Overview: A simulation based metaheuristic optimization approach to optimal power dispatch related to a smart electric grid

Stephan Hutterer, Franz Auinger, Michael Affenzeller, Gerald Steinmauerer

Research output: Chapter in Book/Report/Conference proceedingsConference contribution

8 Citations (Scopus)

Abstract

The implementation of intelligent power grids, in form of smart grids, introduces new challenges to the optimal dispatch of power. Thus, optimization problems need to be solved that become more and more complex in terms of multiple objectives and an increasing number of control parameters. In this paper, a simulation based optimization approach is introduced that uses metaheuristic algorithms for minimizing several objective functions according to operational constraints of the electric power system. The main idea is the application of simulation for computing the fitness- values subject to the solution generated by a metaheuristic optimization algorithm. Concerning the satisfaction of constraints, the central concept is the use of a penalty function as a measure of violation of constraints, which is added to the cost function and thus minimized simultaneously. The corresponding optimization problem is specified with respect to the emerging requirements of future smart electric grids.

Original languageEnglish
Title of host publicationLife System Modeling and Intelligent Computing (LNCS 6329)
PublisherSpringer Verlag
Pages368-378
Number of pages11
Volume6329 LNCS
EditionPART 2
DOIs
Publication statusPublished - 2010
EventInternational Conference on Intelligent Computing for Sustainable Energy and Environment - Wuxi, China
Duration: 17 Sep 201020 Sep 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
ISSN (Print)0302-9743

Conference

ConferenceInternational Conference on Intelligent Computing for Sustainable Energy and Environment
CountryChina
CityWuxi
Period17.09.201020.09.2010

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