Frequency Stabilization for Multi-area Thermal–Hydro Power System Using Genetic Algorithm-optimized Fuzzy Logic Controller in Deregulated Environment

Abstract—This article develops a model of load frequency control for an interconnected two-area thermal–hydro power system under a deregulated environment. In this article, a fuzzy logic controller is optimized by a genetic algorithm in two steps. The first step of fuzzy logic controller optimization is for variable range optimization, and the second step is for the optimization of scaling and gain parameters. Further, the genetic algorithm-optimized fuzzy logic controller is compared against a conventional proportional-integral-derivative controller and a simple fuzzy logic controller. The proposed genetic algorithm-optimized fuzzy logic controller shows better dynamic response following a step-load change with combination of poolco and bilateral contracts in a deregulated environment. In this article, the effect of the governor dead band is also considered. In addition, performance of genetic algorithm-optimized fuzzy logic controller also has been examined for various step-load changes in different distribution unit demands and compared with the proportional-integral-derivative controller and simple fuzzy logic controller.     

A self-tuning fuzzy PI controller for TCSC to improve power system stability

In this paper, a self-tuning fuzzy PI controller (STFPIC) is proposed for thyristor-controlled series capacitor (TCSC) to improve power system dynamic performance. In a STFPIC controller, the output-scaling factor is adjusted on-line by an updating factor (α). The value of α is determined from a fuzzy rule-base defined on error (e) and change of error (Δe) of the controlled variable. The proposed self-tuning controller is designed using a very simple control rule-base and the most natural and unbiased membership functions (MFs) (symmetric triangles with equal base and 50% overlap with neighboring MFs). The comparative performances of the proposed STFPIC and the standard fuzzy PI controller (FPIC) have been investigated on two multi-machine power systems (namely, 4 machine, 2 area system and 10 machine 39 bus system) through detailed non-linear simulation studies using MATLAB/SIMULINK. From the simulation studies it has been found out that for damping oscillations, the performance of the proposed STFPIC is better than that obtained by the standard FPIC. Moreover, the proposed STFPIC as well as the FPIC have been found to be quite effective in damping oscillations over a wide range of operating conditions and are quite effective in enhancing the power carrying capability of the power system significantly.     

Fractional-order Proportional-integral-derivative-based Automatic Generation Control in Deregulated Power Systems

Abstract—In this article, implementation of a fractional-order proportional-integral-derivative controller is proposed as supplementary automatic generation control of interconnected multi-area deregulated power systems that operates under the effects of bilateral contracts on the dynamics. The tuning of the fractional-order proportional-integral-derivative controller parameters is formulated as an optimization problem and solved by employing a genetic algorithm. The traditional automatic generation control loop incorporated with the concept of the distribution company participation matrix and fractional-order proportional-integral-derivative supplementary controller is simulated for different operating cases; a comparison among the conventional integral controller, hybrid fuzzy proportional-integral controller, genetic algorithm-tuned proportional-integral controller, and genetic algorithm-tuned proportional-integral-derivative controllers is presented. The simulation results show that the system employing a genetic algorithm-tuned fractional-order proportional-integral-derivative controller has better performance than the integer-order hybrid fuzzy proportional-integral, genetic algorithm-tuned proportional-integral, and genetic algorithm-tuned proportional-integral-derivative controllers in terms of settling time and overshoot.     

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

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.     

AUTOMATIC GENERATION CONTROL WITH SUPERCONDUCTING MAGNETIC ENERGY STORAGE IN POWER SYSTEM

ABSTRACT

This paper describes the development of a digital computer model for a two area interconnected power system which includes the governor deadband nonlinearity, steam reheat constraints and boiler dynamics. The improvement in automatic generation control (AGO with the addition of a small capacity Superconducting Magnetic Energy Storage (SMES) unit is studied. Time domain simulations are used to study the performance of the power system and the controller. Parameter optimization of the controller are carried out by the second method of Lyapunov, which ensures the stability of the system. Suitable methods for the control of SMES unit are also described.     

