ESTIMATION OF DEGREE OF INSECURITY OF POWER SYSTEM USING FUNCTIONAL LINK NETWORK

Abstract

As power system have become more heavily loaded due to increases load and larger interconnections, there will be an increase in number of situations, where the power flow equations have no real solution or solution with violating limits particularly -in contingency analysis and planning applications. In a given operating condition, system state can lie either in unsolvable region where load flow solution does not exist or in an insecure region where load flow solution exist but system operating constraints are not satisfied or in a secure region where operating constraints are satisfied along with existence of load flow solution. Since insecurity cases often represent the most severe threats to secure system operation, it is important that the user be provided with a measure for quantifying the severity of the cases. The purpose of the present work is to provide a measure of the degree of insecurity of power system. The distance (Euclidean norm) in parameter space between, any insecure point and closest point on feasible -(secure) hypersurface o has been used as a measure of insecurity. The problem has been formulated as a standard constrained optimization problem with an objective function defined as one half the square of the power mismatches to find the closest secure point in parameter space. The conventional optimization method can be used for solving this problem. These methods take more computational time and hence can not be used for on-line application. Artificial Neural Network (ANN) based Functional Link, Network (FLN) has been proposed . The various FLN models are considered and have been applied on IEEE 30 bus system for estimating the degree of insecurity. It is found from the present investigation that the proposed FLN estimate the degree of insecurity with high accuracy.