NOVEL INTELLIGENT CONTROLLERS FOR LOAD FREQUENCY CONTROL OF A MULTI AREA HYBRID POWER SYSTEM

Abstract

In today’s world, power system become more and more complex due to lot of interconnectivity. There is a rapid increase in demand of large customer and to meet that demand is a challenging task, which also fluctuates the generation-demand equation. In power system due to abrupt change in load demand the system frequency and working voltage fluctuates, which effects the system stability. A large amount of Tie-line power interchange effects the system characteristics. , automatic generation control (AGC) have a important part in maintain the power system frequency to nominal values and also minimizing the transient deviation and make steady state error to zero with using suitable control strategies As there is large energy demand renewable energy sources have to come into the picture to supply the required load demand. Renewable energy, such as wind and solar energy, is desirable for power generation due to its unlimited existence and environmental friendly nature. In this thesis, a intelligent Neuro-fuzzy based controller is proposed for a multi-area load frequency control with PV system, suitable for a restructured power system. The proposed controller has been compared with and without PV system. A comparative analysis of different controllers has been done in which PI, PID, FGSPI and ANFIS controllers are compared. The proposed hybrid neuro-fuzzy controller evaluates the current system situation and regulates system characteristics efficiently. The functioning of proposed scheme has been tested on multi area AC network in which two areas are diesel generator based and one area is non-conventional PV array. The suggested control technique has been validated to be better than the conventional control technique used in AGC designing. The results of proposed scheme have been compared with and without PV system.