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Load frequency control of three area interconnected hydro-thermal reheat power system using artificial intelligence and PI controllers
S Prakash, SK Sinha
International Journal of Engineering, Science and Technology , 2012,
Abstract: This paper present analysis on dynamic performance of Load Frequency Control (LFC) of three area interconnected hydrothermal reheat power system by the use of Artificial Intelligent and PI Controller. In the proposed scheme, control methodology developed using conventional PI controller, Artificial Neural Network (ANN) and Fuzzy Logic controller (FLC) for three area interconnected hydro-thermal reheat power system. In this paper area-1 and area-2 consists of thermal reheat power plant whereas area-3 consists of hydro power plant. In this proposed scheme, the combination of most complicated system like hydro plant and thermal plant with reheat turbine are interconnected which increases the nonlinearity of the system. The performances of the controllers are simulated using MATLAB/SIMULINK package. A comparison of PI controller, Fuzzy controller and ANN controller based approaches shows the superiority of proposed ANN based approach over Fuzzy and PI for same conditions. To enhance the performance of PI, Fuzzy and neural controller sliding surface is included. The simulation results also tabulated as a comparative performance in view of settling time and peak over shoot.
Power System Restoration Index for Load Frequency Control Assessment Using Artificial Bee Colony Algorithm in a Two-Area Reheat Interconnected Power System Co-ordinated with SMES Units  [PDF]
R . Jayanthi,I.A.Chidambaram
International Journal of Soft Computing & Engineering , 2012,
Abstract: This paper proposes evaluation of Restoration Indices for the Load-Frequency Control assessment of a Two-Area Two Unit Interconnected Power System (TATURIPS) coordinated with Superconducting Magnetic Energy Storage (SMES) units. As Proportional Integral (PI) type controller is still widely used for the solution of the Load Frequency Control (LFC) problem, in this paper also PI controllers are used. The optimal gain tuning of PI controllers for various case studies for the LFC problem is proposed and obtained using Artificial Bee Colony (ABC) algorithm. These controllers are designed and implemented in a TATURIPS coordinated without and with SMES units. The system was simulated and the frequency deviations, tie-line power deviation, control input deviations and additional mechanical power generation required for step load disturbance of 0.01 p.u.MW and 0.04 p.u.MW without and with outage condition in area-1 are presented. The simulation results and the evaluation of the Restoration Indices shows that the TATURIPS coordinated with SMES units ensures a better transient and steady state response and improved Restoration Indices than that of TATURIPS without SMES Units.
Computational Analysis of Different Artificial Intelligence Based Optimization Techniques for Optimal Power Flow and Economic Load Dispatch Problem  [cached]
Netra M Lokhande,Debirupa Hore
International Journal of Computers & Technology , 2013,
Abstract: The purpose of this paper is to present a computational Analysis of various Artificial Intelligence based optimization Techniques used to solve OPF problems. The various Artificial Intelligence methods such as Genetic Algorithm(GA), Particle Swarm Optimization(PSO), Bacterial Foraging Optimization(BFO), ANN are studied and analyzed in detail. The objective of an Optimal Power Flow (OPF) algorithm is to find steady state operation point which minimizes generation cost and transmission loss etc. or maximizes social welfare, load ability etc. while maintaining an acceptable system performance in terms of limits on generators’ real and reactive powers, power flow limits, output of various compensating devices etc. Traditionally, Classical optimization methods were used effectively to solve optimal power flow. But, recently due to the incorporation of FACTS devices and deregulation of power sector the traditional concepts and practices of power systems are superimposed by an economic market management and hence OPF have become more complex. So, in recent years, Artificial Intelligence (AI) methods have been emerged which can solve highly complex OPF problems at faster rate.
Modified Genetic Algorithm Based Load Frequency Controller for Interconnected Power Systems
S. Ramesh,A. Krishnan
International Journal of Electrical and Power Engineering , 2012,
Abstract: Power engineers have the responsibility to deliver economically, adequate and quality power to the consumers. In order to achieve this, the power system must be maintained at the desired operating level by suitable modern control strategies. The controlling of power system is becoming increasingly more complex due to large interconnections. The load frequency control is very important in power system operation and control for supplying sufficient and reliable electric power with good quality. This study deals with the application of real coded genetic algorithm for optimizing the gain of a proportional integral controller for load frequency control of interconnected power systems. Non-linearities such as Governor Dead Band (GDB) and Generation Rate Constraints (GRC) for a two-area reheat thermal power system have been included. Floating point representation has been used, since it is more consistent, more precise and leads to faster convergence. The simulation results confirm the designed control performance of the proposed controller.
