amirreza yari - Department of Electrical and Power Engineering, Faculty of Engineering, Lorestan University, Khorramabad, Iran
Mahmoud Reza Shakarami - Department of Electrical and Power Engineering, Faculty of Engineering, Lorestan University, Khorramabad, Iran
farhad namdari - Department of Electrical and Power Engineering, Faculty of Engineering, Lorestan University, Khorramabad, Iran
Hassan Moradi CheshmehBeigi - Electrical Eng. Dep.

Nowadays, the power distribution companies are working in a competitive atmosphere. Therefore, a major goal for electricity distribution managers is to provide the electrical energy with high reliability level with considering the economic issues.The Reliability- centered maintenance (RCM) is an efficient way of realizing this aim and improving the network maintenance processes. This approach is an operative step to improve the reliability of critical equipment and overall system performance which may reduce the costs of utilities.This paper, by using RCM provides a practical model for maintenance scheduling by considering the economic risk function and the budget restriction based on the cost of preventive maintenance (PM) and value of lost load (VOLL). In this method, PM schedules are proposed based on failure causes of different network elements. Studied elements include overhead lines, underground cables and power switches (circuit breaker (CB), manual and remote control switches (RCSs)). Failure cause and average repair time of each element is determined through data mining in geographical information system (GIS) and ENOX. For more realistic modeling and the consideration of the network loads’ uncertainties, the fuzzy triangular method is used. Due to the inconsistency between the problem’s goals, the non-dominated sorting genetic algorithm (NSGA II) is employed. Results show the effectiveness of the proposed method.

Big data, Economic risk, Load uncertainly, NSGA II, RCM