Proc. of Int. Conf. on Control, Communication and Power Engineering 2010
Load Frequency Control In Power Systems Using Genetic Algorithm A.Sheela (Senior Lecturer), R.Meenakumari (Professor) School of Electrical Sciences Department of Electrical and Electronics Engineering Kongu Engineering College, Perundurai, India gsheela1@rediffmailcom theory in a two-area power system in ref [5]. This control system is based on the pattern recognition rinciple and in implementation on the parallel-distributed computational architecture of NNs. Furthermore other controllers which are based on the optimization the parameters of PI and PID have been proposed. In ref [6], PID parameters were changed using fuzzy based gain scaling technique. Also fuzzy gain scheduling technique was applied to load frequency control in [7]. Also dynamic wavelet neural network and fuzzy neural network were experienced to design adaptive load frequency controllers .In this study, PI parameters are improved by using the genetic algorithms and developed PI controller is applied to a two-area power system.
Abstract—This paper presents a Genetic algorithm application to the area of load-frequency control (LFC). The study has been designed for a two area interconnected power system. Using variable values for the proportional and integral gains in the controller unit, the dynamic performance of the system is improved. The proposed Genetic algorithm gain scheduling of PID controller is presented and it has been shown that the proposed controller can generate the best dynamic response following a step load change. Keywords- LFC, Two area system, Genetic Algorithm, PID controller 1. INTRODUCTION
II.TWO AREA POWER SYSTEM
Frequency is a major stability criterion for largescale stability in multi area power systems. To provide the stability, active power balance and constant frequency are required. Frequency depends on active power balance. To improve the stability of the power networks, it is necessary to design a load frequency control (LFC) systems that control the power generation and active power at tie lines. Because of the relationship between active power and frequency, three level automatic generation controls have been proposed by power system researcher [1, 2]. Load frequency control scheme have to be two main control loops. These are primary control and secondary control [1]. This action is realized by turbinegovernor system in the plant. In this control level, only active power is balanced. However, maintaining the frequency at scheduled value (e.g. 50 Hz) cannot be provided. Therefore, steady state frequency error can occur forever. So this level does not enough for interconnected system. In interconnected power systems, frequency must be equal at all areas. The second level of generation control called as secondary or supplementary control is happened in large power systems which include two or more areas. Up to now, there have been developed several controllers for load frequency control by using novel and intelligent control techniques. These controllers have given good results in load frequency control. In ref [3] layered neural networks for nonlinear control of power system is applied. A Feed-forward neural network is proposed to control of the steam turbine in this study. Another neural network (NN) controller is experienced in ref [4] by using long training times and a great number of neurons. It is demonstrated the availability of an adaptive optimal load frequency controller using NNs and fuzzy set
Most of them are nonlinear and/or nonminimum phase systems . Power systems are divided into control areas connected by tie lines. All generators are supposed to constitute a coherent group in each control area. From experiments on power systems, it can be seen that each area needs its system frequency and tie line power flow to be controlled . By its actions, the various generators in the control area track a load variation and share it in proportion to their capacities. Depending upon the turbine type the primary loop typically responds within 2–20 s. This control is considerably slower and goes into action only when the primary speed control has done its job. Response time may be of the order of one minute. Two area power system with integral controller is given in fig.1
Fig.1 Two area power system
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