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Reports from Federal University of Santa Maria Provide New Insights into Computational Intelligence (A Computational Intelligence Approach To Improve the Efficiency of Repair Services In the Smart Grid Context)

Source: 
Robotics & Machine Learning Daily News

2019 MAY 23 (NewsRx) -- By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News -- Fresh data on Computational Intelligence are presented in a new report. According to news reporting originating from Santa Maria, Brazil, by NewsRx correspondents, research stated, “In a smart grid context, self-healing is the capability of the system to perform fault location, fault isolation and service restoration in a fully automated process. Self-healing reduces the outage duration and can help improve the efficiency of the crews that must be dispatched in an emergency situation to repair the system and return it to its normal state.”

Financial supporters for this research include RGE SUL Distribuidora Energia SA, National Institute of Science and Technology in Distributed Generation (INCT GD-UFSM, CNPq), National Institute of Science and Technology in Distributed Generation (CAPES), National Institute of Science and Technology in Distributed Generation (FAPERGS).

Our news editors obtained a quote from the research from the Federal University of Santa Maria, “This work proposes an iterated local search algorithm to solve the Service Dispatch Problem (SDP) for assignment, scheduling and dispatching of those working crews to attend to emergency and regular orders. The main contribution involves simultaneously considering the working hour constraints related to the crews and the minimization of latency for both regular (off-line version) and emergency orders (on-line version).”

According to the news editors, the research concluded: “The computational results obtained from a test set of ten actual data instances of the problem highlight the effectiveness of the proposed algorithm when addressing the SDP.”

For more information on this research see: A Computational Intelligence Approach To Improve the Efficiency of Repair Services In the Smart Grid Context. Computers & Electrical Engineering, 2018;70():37-52. Computers & Electrical Engineering can be contacted at: Pergamon-Elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, England. (Elsevier - www.elsevier.com; Computers & Electrical Engineering - http://www.journals.elsevier.com/computers-and-electrical-engineering/)

The news editors report that additional information may be obtained by contacting C.H. Barriquello, Federal University, Br-97105900 Santa Maria, Rs, Brazil. Additional authors for this research include V.J. Garcia, L.F. Braghirolli and D.P. Bernardon.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1016/j.compeleceng.2018.05.016. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

 

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