Ant Colony Optimized Fuzzy Control Solution for Frequency Oscillation Suppression

This paper presents a novel approach in addressing a critical power system issue, i.e., automatic generation control (AGC) in a smart grid scenario. It proposes the design and implementation of an optimized fuzzy logic controller (FLC) for AGC of interconnected power network. There are three different sources of power generation considered in the two-area interconnected model of power system network. First area is equipped with a single reheat thermal unit and a superconducting magnetic energy storage (SMES) unit, while another area has a hydro-unit with SMES. A multi-stage optimization strategy for the optimal solution of FLC for tie-line and frequency oscillation suppression is proposed in this paper using an ant colony optimization technique. The optimization of FLC is carried out in four different stages. The first stage is the optimization of range of input and output variables; the second stage is the optimization of membership function; the third and fourth stages are the optimization for rule base and rule weight optimization, respectively. The performance of the proposed controller is also compared with another control approaches to stabilize P_tie-line and Δf oscillations; these are the Ziegler–Nichols-tuned proportional–integral–derivative (PID) controller and genetic algorithm optimized PID controller. A comprehensive analysis of the traditional techniques and proposed techniques is presented on the basis of major dynamic performance parameters, i.e., settling time and peak overshoot.     

Optimal Automatic Generation Control with Hydro,Thermal, Gas,and Wind Power Plants in 2-Area Interconnected Power System

Abstract

This paper explores automatic generation control (AGC) of a more realistic 2-area multi-source power system comprising hydro, thermal, gas, and wind energy sources-based power plants in each control area. The wind power plants (WPPs) have been growing continuously worldwide due to their inherent feature of providing eco-friendly sustainable energy. But, operations of WPPs are associated with system stability problems due to lack of inertia. However, WPPs do not participate in the elimination of mismatch between generation and demand by AGC but disturbance can be injected by the WPPs due to the stochastic nature of wind energy. An optimal controller based on full state feedback control theory is designed to conduct the study. The system dynamic performance analysis is carried out for 1% step load disturbance in corresponding control areas. It is observed that the system dynamic graphs of deviation in area frequency and tie-line power are significantly improved with the implementation of optimal AGC controller compared to GA tuned classical controller. It has also been shown that the WPPs aid the increase in load disturbance when the input wind power reduces but it negates the effect of increase in load disturbance for increase in wind energy to the WPPs.     

HVDC紧急功率支援自适应模糊控制器设计

研究了高压直流输电系统（HVDC）紧急功率支援控制的实现方法，提出了一种基于参数自适应模糊PID控制算法的HVDC紧急功率支援控制器，它可以根据两侧交流系统的运行情况、故障后的状态等信息，即时地决定最佳的支援功率值，并控制直流输电系统按照最佳支援功率值进行定值功率支援。该控制器基于确定模糊模型，构造模糊PID控制器，并引入确定性模糊调整规则对其进行参数自适应调整，整个控制器结构简单、稳定性强且实现容易。文中采用一个两区域系统对该控制器进行了时域仿真计算。仿真结果表明：投入该控制器后，交流系统在各种大干扰下的频率响应均表现出令人满意的特性。     

A fuzzy logic controlled superconducting magnetic energy storage,SMES frequency stabilizer

This paper presents application of fuzzy logic controlled superconducting magnetic energy storage device, SMES to damp the frequency oscillations of interconnected two-area power systems due to load excursions. The system frequency oscillations appear due to load disturbance. To stabilize the system frequency oscillations, the active power can be controlled via superconducting magnetic energy storage device, SMES. The error in the area control and its rate of change is used as controller input signals to the proposed fuzzy logic controller. In order to judge the effect of the proposed fuzzy logic controlled SMES, a comparative study is made between its effect and the effect of the conventional proportional plus integral (PI) controlled SMES. The studied system consists of two-area (thermal–thermal) power system each one equipped with SMES unit. The time simulation results indicate the superiority of the proposed fuzzy logic controlled SMES over the conventional PI SMES in damping the system oscillations and reach quickly to zero frequency deviation. The system is modeled and solved by using MATLAB software.     

A new method of excitation control based on fuzzy set theory

The synthesis of the structure of the power system stabiliser (PSS) and its parametrization are based entirely on methods of linear system theory. Thus the desired effect of the PSS is limited to a bounded area around one system operating point. The use of a controller based on fuzzy set theory introduces an event controlled excitation of the synchronous machine taking into account the power system operation. The desired response of the fuzzy controller is given by a set of rules which are obtained from the limits of the voltage regulator and the undesired performance of the conventional excitation control. A fuzzy controller has been developed for which simulation results are provided. These results support the concept of a fuzzy controller for the purpose of excitation control. They show that a well designed fuzzy controller is superior to a fast excitation control with an additional PSS     