An Investigation of ANN based PID Controllers using Three- Area Load Frequency Control in Interconnected Power System
V.Shanmuga Sundaram ,,Dr. T.Jayabharathi
International Journal of Engineering Science and Technology , 2011,
Abstract: The LFC problem, which is the major requirement in parallel operation of several interconnected systems, is one of very important subjects in power system studies. In this study, the power systems with threeareas connected through tie-lines are considered. The perturbation of frequencies at the areas and resulting tieline power flows arise due to unpredictable load variations that cause mismatch between the generated and demanded powers. The objective of LFC is to minimize the transient deviations and to provide zero steady state errors of these variables in a very short time. Variation in load frequency is an index for normal operation of power systems. When load Perturbation takes place anywhere in any area of the system, it will affect the frequency at other areas also. To control load frequency of power systems various controllers are used in different areas, but due to non-linearity's in the system components and alternators, these controllers cannot control the frequency quickly and efficiently. The simple neural networks can alleviate this difficulty. This paper deals with various controllers like proportional integral (PI), Proportional Integral Derivative (PID) andANN (Artificial neural network) tuned PID controller for three area load frequency control.The performance of the PID type controller with fixed gain, Conventional integral controller (PI) and ANN based PID (ANN-PID) controller have been compared through MATLAB Simulation results. Comparison of performance responses of integral controller & PID controller show that the ANN- PID controller has quite satisfactory generalization capability, feasibility and reliability, as well as accuracy in three area system. The qualitative and quantitative comparison have been carried out for Integral,PID and ANN- PID controllers. The superiority of the performance of ANN over integral and PID controller is highlighted.
Robust Distributed Model Predictive Load Frequency Control of Interconnected Power System  [PDF]
Xiangjie Liu,Huiyun Nong,Ke Xi,Xiuming Yao
Mathematical Problems in Engineering , 2013, DOI: 10.1155/2013/468168
Abstract: Considering the load frequency control (LFC) of large-scale power system, a robust distributed model predictive control (RDMPC) is presented. The system uncertainty according to power system parameter variation alone with the generation rate constraints (GRC) is included in the synthesis procedure. The entire power system is composed of several control areas, and the problem is formulated as convex optimization problem with linear matrix inequalities (LMI) that can be solved efficiently. It minimizes an upper bound on a robust performance objective for each subsystem. Simulation results show good dynamic response and robustness in the presence of power system dynamic uncertainties. 1. Introduction The load frequency control (LFC) has long been a much concerned research interest for power system engineers over the past forty years [1]. In modern power system, undesirable frequency and scheduled tie-line power changes in multiarea power system are a direct result of the imbalance between generated power and system demand plus associated system losses. The main objectives of the LFC are to keep the system frequency at the scheduled value and regulate the generator units to make the area control error tend to zero under the continuous adjustment of active power, so that the generation of the entire system and the load power well match. In a practical power system, there exist different kinds of uncertainties, such as changes in parameter. And each control area contains various disturbances due to increased complexity, system modeling errors, and changing power system structure. Thus the robustness must be taken into theoretical consideration in the LFC design procedure to promise high power quality. A fixed controller based on classical theory is not very suitable for the LFC problem. It is necessary that a flexible controller should be developed [2–4]. Robust LFC was early designed based on the Riccati equation approach [5], which is simple and effective and can ensure the overall system to be asymptotically stable for all admissible uncertainties. Motivated by the large uncertainty in dynamic models of power system components and their interconnections, paper [6] proposes a physically motivated passivity objective as a means to achieve effective closed-loop control. Recently, robust LFC can be realized using linear matrix inequalities [7], fuzzy logic [8], neural networks [9], and genetic algorithms [10]. Model predictive control (MPC) has been an attracting method for power system LFC, which can perform an optimization procedure to calculate optimal
Load Frequency Control of Interconnected Hydro-Thermal System with Conventional Controllers and Expert Controllers  [cached]
Krishan Arora,Baljinder Singh
Buletin Teknik Elektro dan Informatika , 2012,
Abstract: Load-frequency control (LFC) is a part of the Automatic Generation Control (AGC) in power systems, the aim of which is to maintain the system frequency and tie line flow at their scheduled values during normal period in an interconnected system. This research paper is devoted to explore the interconnection of the load frequency control of hydro power system and the thermal system. The thermal system is comprised with governor dead band, generation rate constraint and boiler dynamics where as the hydro system is comprised with generation rate constraint. The conventional PID controller does not have adequate control performance with the consideration of nonlinearities and boiler dynamics. To overcome this drawback, Genetic Algorithm helps in solving optimization problems by exploitation of random search. The aim of the proposed expert controller is to restore the frequency to its nominal value in the smallest possible time whenever there is any change in the load demand etc.
