Pareto-optimal Glowworm Swarms Optimization for Smart Grids Management

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Citations (Scopus)

Abstract

This paper presents a novel nature-inspired multi-objectiveoptimization algorithm. The method extends the glowworm swarm particlesoptimization algorithm with algorithmical enhancements which allowto identify optimal pareto front in the objectives space. In addition,the system allows to specify constraining functions which are needed inpractical applications. The framework has been applied to the powerdispatch problem of distribution systems including Distributed EnergyResources (DER). Results for the test cases are reported and discussedelucidating both numerical and complexity analysis.
Original languageEnglish
Title of host publicationApplications of Evolutionary Computation
Pages22-31
Number of pages10
Publication statusPublished - 2013

Publication series

NameLECTURE NOTES IN COMPUTER SCIENCE

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

Fingerprint

Dive into the research topics of 'Pareto-optimal Glowworm Swarms Optimization for Smart Grids Management'. Together they form a unique fingerprint.

Cite this