This document discusses the performance of hybrid intelligent controllers for load frequency control in multi-area interconnected power systems. It compares the performance of adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN), fuzzy, PI, and PID controllers. ANFIS combines the advantages of fuzzy systems and ANN's quick response and adaptability. The document finds that ANFIS has superior performance over ANN, fuzzy, PI, and PID controllers for a 1% step load variation based on simulations in MATLAB/Simulink of a four area hydro-thermal power system.
1) The document presents a framework for automatic generation control (AGC) in a two-area restructured power system with non-linear governor characteristics, including hydro-hydro systems.
2) It models the addition of a frequency stabilizer equipped with an energy storage system to stabilize frequency and tie-line power oscillations under disturbances.
3) The gains of controllers and parameters of the stabilizer are optimized using genetic algorithms. Simulations show the response of the optimized load frequency controller under different transactions in the restructured electricity market.
A New Control Method for the Multi-Area LFC System Based on Port-Hamiltonian ...IRJET Journal
This document presents a new control method for load frequency control (LFC) in a multi-area power system based on Port-Hamiltonian and cascade systems. The proposed method uses PID control laws that decouple total tie-line power flow and provide robust disturbance rejection. Simulation results in Matlab/Simulink validate that the proposed method performs better than existing PID methods by achieving faster response speeds and smaller overshoots for changes in tie-line power and frequency deviations in both two-area and four-area test systems with and without reheated turbines.
Parallel control structure scheme for load frequency controller design using ...IJECEIAES
This paper presents load frequency controller design for a single area as well as the multi-area thermal power system using direct synthesis approach with parallel control structure (PCS) scheme. The set-point and load frequency controller has been designed for frequency regulation and maintains tie-line power within a pre-specified limit for LFC power system. The proposed controller has been implemented for single-area, two-area, and four-area thermal power system for frequency regulation. The proposed method shows impressive simulation results compared with existed control method. The robustness of the proposed method has been examined with the help maximum sensitivity and parametric variation in the nominal power system.
The document provides information about the structure, operation, and control of power systems. It discusses:
1) The typical structure of power systems including generation, transmission, and distribution systems organized into interconnected regional grids and pools.
2) SCADA and EMS systems which monitor power system parameters, send real-time data to control centers, and support functions like generation control, scheduling, forecasting, and contingency analysis to guide optimal system operation.
3) Key aspects of power system operation and control including load frequency control, automatic voltage control, state estimation, and flexible AC transmission systems which maintain system stability and security through monitoring and automated response.
IRJET- Load Frequency Control of a Renewable Source Integrated Four Area ...IRJET Journal
This document discusses using an adaptive neuro-fuzzy inference system (ANFIS) approach for automatic load frequency control of a four-area power system with multiple generation sources including renewable sources. The system consists of four equal areas, each with two thermal plants, a hydro plant, a wind plant, and an HVDC link. ANFIS combines the advantages of neural networks and fuzzy logic. The proposed ANFIS-PID controller is simulated and its performance is compared to a PID controller in response to a 1% load change in each area. Simulation results show the ANFIS-PID controller improves the system's dynamic response.
PaperLoad following in a deregulated power system with Thyristor Controlled S...rajeshja
Load following is considered to be an ancillary service in a deregulated power system. This paper investigates
the effect of a Thyristor Controlled Series Compensator (TCSC) for load following in a deregulated
two area interconnected thermal system with two GENCOs and two DISCOs in either areas. Optimal
gain settings of the integral controllers in the control areas are obtained using Genetic Algorithm by
minimizing a quadratic performance index. Simulation studies carried out in MATLAB validates that a
Thyristor Controlled Series Compensator in series with tie-line can effectively improve the load following
performance of the power system in a deregulated environment.
DESIGN OF CONTROL STRATEGIES FOR THE LOAD FREQUENCY CONTROL (LFC) IN MULTI AR...IAEME Publication
This paper features the Differential Evolution (DE) by controller parameters tuning algorithm
and also an application of a multi source power system to a Load Frequency Control (LFC) by
having several sources of power generation techniques. At first, a single area multi-source power
system using integral controllers for every unit is taken and DE procedure is implemented to attain
the controller parameters. Several mutation procedures of DE are estimated and the control
parameters of DE for best obtained procedure are tuned by implementing numerous runs of
algorithm for every change in parameter. Multi-area multi-source power system is also discussed
and a HDVC link is also taken in accordance with the current AC tie line for the internal
connection between the areas. The two variables of Integrals which are to be enhanced using tuned
DE algorithm are proportional integral and proportional integral derivative.
