Mitigating Energy System Vulnerability by Implementing a Microgrid with a Distributed Management Algorithm
This work presents a management strategy for microgrid (MG) operation. Photovoltaic (PV) and wind generators, as well as storage systems and conventional units, are distributed over a wide geographical area, forming a distributed energy system, which is coordinated to face any contingency of the uti...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-02-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/12/4/616 |
| _version_ | 1811185091950411776 |
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| author | Juan M. Lujano-Rojas José M. Yusta José Antonio Domínguez-Navarro |
| author_facet | Juan M. Lujano-Rojas José M. Yusta José Antonio Domínguez-Navarro |
| author_sort | Juan M. Lujano-Rojas |
| collection | DOAJ |
| description | This work presents a management strategy for microgrid (MG) operation. Photovoltaic (PV) and wind generators, as well as storage systems and conventional units, are distributed over a wide geographical area, forming a distributed energy system, which is coordinated to face any contingency of the utility company by means of its isolated operation. The management strategy divides the system into three main layers: renewable generation, storage devices, and conventional units. Interactions between devices of the same layer are determined by solving an economic dispatch problem (EDP) in a distributed manner using a consensus algorithm (CA), and interactions between layers are determined by means of a load following strategy. In this way, the complex behaviour of PV and wind generation, the battery storage system, and conventional units has been effectively combined with CA to solve EDP in a distributed manner. MG performance and its vulnerability are deeply analysed by means of an illustrative case study. From the observed results, vulnerability under extreme conditions could be reduced up to approximately 30% by coupling distributed renewable generation and storage capacity with an energy system based on conventional generation. |
| first_indexed | 2024-04-11T13:24:51Z |
| format | Article |
| id | doaj.art-7f81ce9578cf48ceb7dcae7a04567d28 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T13:24:51Z |
| publishDate | 2019-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-7f81ce9578cf48ceb7dcae7a04567d282022-12-22T04:22:07ZengMDPI AGEnergies1996-10732019-02-0112461610.3390/en12040616en12040616Mitigating Energy System Vulnerability by Implementing a Microgrid with a Distributed Management AlgorithmJuan M. Lujano-Rojas0José M. Yusta1José Antonio Domínguez-Navarro2Department of Electrical Engineering, University of Zaragoza, Calle María de Luna 3, 50018 Zaragoza, SpainDepartment of Electrical Engineering, University of Zaragoza, Calle María de Luna 3, 50018 Zaragoza, SpainDepartment of Electrical Engineering, University of Zaragoza, Calle María de Luna 3, 50018 Zaragoza, SpainThis work presents a management strategy for microgrid (MG) operation. Photovoltaic (PV) and wind generators, as well as storage systems and conventional units, are distributed over a wide geographical area, forming a distributed energy system, which is coordinated to face any contingency of the utility company by means of its isolated operation. The management strategy divides the system into three main layers: renewable generation, storage devices, and conventional units. Interactions between devices of the same layer are determined by solving an economic dispatch problem (EDP) in a distributed manner using a consensus algorithm (CA), and interactions between layers are determined by means of a load following strategy. In this way, the complex behaviour of PV and wind generation, the battery storage system, and conventional units has been effectively combined with CA to solve EDP in a distributed manner. MG performance and its vulnerability are deeply analysed by means of an illustrative case study. From the observed results, vulnerability under extreme conditions could be reduced up to approximately 30% by coupling distributed renewable generation and storage capacity with an energy system based on conventional generation.https://www.mdpi.com/1996-1073/12/4/616consensus algorithmvulnerabilitydynamic voltage collapsemaximum loadability index |
| spellingShingle | Juan M. Lujano-Rojas José M. Yusta José Antonio Domínguez-Navarro Mitigating Energy System Vulnerability by Implementing a Microgrid with a Distributed Management Algorithm Energies consensus algorithm vulnerability dynamic voltage collapse maximum loadability index |
| title | Mitigating Energy System Vulnerability by Implementing a Microgrid with a Distributed Management Algorithm |
| title_full | Mitigating Energy System Vulnerability by Implementing a Microgrid with a Distributed Management Algorithm |
| title_fullStr | Mitigating Energy System Vulnerability by Implementing a Microgrid with a Distributed Management Algorithm |
| title_full_unstemmed | Mitigating Energy System Vulnerability by Implementing a Microgrid with a Distributed Management Algorithm |
| title_short | Mitigating Energy System Vulnerability by Implementing a Microgrid with a Distributed Management Algorithm |
| title_sort | mitigating energy system vulnerability by implementing a microgrid with a distributed management algorithm |
| topic | consensus algorithm vulnerability dynamic voltage collapse maximum loadability index |
| url | https://www.mdpi.com/1996-1073/12/4/616 |
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