AUTOMATIC GENERATION CONTROL OF MULTI AREA POWER SYSTEMS USING ANN CONTROLLER
Bipasha Bhatia,Mrs. Sanju Saini,Dr. Narender Kumar
International Journal of Engineering Science and Technology , 2012,
Abstract: This paper presents the use of one of the methods of artificial intelligence to study the automatic generation control of interconnected power systems. In the given paper, a control line of track is established for interconnected three area thermal-thermal-thermal power system using generation rate constraints (GRC) &Artificial Neural Network (ANN). The working of the controllers is simulated using MATLAB/SIMULINK package. The outputs using both controllers are compared and it is established that ANN based approach is better than GRC for 1% step load conditions.
Load Frequency Control in Interconnected Power System Using Multi-Objective PID Controller  [PDF]
K. Sabahi,A. Sharifi,M. Aliyari Sh.,M. Teshnehlab
Journal of Applied Sciences , 2008,
Abstract: In this study, designing of multi-objective (MO) proportional, integral and derivative (PID) controller for load frequency control (LFC) based on adaptive weighted particle swarm optimization (AWPSO) has been proposed. Unlike single objective optimizations methods, MO optimization can find different solutions in a single run and we can select appropriate and desirable solution based on valuation to the objects. In this study for PID controller design, overshoot/undershoot and settling time are used as objective functions for MO optimization in LFC problem. So that various solutions with different overshoot/undershoot and settling time obtained. From these different PID parameters, one can select a single solution based on valuation to objects and as well as system constraints, reliability etc. The proposed method is used for designing of PID parameters for two area interconnected power system. From the simulation results, efficiency of proposed controller design can be seen.
计及时滞的互联电网负荷频率控制最优分数阶PID控制器设计
Optimal fractional-order PID controller design for interconnected power grid load frequency control considering time-delay
 [PDF]

左剑,王子琪,李银红,段献忠
控制理论与应用 , 2017, DOI: 10.7641/CTA.2017.60959
Abstract: 分数阶PID控制器相比于传统整数阶PID控制器, 具有控制性能好、鲁棒性强等诸多优势, 可应用于电网的 负荷频率控制(load frequency control, LFC)中. 针对网络化时滞互联电网的LFC问题, 提出了一种基于计算智能的分 数阶PID控制器参数优化整定方案. 该方案选择时滞LFC系统时域输出响应构建优化目标函数, 采用最近提出的灰 狼优化算法获得最优的分数阶PID控制器参数, 所设计的控制器能确保一定时滞区间内LFC系统的稳定性. 仿真算 例表明, 所设计的LFC最优分数阶PID控制器比传统整数阶PID控制器的控制性能更优, 时滞鲁棒性更强.
Fractional-order PID controller, with the advantages of better performance and stronger robustness compared to traditional integer-order PID controller, can be applied to load frequency control (LFC) of interconnected power grid. A computational intelligence algorithm based parameter optimizing and tuning scheme of fractional-order PID controller is proposed in this paper for the complicated problems of networked time-delay interconnected power grid LFC. The timedomain output response of time-delay LFC system is modeled as an optimization objective function of the proposed scheme. The recently developed metaheuristic algorithm known as GreyWolf Optimizer algorithm is employed to iteratively identify the optimal parameters of fractional-order PID controller. The designed controller can guarantee the stability of the LFC system within a certain time-delay interval. The simulation results demonstrate that the designed optimal fractional-order PID controller has better control performance and stronger time-delay robustness than conventional integer-order PID controller.
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