An improved C-DEEPSO algorithm for optimal active-reactive power dispatch in microgrids with electric vehicles
In the last years, our society's high energy demand has led to the proposal of novel ways of consuming and producing electricity. In this sense, many countries have encouraged micro generation, including the use of renewable sources such as solar irradiation and wind generation, or considering...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universidad de Alcalá (UAH) |
| Repositorio: | e_Buah Biblioteca Digital Universidad de Alcalá |
| Idioma: | inglés |
| OAI Identifier: | oai:ebuah.uah.es:10017/53116 |
| Acceso en línea: | http://hdl.handle.net/10017/53116 https://dx.doi.org/10.1109/ACCESS.2022.3203728 |
| Access Level: | acceso abierto |
| Palabra clave: | Energy efficiency Optimal power flow Microgrids Swarm intelligence C-DEEPSO Informática Energías Renovables/Energías Alternativas Computer science Alternative energies |
| Sumario: | In the last years, our society's high energy demand has led to the proposal of novel ways of consuming and producing electricity. In this sense, many countries have encouraged micro generation, including the use of renewable sources such as solar irradiation and wind generation, or considering the insertion of electric vehicles as dispatchable units on the grid. This work addresses the Optimal active&-reactive power dispatch (OARPD) problem (a type of optimal power flow (OPF) task) in microgrids considering electric vehicles. We used the modified IEEE 57 and IEEE 118 bus-systems test scenarios, in which thermoelectric generators were replaced by renewable generators. In particular, under the IEEE 118 bus system, electric vehicles were integrated into the grid. To solve the OARDP problem, we proposed the use and improvement of the Canonical Differential Evolutionary Particle Swarm Optimization (C-DEEPSO) algorithm. For further refinement in the search space, C-DEEPSO relies on local search operators. The results indicated that the proposed improved C-DEEPSO was able to show generation savings (in terms ofmillions of dollars) acting as a dispatch controller against two algorithms based on swarm intelligence. |
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