Alleviating Congestion By Load Curtailment Using PSO

Abstract

Transmission congestion the executives is one of the basic and significant errands of the System Operator (SO). Power system deregulation and transmission network capacities have led to increased interest in Load Curtailment (LC) sources. This paper shows an explanatory way to deal with distinguish the reason for load reduction and ideal size of LCs based on the Generation Shift Factor (GSF) using Particle Swarm Optimization (PSO) algorithm. A two-stage methodology is used for the optimal size of load curtailment. First GSF is utilized as an objective function to determine the basis for LC.  Next, a PSO-based model is used as a target capacity to decide the ideal LC size to limiting framework's genuine power misfortunes. The principle target of Load Curtailment is to calm clog, limit organize control misfortunes and keep up the influence stream inside the framework activity and security imperatives. The proposed structure is shown utilizing an IEEE 30-transport test systems