Fuzzy-Heuristic Methodology to Estimate the Load Restoration Time in MV Networks

A marked feature of electrical markets in Latin America is the high level of penalizations imposed on the utilities on account of nonsupplied energy (NSE). These economical sanctions are intended as a preventive measure to keep the Electric Service Quality (ESQ) as high as possible. NSE is computed and controlled during a fixed period individually for each group of clients (INSE). When the INSE is violated, the utilities must pay a cost of penalization for the entire INSE. The total cost of penalizations will depend on the NSE allocation between different groups of clients. In case of a fault or simultaneous faults in MV networks, there are several alternatives for radial configuration operation to restore the service. They can be classified according to the switches that have to be operated for such an end, and each alternative has an associated INSE penalty cost that depends mainly on the restoration time implied. This work develops a fuzzy-heuristic methodology to estimate the times involved in the restoration times, and it is a part of a larger optimization method for solving the load restoration problem. The results from testing the methodology in a real 290-node network have proven the feasibility of this proposed tool.