LOAD FREQUENCY HYBRID INTELLIGENT CONTROL FOR MULTI- AREA INTERCONNECTED POWER SYSTEM

In this research work, the power systems with, three areas and four areas hydrothermal power system connected through tie-lines are investigated. The main purpose of system generation control is to balance the system generation against the load and losses so that the desired frequency and power interchange between neighboring systems are maintained. This dissertation is mainly focused on technical issues associated with load-frequency control (LFC)in structured power systems. The PI & PID controllers are very simple for implementation and give better dynamic response, but their performances deteriorate when the complexity in the system increases due to disturbances like load variation boiler dynamics. Therefore, there is needof a controller which can overcome this problem. The Artificial Intelligent controllers like Fuzzy and Neural control approaches are more suitable in this respect. Fuzzy system has been applied tothe load frequency control problems with rather promising results. The salient feature of these techniques is that they provide a model- free description of control systems and do not require model identification when selecting the specific number of membership function. This has some limitation of selecting membership function and defuzzification methods for unstructured power system, to overcome these above said problems Artificial Neural Network (ANN) and ANFIS controllers are introduced. These have advance adaptive control configuration. The NNs are able to monitor the system frequency as the controller issues its control command. The neural control approach is shown to have several advantages over the basic fixed parameter schemes and the more advanced adaptive control technique that have been recently developed. The proposed ANFIS controller combines the advantages of fuzzy controller as well as quick response and adaptability nature of ANN. The intelligent controllers like Fuzzy logic, ANN and Hybrid Fuzzy Neural Network approaches are used for Automatic Generation Control for the two areas, three area and four areas interconnected power systems. Area-1 and area-2 consist of thermal reheat power plant whereas area-3 and area-4 consist of hydro power plant with electric governor. Performance evaluation is carried out by using intelligent (ANFIS, ANN and Fuzzy) control and conventional PI & PID control approaches. To enhance the performance of controller sliding surface i.e. variable structure control is included. The three models of interconnected power system have been developed with all five types of said controllers and simulated using MATLAB/SIMULINKpackage.