Solving the Optimal Active-Reactive Power Dispatch Problem in Smart Grids with the C-DEEPSO Algorithm

Carolina G. Marcelino, Elizabeth F. Wanner, Flavio V.C. Martins, Jorge Perez-Aracil, Silvia Jimenez-Fernandez, Sancho Salcedo-Sanz

Research output: Chapter in Book/Published conference outputConference publication

Abstract

Optimal active-reactive power dispatch problems (OARPD) are considered large scale optimization problems with a high nonlinear complexity. Usually, in OARPD the objective is to minimize the cost of the system operation. In 2018, the IEEE PES committee proposed a competition, the 'Operational planning of sustainable power systems', in which a test bed relating the OARPD and a renewable energy generation challenge within a smart grid was proposed. In this work we consider three test scenarios proposed in that competition. Specifically, we present a hybrid meta-heuristic optimization approach applied to the OARPD, the Canonical Differential Evolutionary Particle Swarm Optimization (C-DEEPSO), to tackle these test scenarios. Comparative results with other algorithms such as CMA-ES, EPSO, and CEEPSO indicate that C-DEEPSO shows a competitive performance when solving the OARPD problems.

Original languageEnglish
Title of host publication2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings
PublisherIEEE
ISBN (Electronic)9781665467087
DOIs
Publication statusPublished - 6 Sept 2022
Event2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Padua, Italy
Duration: 18 Jul 202223 Jul 2022

Publication series

Name2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings

Conference

Conference2022 IEEE Congress on Evolutionary Computation, CEC 2022
Country/TerritoryItaly
CityPadua
Period18/07/2223/07/22

Keywords

  • C-DEEPSO
  • Evolutionary algorithms
  • OARPD
  • Smart Grids

Fingerprint

Dive into the research topics of 'Solving the Optimal Active-Reactive Power Dispatch Problem in Smart Grids with the C-DEEPSO Algorithm'. Together they form a unique fingerprint.

Cite this