Experimental Verification of Photovoltaic-based Three-phase Four-wire Series Hybrid Active Power Filter

Abstract—This article proposes a photovoltaic and battery interfaced series hybrid active power filter, which is comprised of a series active power filter and an inductor-capacitor (LC) shunt passive filter. The main benefits of the proposed system provide the compensation against the voltage harmonics, current harmonics, and voltage interruption for the whole day. A series active power filter demands a source of energy for compensating the voltage sag/swell. The proposed topology utilizes the green energy source with an energy storage unit to meet the DC-link voltage requirement of the series active power filter. The control strategy is based on the dual formulation of the compensation system principles with adaptive fuzzy logic controller. The simulation and experimental studies are carried out to validate the effectiveness of the proposed photovoltaic interfaced three-phase four-wire series hybrid active power filter.     

Adaptive fuzzy logic load frequency control of multi-area power system

Based on indirect adaptive fuzzy control technique, a new load frequency control (LFC) scheme for multi-area power system is proposed. The power systems under study have the characterization of unknown parameters. Local load frequency controller is designed using the frequency and tie-line power deviations of each area. In the controller design, the approximation capabilities of fuzzy systems are employed to identify the unknown functions, formulate suitable adaptive control law and updating algorithms for the controller parameters. It is proved that the proposed controller ensures the boundedness of all variables of the closed-loop system and the tracking error. Moreover, in the proposed controller an auxiliary control signal is introduced to attenuate the effect of fuzzy approximation error and to mitigate the effect of external disturbance on the tracking performance. Simulation results of a three-area power system are presented to validate the effectiveness of the proposed LFC and show its superiority over a classical PID controller.     

ANALYSIS OF POWER CONVERTER CONTROL USING NEURAL NETWORK AND RULE-BASED METHODS

ABSTRACT

Current-controlled voltage source inverters offer substantial advantages in improving motor system dynamics for high-performance ac drive systems. The controller switches follow a set of reference current waveforms. Fixed-band hysteresis and sinusoidal-band hysteresis controllers have been studied. The first part of this paper develops neural network and fuzzy logic based current-controlled voltage source inverters. The models and learning techniques have been investigated by simulation. The implementation of neural networks is described and simulation results are presented. In the second part of this paper, the new UPS (uninterruptible power supply) with fuzzy logic compensator is proposed. Proposed fuzzy logic compensator is used to prevent voltage drop from nonlinear load. The total harmonic distortion (THD) of proposed scheme is better than that of conventional deadbeat control method for linear and nonlinear load. In the third part of this paper, the application of fuzzy control to DC-DC converters operating at finite switching frequency is studied. Several control methods currently used for buck, boost and buck/boost converters are compared to the fuzzy converter control. Simulation results for several control methods are presented. The simulations show that the fuzzy control method has better dynamic performance and less steady state error.     

Robust controller design for large interconnected power systems with model uncertainties based on wide-area measurement

Recently the controller using wide-area measurement systems (WAMS) signals has been suggested to accommodate the dynamic performances of large interconnected power systems. However, there is an unavoidable delay before the wide-area signals are received at the controller site. Therefore, a delay-independent robust control problem of large interconnected power systems is studied via H _∞ fuzzy control method based on wide-area measurement. First, a set of equivalent Takagi–Sugeno (T–S) fuzzy model is adopted to represent the nonlinear large interconnected power system. A wide-area state feedback decentralized H _∞ fuzzy control scheme is developed to override the various disturbances, solve the effect of model uncertainties and stabilize the large power system. The H _∞ decentralized control problem is parameterized in terms of a linear matrix inequality (LMI) problem, and the LMI problem can be solved efficiently using convex optimization techniques. Finally, the effectiveness of the proposed controller design methodology is demonstrated through simulation example. This work is supported by the National Science Foundation of China under grant 60374039, 60404007.     

