A Novel Approach for Load Frequency Control of Interconnected Thermal Power Stations

Introduction

Automatic generation control (AGC) determines the active power such that overall system generation meets the system load. AGC/Load frequency control (LFC) is of importance in electric power system design and operation. The objective of the LFC in an interconnected power system is to maintain the frequency of each power system area and to keep tie-line power flows within some pre-specified tolerances by adjusting the MW outputs of the LFC generators so as to accommodate fluctuating load demands. There has been increasing interest for designing load frequency controllers with better performance during past years and many control strategies have been developed (Nanda & Kaul, 1978; Kumar, 1998) for LFC. The first proposed control strategy was a proportional plus integral (PI) controller, which is widely used in the industry nowadays. Due to the non-linearities of various components of power systems, a linear model obtained by linearization around an operating point is usually adopted for the controller design (Mariono & Ferreira, 2008; Aldeenn & Crusca, 1995; Heniche et al., 1995). However, because of the inherent characteristics of changing loads, the operating points of a power system may change very much randomly during a daily cycle. As a result, a fixed controller is certainly not suitable. Therefore, some authors have suggested variable structure and robust control to make the controller insensitive to changes in the plant parameters (Meng et al., 2009; Kazemi et al., 2002). Conventional controllers are quite often very difficult for implementation due to following reasons.

• i)

  The optimal control is a function of all the states of the system. In practice all the states may not be available. The inaccessible states or missing states are required to be estimated.

• ii)

  It may not be economical to transfer all the information over long distances.

• iii)

  The control, which is a function of the states in turn, is dependent on the load demand. Accurate prediction of load demand may be essential for realizing optimal controller.

• iv)

  The optimal control is also dependent on the weighing matrices and is not unique (Sivaramakrishnan et al., 1984; Guo et al., 1999; Wang et al., 1993).

Some fuzzy gain scheduling of PI controllers have been proposed to solve these problems. Researchers (Çam & Kocaarslan, 2005; Yesil et al., 2004; Sreenath et al., 2008) have used such methods for load frequency control in power systems and developed some fuzzy rules for proportional and integral gains separately for two area power system. An example of fuzzy rule presented by Ha (1998) for calculation of area control error (ACE): ‘if ACE is positive but returning to zero at slow rate, don’t do anything’. It is very difficult to express mathematically ‘slow’, which is qualitative in nature. But it can be easily handled by fuzzy logic approach. A three area power system is studied by Ghoshal (2003) but without non-linearity i.e., GRC.

In this paper, the rules for the gains (K_p and K_i) are chosen identical. Therefore, the system performance is improved. The proposed controller is compared with a conventional PI controller. For the PI controller, the gains of proportional and integral are chosen 0.05 and 0.4 respectively. These values are determined experimentally. The comparison between the proposed controller and the conventional PI controller show that the dynamic parameters i.e., overshoot, settling time etc. with the proposed controller is better than conventional PI controller’s.

The paper is organized as follows: We describe the linearized three area power system model. Fuzzy logic controller used in the study is described. Simulation results are presented and conclusion is presented.