Energy restoration for large-scale distribution system using EA and a new data structure

Energy restoration problem in radial distribution systems usually involves network reconfiguration procedures. Service restoration is performed to restore electricity for out-of-service areas. This paper presents solutions for energy restoration in large-scale distribution networks by evolutionary algorithms (EA). The objectives after the location of a fault has been identified and the faulted zone has been isolated are (i) to supply energy to the largest number of customers as possible, (ii) to minimize the number of switching operations, (iii) not to violate operational constraints, (iv) to reduce power losses, (v) to reduce the computational effort, and (vi) to generate only configurations without outage zones and/or closed loops. A new data structure which manipulates graphs producing only feasible configurations is proposed. This can save RAM memory and reduce processing time. The proposed methodology provides an efficient alternative for reconfiguration problems, and it can be used in problems which require online solutions.