Oladeji, Ifedayo Ramon (Auckland University of Technology (AUT)), Zamora, Ramon (Auckland University of Technology (AUT)), Lie, Tek Tjing (AUCKLAND UNIV. OF TECH.)

Modelling an Adaptable Multi-Objective Fuzzy Expert System Based Transmission Network Transfer Capacity Enhancement

Scheduled for presentation during the Regular Session "Learning, Fuzzy and Neural Systems" (FC1), Friday, November 29, 2019, 15:45−17:45, WZ Building Room WZ416

2019 Australian & New Zealand Control Conference (ANZCC), November 27-29, 2019, Auckland, New Zealand

This information is tentative and subject to change. Compiled on April 17, 2024

Abstract

The need to enhance the performance of existing transmission network in line with economic and technical constraints is crucial in a competitive market environment. This paper models the total transfer capacity (TTC) improvement using optimally placed thyristor-controlled series capacitors (TCSC). The system states were evaluated using distributed slack bus (DSB) and continuous power flow (CPF) techniques. Adaptable logic relations was modelled based on security margin (SM), steady state and transient condition collapse voltages (Uss, Uts) and the steady state line power loss (Plss), through which line suitability index (LSI) was obtained. The fuzzy expert system (FES) membership functions (MF) with respective degrees of memberships are defined to obtain the best states. The LSI MF is defined high between 0.2-0.8 to provide enough protection under transient disturbances. The test results on IEEE 30 bus system show that the model is feasible for TTC enhancement under steady state and N-1 conditions.