An improved C-DEEPSO algorithm for optimal active-reactive power dispatch in microgrids with electric vehicles
AuthorsGil Marcelino, Carolina; Matos Cardoso Leite, Gabriel; Jiménez Fernández, Silvia; Salcedo Sanz, Sancho
IdentifiersPermanent link (URI): http://hdl.handle.net/10017/53116
Agencia Estatal de Investigación
Comunidad de Madrid
Gil Marcelino, C., Matos Cardoso Leite, G., Jiménez Fernández, S. & Salcedo Sanz, S. 2022, "An improved C-DEEPSO algorithm for optimal active-reactive power dispatch in microgrids with electric vehicles" , IEEE Access, vol. 10, pp. 94298 - 94311.
Optimal power flow
info:eu-repo/grantAgreement/EC/H2020/754382/EU/GOT Energy Talent/GET
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-85887-C2-2-P/ES/NUEVOS ALGORITMOS HIBRIDOS DE INSPIRACION NATURAL PARA PROBLEMAS DE CLASIFICACION ORDINAL Y PREDICCION/
info:eu-repo/grantAgreement/CAM//S2018%2FEMT4366/ES/PROgrama Microredes INTeligentes-CM/PROMINT-CM
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
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.