Robust decentralized load frequency control of interconnected power system with Generation Rate Constraint using Type-2 fuzzy approach

https://doi.org/10.1016/j.ijepes.2010.12.027Get rights and content

Abstract

The Load Frequency Control (LFC) problem has been a major subject in electrical power system design/operation. LFC is becoming more significant recently with increasing size, changing structure and complexity in interconnected power systems. In practice LFC systems use simple Proportional Integral (PI) controllers. As the PI control parameters are usually tuned, based on classical approaches. Moreover, they have fixed gains; hence are incapable of obtaining good dynamic performance for a wide range of operating conditions and various load changes, in multi-area power system. Literature shows that fuzzy logic controller, one of the most useful approaches, for utilizing expert knowledge, is adaptive in nature and is applied successfully for power system stabilization control. This paper proposes a Type-2 (T2) fuzzy approach for load frequency control of two-area interconnected reheat thermal power system with the consideration of Generation Rate Constraint (GRC). The performance of the Type-2 (T2) controller is compared with conventional controller and Type-1 (T1) fuzzy controller with regard to Generation Rate Constraint (GRC). The system parametric uncertainties are verified by changing parameters by 40% simultaneously from their typical values.

Introduction

With an increasing demand for electric power, the electric power system becomes more and more complicated. Therefore the supply of electric power with stability and high reliability is required. The power system operates in normal state which is characterized by constant frequency and voltage profile with certain system reliability. For a successful operation of power system under abnormal conditions, mismatches have to be corrected via supplementary control [1]. Automatic Generation Control (AGC) or load frequency control [2], [15] is a very important issue in power system operation and control for supplying sufficient and reliable electric power with good quality. An interconnected power system can be considered as being divided into control areas. These control areas are connected by the tie lines. In each control area, all generators are assumed to form a coherent group. The power system is subjected to local variations of random magnitude and duration. For satisfactory operation of a power system the frequency should remain nearly constant. The frequency of a system depends on active power balance. As frequency is a common factor throughout the system, a change in active power demand at one point is reflected throughout the system [12].

A number of control strategies have been employed in the design of load frequency controllers [2], [14], [16], [20], [21], in order to achieve better dynamic performance. Among the various types of load frequency controllers, the most widely employed is the conventional proportional integral (PI) controller [11], [13]. Conventional controller can be simple for implementation but takes more time for control and gives large frequency deviation. A number of state feedback controllers based on linear optimal control technique have been proposed to achieve better performance [10]. Fixed gain controllers are designed at nominal operating conditions and they fail to provide best control performance over a wide range of operating conditions. Therefore, to keep the system performance near its optimum, it is desirable to track the operating conditions and use updated parameters to compute the control. Adaptive controllers with self-adjusting gain settings have been proposed for LFC [13]. Literature survey shows that only a few investigations have been carried out using LFC. The objective of this research is to investigate the load frequency control and inter-area tie-power control problem for a multi-area power system taking into consideration the uncertainties in the parameters of the system. Power system is a highly non-linear and uncertain system, to take care of these uncertainties many authors have proposed fuzzy logic based controllers to power systems [1], [4], [9], [12], [13], [19]. This fuzzy logic, also called as Type-1 fuzzy, can further be modified to Type-2 fuzzy by giving grading to the membership functions which are themselves fuzzy. Or in other words, in Type-2 fuzzy set, at each value of the variable the membership is a function but not just a point value. Therefore, a Type-2 fuzzy set can be visualized as a three dimensional set. The advantage of the third dimension gives an extra degree of freedom for handling uncertainties. Taking this feature into consideration, a robust decentralized control scheme is designed using Type-2 fuzzy logic [17], [18]. The proposed controller is simulated for a two-area power system in the presence of Generation Rate Constraint (GRC) for different operating conditions and was compared with conventional controller and Type-1 fuzzy controller [4]. Results of simulation show that the T2 fuzzy controllers guarantee the robust performance for a wide range of operating conditions.

Section snippets

System model

The detailed block diagram modeling of two area reheat thermal power system with the consideration of Generation Rate Constraint (GRC), for load frequency control, is investigated in this study as shown in Fig. 1 with Area Control Error (ACE) and its derivative as the inputs to the controllers [10]. The parameters of the two areas is given in Table 1. In a power system having steam plants, power generation can change only at a specified maximum rate. As described in Fig. 2, by adding limiters

Type-2 (T2) fuzzy logic controllers

A fuzzy system that uses Type-2 fuzzy sets and/or fuzzy logic and inference is called a Type-2 (T2) fuzzy system. In contrast, a fuzzy system that employs ordinary fuzzy sets, logic, and inference is called Type-1 (T1) fuzzy system [8], [9]. T1 fuzzy systems, especially fuzzy controllers and fuzzy models, have been developed and applied to practical problems. A Type-1 fuzzy set (T1 FS) has a grade of membership that is crisp, whereas a Type-2 fuzzy set (T2 FS) has a grade of membership that is

Simulation results

To illustrate robust performance of the proposed Type-2 fuzzy controller we have chosen different cases of operation conditions as follows:

Case I(a): Step increase in demand of the first area ΔPD1: In this case, step increase in demand of the first area ΔPD1 is applied. The frequency deviation of the first area, Δf1, and the frequency deviation of the second area, Δf2, and inter-area tie-power signals of the closed-loop system are shown in Fig. 7, Fig. 8, Fig. 9. Using proposed method, the

Conclusion

In this paper a new method for load frequency control using Type-2 fuzzy controller in a two-area power system has been proposed. The proposed method was applied to a typical two-area interconnected reheat thermal power system with the consideration of Generation Rate Constraint (GRC) with system uncertainty parametric and various loads conditions. Simulation results demonstrated that the designed controller guarantees the robust stability and robust performance such as precise reference

References (21)

There are more references available in the full text version of this article.

Cited by (140)

  • Online-based approach for frequency control of microgrid using biologically inspired intelligent controller

    2022, Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies
View all citing articles on Scopus
View full text