A computational intelligence approach to improve the efficiency of repair services in the smart grid context
| Autor: | Lynceo Falavigna Braghirolli, Carlos Henrique Barriquello, Daniel Pinheiro Bernardon, Vinicius Jacques Garcia |
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| Rok vydání: | 2018 |
| Předmět: |
021103 operations research
General Computer Science Operations research Iterated local search Computer science 0211 other engineering and technologies Computational intelligence 0102 computer and information sciences 02 engineering and technology Normal state 01 natural sciences Fault detection and isolation Scheduling (computing) Smart grid 010201 computation theory & mathematics Control and Systems Engineering Test set Minification Electrical and Electronic Engineering |
| Zdroj: | Computers & Electrical Engineering. 70:37-52 |
| ISSN: | 0045-7906 |
| DOI: | 10.1016/j.compeleceng.2018.05.016 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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