K.V.Siva Reddy / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 4, Jul-Aug 2013, pp.989-995 989 | P a g e An Adaptive Neuro-Fuzzy Logic Controller for a Two Area Load Frequency Control K.V.Siva Reddy (Assistant Professor, Department of EEE, QISCET, Ongole, A.P, INDIA) ABSTRACT This paper presents the design and analysis of Neuro-Fuzzy controller based on Adaptive Neuro-Fuzzy inference system (ANFIS) architecture for Load frequency control of interconnected areas, to regulate the frequency deviation and power deviations. Any mismatch between generation and demand causes the system frequency to deviate from its nominal value. Thus high frequency deviation may lead to system collapse. This necessitates a very fast and accurate controller to maintain the nominal system frequency. This newly developed control strategy combines the advantage of neural networks and fuzzy inference system and has simple structure that is easy to implement. So, In order to keep system performance near its optimum, it is desirable to track the operating conditions and use updated parameters near its optimum. This ANFIS replaces the original conventional proportional Integral (PI) controller and a fuzzy logic (FL) controller were also utilizes the same area criteria error input. The advantage of this controller is that it can handle the non- linearities at the same time it is faster than other conventional controllers. Simulation results show that the performance of the proposed ANFIS based Neuro-Fuzzy controller damps out the frequency deviation and attains the steady state value with less settling time and reduces the overshoot of the different frequency deviations and also reduces the interchanged tie power. Keywords - Adaptive Neuro-Fuzzy Inference System, Conventional PI Controller, Fuzzy Logic Controller, Load Frequency Control, Neuro-Fuzzy Controller. I. INTRODUCTION Nowadays, electricity generation is very important because of its increasing necessity and enhanced environmental awareness such as reducing pollutant emissions. The dynamic behavior of the system depends on changes in the operating point. The quality of generated electricity in power system in dependent on the system output, which has to be of constant frequency and must maintain the scheduled power and voltage. Therefore, load frequency control, LFC, is very important in order to supply reliable electric power with good quality for power systems. Large-scale power systems are composed of control areas or regions representing coherent groups of generators. These various are interconnected through tie lines. The tie lines are utilized for energy exchange between areas and provide inter-area support in case of abnormal condition [1-5]. Load changes in area and abnormal conditions, such as outages of generation, leads to mismatch in scheduled power interchanges between areas. These mismatches have to be corrected via supplementary control. In recent years, large tie-line power fluctuations have been observed as a result of increased system capacity and very close interconnection among power systems [1-2].This observation suggests a strong need of establishing a more advanced load frequency control (LFC) scheme. An effective controller for stabilizing frequency oscillations and maintaining the system frequency within acceptable range and to maintain the interchange power between control areas at scheduled values by adjusting the MW output power of the selected generators so as to accommodate changing in load demands [4-5].The load Frequency control (LFC) or Automatic Generation control (AGC) has been one of the most important subjects concerning power system engineers in the last decades. Many investigations in the area of LFC problem have been reported and a number of control strategies have been employed in the design of load frequency(LF) controller in order to achieve better dynamic performance[6-8].In recent years, fuzzy system applications have received increasing attention in power system operation and control[8,9,10,11,12 ].Among the various types of load frequency controllers, The most widely employed is the conventional proportional integral(PI) controller [5-6].Conventional controller is simple for implementation but takes more time and gives large frequency deviation. A number of state feedback controllers based on linear optimal control theory have been proposed to achieve better performance [6].Fixed gain controllers are designed at nominal operating conditions and fail to provide best control performance over a wide range of operating conditions. So, to keep system performance near its optimum, it is desirable to track the operating conditions and use updated parameters to compute the control. Recently, fuzzy-logic control application to power system are rapidly developing especially power system stabilization problem [8,10,14,15] as well as load frequency control problem. The basic