Extreme learning machine-based alleviation for overloaded power system

Abstract

The present study proposes a corrective method of electric system overload provided that the wind farm is integrated into the distribution system, taking into account the congestion cost. The authors attempted to mitigate the overload and to monitor flow over transmission lines. Unified power flow controller device was the first suggestion utilised to solve this problem, then due to its extremely fast training and the excellent generalisation performance, extreme learning machine algorithm is employed. The fundamental point is the transmission line alleviation. In addition, other targets are realised: the load shedding avoidance, minimisation of losses and congestion cost. This study is also designed to utilise PowerWorld Simulator and MATLAB software to demonstrate methods for relieving transmission overloads. The accuracy of the proposed approach has been tested for Algerian (Adrar) 22-bus system. Obtained results showed an improvement in power system behaviour. Simulation results are exposed, discussed and compared at the end of this study.