新型模糊逻辑二级电压控制器

摘要： 设计了一种新型的基于极坐标二值模糊逻辑规则的模糊逻辑二级电压控制器。该控制器有效地将模糊逻辑规则和二次电压控制相结合：将引导节点的电压偏差及其微分作为模糊逻辑控制规则的前项输入，与规则作用后，推理出相应的电压控制信号，然后引入比例积分器，得到区域无功控制信号，通过发电机的励磁控制，实现对引导节点电压的控制。该控制器通过引入控制发电机的参与因子，实现了区域内各控制发电机之间的相互协调和补充。以New England 39节点系统为例进行仿真计算，结果表明：所设计的二级电压控制器在系统发生电压扰动的期间，能够从区域电压稳定的角度出发，调整各级电压控制器的电压参考值从而调整其无功出力，为系统提供所需的电压支持，使得系统的负荷电压水平维持在较好的状态，提高了系统的电压稳定性。它比常规PID二级电压控制器具有更好的控制性能。     

Design and Implementation of Adaptive Neuro–Fuzzy Inference System Based Control Algorithm for Distribution Static Compensator

This article focuses on the design and implementation of a distribution static compensator using an adaptive neuro–fuzzy inference system based controller. The distribution static compensator is controlled to provide power quality improvement, such as power factor correction, harmonics compensation, load balancing, and voltage regulation. Active and reactive power fundamental components of load currents are extracted using d-q theory. A distribution static compensator is realized using a voltage source converter. Both simulation and experimental results prove the effectiveness of the control algorithm under non-linear loads. The adaptive neuro–fuzzy inference system based controller works satisfactorily for power factor correction and harmonics reduction under balanced as well as unbalanced load conditions. Test results clearly depict the dynamics of the performance of the system under steady state as well as dynamics under load change and load unbalancing.     

Identification and Optimal Control of a Generating Unit in an Interconnected System

Abstract

The paper describes the identification and discrete-time optimal control design of a generating unit, operating in a multimachine environment. The system comprises three generating units which are interconnected to supply a common load area in addition to their local loads. The generating unit, which is the most effective candidate for optimal control application, is selected first on the basis of eigenvalue analysis. A low-order state-space model of this unit is obtained by using recursive least-squares identification. On the basis of this model, a local state-feedback optimal controller is designed by using the dynamic programming procedure. The controller provides integrated control to the generator exciter and turbine-valving, and is implemented on a fairly detailed non-linear model which simulates the interconnected system. A comparison is made between this optimal controller and conventional controllers which are in common use in power stations. The simulation results, which include 3-phase fault tests and stability boundaries, show the appreciable improvement in system performance obtained by adopting the optimal controller based on the identified model.     

负荷频率系统的LFC模糊监控器设计

应用在LFC控制中常规的模糊调整增益PI控制器和I控制器,只针对单一区域的负荷频率进行控制,并不考虑实际模型中的互相扰动.其中最突出的问题是由于不限制联络线上的功率流动,电能总是从频率高区域流向频率低区域,加剧了频率高区域的控制负担,再加上各区域控制动作的不协调,使得当扰动在不同的时间和幅值时引起系统调节过程的急剧恶化,导致整个系统不稳定.提出一种基于模糊MAMDANI推理算法的模糊监督控制器,采用各个区域的频率偏差作为控制器的输入,监督控制器作为一种前馈补偿,设计输出为一个ACE的倍数,加快调节过程,到达稳态.经过实验仿真数据对比,说明提出的监督控制器能有效提高系统的稳定性.     

Real-time Energy Control Approach for Smart Home Energy Management System

Abstract

This article investigates a real-time energy control approach for a home energy management system, including the electric water heater, air conditioner, clothes dryer, electric vehicle, photovoltaic cell, critical loads, and battery system. A demand response mechanism is proposed to enable households to participate in demand response services. Half-hour-ahead rolling optimization and a real-time control strategy are combined to achieve household economic benefits and ability to deal with complex operating environments. A fuzzy logic controller is utilized to determine battery charging/ discharging power; proper rules are proposed to ensure benefits from operating the battery under the real-time electricity price. The simulation test results indicate that the proposed control approach can optimize the schedule for home appliances and battery charging/ discharging behavior, even if the forecasted information is not accurate. A physical test platform has also been established and tested in the lab to support the operation of the whole system.     

APPLICATION OF STATIC VAR COMPENSATION FOR LOAD FREQUENCY CONTROL

ABSTRACT

In this paper the problem of designing load frequency control CLFO system which reduces frequency oscillation based on static Var compensation (SVC) has been investigated. A linear model of a power system area has been used, and a new feedback control signal sent from SVC to power houses is suggested. The new feedback controller includes the frequency deviation and the change of reactive power due to SVC. The dynamic response of the system is determined in the presence of the suggested control system and compared with the case of no control action to evaluate the capabilities of the proposed control system.