A Multiobjective Approach for the Optimal Placement of Protection and Control Devices in Distribution Networks with Microgrids
Protection and control systems represent an essential part of distribution networks by ensuring the physical integrity of components and by improving system reliability. Protection devices isolate a portion of the network affected by a fault, while control devices reduce the number of de-energized l...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2022 |
| País: | Brasil |
| Institución: | Universidade Estadual Paulista (UNESP) |
| Repositorio: | Repositório Institucional da UNESP |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.unesp.br:11449/239892 |
| Acceso en línea: | http://dx.doi.org/10.1109/ACCESS.2022.3166918 http://hdl.handle.net/11449/239892 |
| Access Level: | acceso abierto |
| Palabra clave: | compromise programming Distribution systems microgrids non-dominated sorting genetic algorithm protection system planning |
| Sumario: | Protection and control systems represent an essential part of distribution networks by ensuring the physical integrity of components and by improving system reliability. Protection devices isolate a portion of the network affected by a fault, while control devices reduce the number of de-energized loads by transferring loads to neighboring feeders. The integration of distributed generation has the potential to enhance the continuity of energy services through islanding operation during outage conditions. In this context, this study presents a multi-objective optimization approach for sizing and allocating protection and control devices in distribution networks with microgrids supplied by renewable energy sources. Reclosers, fuses, remote-controlled switches, and directional relays are considered in the formulation. Demand and generation uncertainties define the islanding operation and the load transfer possibilities. A non-dominated sorting genetic algorithm is applied in the solution of the allocation problem considering two conflicting objectives: cost of energy not supplied and equipment cost. The compromise programming is then performed to achieve the best solution from the Pareto front. The results show interesting setups for the protection system and viability of islanding operation. |
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