A New Heuristic Providing an Effective Initial Solution for a Simulated Annealing approach to Energy Resource Scheduling in Smart Grids

Tiago M Sousa, Hugo Morais, R. Castro, Zita Vale

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    Abstract

    An intensive use of dispersed energy resources is expected for future power systems, including distributed generation, especially based on renewable sources, and electric vehicles. The system operation methods and tool must be adapted to the increased complexity, especially the optimal resource scheduling problem. Therefore, the use of metaheuristics is required to obtain good solutions in a reasonable amount of time. This paper proposes two new heuristics, called naive electric vehicles charge and discharge allocation and generation tournament based on cost, developed to obtain an initial solution to be used in the energy resource scheduling methodology based on simulated annealing previously developed by the authors. The case study considers two scenarios with 1000 and 2000 electric vehicles connected in a distribution network. The proposed heuristics are compared with a deterministic approach and presenting a very small error concerning the objective function with a low execution time for the scenario with 2000 vehicles.
    Original languageEnglish
    Title of host publicationProceedings of IEEE Symposium Series on Computational Intelligence
    PublisherIEEE
    Publication date2014
    Pages132-139
    ISBN (Print)978-1-4799-4546-7
    DOIs
    Publication statusPublished - 2014
    Event2014 IEEE Symposium Series on Computational Intelligence - Orlando, United States
    Duration: 9 Dec 201412 Dec 2014

    Conference

    Conference2014 IEEE Symposium Series on Computational Intelligence
    Country/TerritoryUnited States
    CityOrlando
    Period09/12/201412/12/2014

    Fingerprint

    Dive into the research topics of 'A New Heuristic Providing an Effective Initial Solution for a Simulated Annealing approach to Energy Resource Scheduling in Smart Grids'. Together they form a unique fingerprint.

    Cite this