A computational intelligence approach to improve the efficiency of repair services in the smart grid context. (August 2018)

• Record Type: Journal Article
• Authors: Jacques Garcia, Vinícius; Falavigna Braghirolli, Lynceo; Henrique Barriquello, Carlos; Pinheiro Bernardon, Daniel
• Is Part Of: Computers & electrical engineering. Volume 70(2018)
• Page Start: 37
• Page End: 52
• Publication Date: 2018-08
• Subjects: Smart grid -- Service operations -- Electric power systems -- Multiple traveling repairmen problem -- Metaheuristic -- Iterated local search; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2018.05.016
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: The power grid repair problem is modeled as the Multiple Traveling Repairmen Problem. Service time on nodes, multiple depots and profits are added to classical MTRP. Two algorithms are proposed to the non-dynamic and partially dynamic MTRP. The offline and online versions of the SDP are solved using the ILS metaheuristics. The negative impact of the emergencies in the backlog of regular orders is mitigated. Abstract: 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. 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). 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.