. | |
dc.date.accessioned | 2022-09-06T10:07:27Z | |
dc.date.available | 2022-09-06T10:07:27Z | |
dc.date.issued | 2021-11-03 | |
dc.description.abstract | This paper presents a strategy based on mixed-integer linear programing (MILP) model to improve the resilience in electric distribution systems (EDSs). The restoration process considers operational resources such as the optimal coordination of dynamic switching operations, islanding operation of distributed generation (DG) units, and displacement of mobile emergency generation (MEG) units. In addition, the benefits of considering a demand response (DR) program to improve the recoverability of the system are also studied. The switching operations aim to separate the in-service from the out-of-service part of the system keeping the radiality of the grid. The proposed MILP model is formulated as a stochastic scenario-based problem where the uncertainties are associated with PV-based power generation and demand consumption. The objective function minimizes the amount of energy load shedding after fault, and the generation curtailment of the PV-based DG. To validate the proposed strategy, a 33-bus EDS is analyzed under different test cases. Results show the benefits of coordinating the dynamic switching operations, the optimal scheduling of MEG units, and a demand response program during the restoration process. | pt_PT |
dc.identifier.citation | Home-Ortiz, J. M., Melgar-Dominguez, O. D., Javadi, M. S., Santos, S. F., Mantovani, J. R. S. & Catalao, J. P. S. (2021). Distribution systems resilience improvement utilizing multiple operational resources. In 2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), Bari, Italy, 7th-10th September 2021 (pp. 1-6). 10.1109/EEEIC/ICPSEurope51590.2021.9584831. Repositório Institucional UPT. http://hdl.handle.net/11328/4427 | pt_PT |
dc.identifier.doi | 10.1109/EEEIC/ICPSEurope51590.2021.9584831 | pt_PT |
dc.identifier.isbn | 978-1-6654-3613-7 (Electronic) | |
dc.identifier.uri | http://hdl.handle.net/11328/4427 | |
dc.language.iso | eng | pt_PT |
dc.peerreviewed | yes | pt_PT |
dc.publisher | IEEE | pt_PT |
dc.relation | Support by FEDER funds through COMPETE 2020 and by Portuguese funds through FCT, under POCI-01-0145-FEDER-029803 (02/SAICT/2017). | pt_PT |
dc.rights | open access | pt_PT |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
dc.subject | Demand response | pt_PT |
dc.subject | Dynamic restoration | pt_PT |
dc.subject | Islanding operation | pt_PT |
dc.subject | Mobile emergency generators | pt_PT |
dc.subject | PV-based generation | pt_PT |
dc.subject | Resilience enhancement. | pt_PT |
dc.title | Distribution systems resilience improvement utilizing multiple operational resources | pt_PT |
dc.type | conferenceObject | pt_PT |
degois.publication.firstPage | 1 | pt_PT |
degois.publication.lastPage | 6 | pt_PT |
degois.publication.location | Bari, Italy | pt_PT |
degois.publication.title | 2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) | pt_PT |
dspace.entity.type | Publication | en |
person.affiliation.name | REMIT – Research on Economics, Management and Information Technologies | |
person.familyName | Santos | |
person.givenName | Sérgio F. | |
person.identifier.ciencia-id | E41A-D6C6-E3D7 | |
person.identifier.orcid | 0000-0003-3277-2833 | |
person.identifier.rid | GNM-6353-2022 | |
person.identifier.scopus-author-id | 56483358000 | |
relation.isAuthorOfPublication | d0a5755c-d682-4ead-bf2a-ce1ad6c63ede | |
relation.isAuthorOfPublication.latestForDiscovery | d0a5755c-d682-4ead-bf2a-ce1ad6c63ede |
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