Multi Objective Congestion Management using Facts Devices in A Deregulated Power System

Abstract

Congestion management is one of the major technical issues in deregulated power system. newlineIn deregulated power system, the generation, transmission, and distribution operations are newlineseparated as individual entities and private owned companies are allowed to operate the newlinegeneration and distribution activities. However the transmission operations are controlled newlineby a neutral organization preferably the government, to make unbiased decision for the sake newlineof ensuring security of the power system along with economical operation. Transmission newlinecongestion may be defined as the condition where more power is scheduled or flows across newlinetransmission lines and transformers than the physical limits. Congestion of a transmission newlinenetwork can occur due to transmission line outages, generator outages, sudden change in newlinedemand and uncoordinated transactions. Congestion should be alleviated as fast as possible newlinesince it may lead to tripping of overloaded lines, consequential tripping of other lines and in newlinesome cases to voltage stability problem. Accurate prediction and alleviation of line overloads newlineare the suitable corrective actions to avoid network collapse. The problem of transmission newlinecongestion management and pricing has been identified as one of the critical and important newlinetasks of the Independent System Operator (ISO) for the smooth functioning of competitive newlineelectricity markets. newlineThe proposed congestion management problem is formulated as non-linear Optimal newlinePower Flow (OPF) problem, Nowadays; heuristic search techniques are applied successfully newlinefor solving many engineering optimization problems because of their ability to handle newlinenon-differentiable, noisy and time dependent objective functions. Conventional optimization newlinetechniques have been proposed in the literature for solving these power system security newlineproblems. But, these techniques have the common weakness of requiring differential newlineobjective function, convergence to local minima and difficulty in dealing with decision newlinevariables. This thesis explores the conventional method using