ANN Based Approach for the Estimation and Enhancement of Power Transfer Capability

Major challenges emerging from the deregulation in power transmission system is transfer of bulk power over long distance. Transfer capability information is essential in Independent System Operator (ISO) to estimate the load forecast demand in order to ensure system security. Estimation of Available Transfer Capability (ATC) is required at regular instant to ensure that whole system is running in a reliable manner while serving wide variety of multilateral transactions. Artificial Neural Network (ANN) based ISO can estimate the online power transfer capability values for different possible power transmission in deregulated based power transmission system. Therefore, optimal utilization of ANN based estimated available power across large inter area tie lines can increase the system reliability under normal as well as contingency conditions. In power-distributed network, ATC should be estimated and enhanced for several transactions in minor duration. In this paper, case study of a 4-bus system that is estimating the transfer capability for many transactions using cascaded ANN-based technique. So, an intelligence-based approach is successfully designed in order to rise in the estimation ability as well as stabilize the performance of ISO. Simulation of 4-bus model with FACTS based Control strategies is designed for stability enhancement using MATLAB toolbox.