Adaptive neuro-fuzzy based AGC of hydro-thermal reheat deregulated power system

Abstract

With the increasing complexities and size of the electric power system, the gap between the electric power demand and generation is also becoming challenging. The wide and abrupt change in load consumptions results in frequency and voltage variations alongwith the variations in the power of the tieline. In order to tackle this problem, AGC plays a very significant role in centralised operation of the power system with the aim to reduce the transient deviations and make steady state error to zero. To make the power business profitable, the modern complex power system is restructured or deregulated taking into account the increasing competition. In a deregulated power system, private sectors manage the generation, transmission and distribution of the electrical power as a result of which AGC has been imposed with more significant roles. In this work, a hydro-thermal reheat based two area deregulated power system is being modelled and then the performance of the conventional controllers is being compared with the intelligent fuzzy controllers for different transaction cases.