Optimal Placement of DG for Loss Reduction and Voltage Sag Mitigation in Radi...IDES Editor
This paper presents the need to operate the power
system economically and with optimum levels of voltages has
further led to an increase in interest in Distributed
Generation. In order to reduce the power losses and to improve
the voltage in the distribution system, distributed generators
(DGs) are connected to load bus. To reduce the total power
losses in the system, the most important process is to identify
the proper location for fixing and sizing of DGs. It presents a
new methodology using a new population based meta heuristic
approach namely Artificial Bee Colony algorithm(ABC) for
the placement of Distributed Generators(DG) in the radial
distribution systems to reduce the real power losses and to
improve the voltage profile, voltage sag mitigation. The power
loss reduction is important factor for utility companies because
it is directly proportional to the company benefits in a
competitive electricity market, while reaching the better power
quality standards is too important as it has vital effect on
customer orientation. In this paper an ABC algorithm is
developed to gain these goals all together. In order to evaluate
sag mitigation capability of the proposed algorithm, voltage
in voltage sensitive buses is investigated. An existing 20KV
network has been chosen as test network and results are
compared with the proposed method in the radial distribution
system.
1) The document presents a framework for automatic generation control (AGC) in a two-area restructured power system with non-linear governor characteristics, including hydro-hydro systems.
2) It models the addition of a frequency stabilizer equipped with an energy storage system to stabilize frequency and tie-line power oscillations under disturbances.
3) The gains of controllers and parameters of the stabilizer are optimized using genetic algorithms. Simulations show the response of the optimized load frequency controller under different transactions in the restructured electricity market.
A New Control Method for the Multi-Area LFC System Based on Port-Hamiltonian ...IRJET Journal
This document presents a new control method for load frequency control (LFC) in a multi-area power system based on Port-Hamiltonian and cascade systems. The proposed method uses PID control laws that decouple total tie-line power flow and provide robust disturbance rejection. Simulation results in Matlab/Simulink validate that the proposed method performs better than existing PID methods by achieving faster response speeds and smaller overshoots for changes in tie-line power and frequency deviations in both two-area and four-area test systems with and without reheated turbines.
Parallel control structure scheme for load frequency controller design using ...IJECEIAES
This paper presents load frequency controller design for a single area as well as the multi-area thermal power system using direct synthesis approach with parallel control structure (PCS) scheme. The set-point and load frequency controller has been designed for frequency regulation and maintains tie-line power within a pre-specified limit for LFC power system. The proposed controller has been implemented for single-area, two-area, and four-area thermal power system for frequency regulation. The proposed method shows impressive simulation results compared with existed control method. The robustness of the proposed method has been examined with the help maximum sensitivity and parametric variation in the nominal power system.
The document provides information about the structure, operation, and control of power systems. It discusses:
1) The typical structure of power systems including generation, transmission, and distribution systems organized into interconnected regional grids and pools.
2) SCADA and EMS systems which monitor power system parameters, send real-time data to control centers, and support functions like generation control, scheduling, forecasting, and contingency analysis to guide optimal system operation.
3) Key aspects of power system operation and control including load frequency control, automatic voltage control, state estimation, and flexible AC transmission systems which maintain system stability and security through monitoring and automated response.
IRJET- Load Frequency Control of a Renewable Source Integrated Four Area ...IRJET Journal
This document discusses using an adaptive neuro-fuzzy inference system (ANFIS) approach for automatic load frequency control of a four-area power system with multiple generation sources including renewable sources. The system consists of four equal areas, each with two thermal plants, a hydro plant, a wind plant, and an HVDC link. ANFIS combines the advantages of neural networks and fuzzy logic. The proposed ANFIS-PID controller is simulated and its performance is compared to a PID controller in response to a 1% load change in each area. Simulation results show the ANFIS-PID controller improves the system's dynamic response.
PaperLoad following in a deregulated power system with Thyristor Controlled S...rajeshja
Load following is considered to be an ancillary service in a deregulated power system. This paper investigates
the effect of a Thyristor Controlled Series Compensator (TCSC) for load following in a deregulated
two area interconnected thermal system with two GENCOs and two DISCOs in either areas. Optimal
gain settings of the integral controllers in the control areas are obtained using Genetic Algorithm by
minimizing a quadratic performance index. Simulation studies carried out in MATLAB validates that a
Thyristor Controlled Series Compensator in series with tie-line can effectively improve the load following
performance of the power system in a deregulated environment.
DESIGN OF CONTROL STRATEGIES FOR THE LOAD FREQUENCY CONTROL (LFC) IN MULTI AR...IAEME Publication
This paper features the Differential Evolution (DE) by controller parameters tuning algorithm
and also an application of a multi source power system to a Load Frequency Control (LFC) by
having several sources of power generation techniques. At first, a single area multi-source power
system using integral controllers for every unit is taken and DE procedure is implemented to attain
the controller parameters. Several mutation procedures of DE are estimated and the control
parameters of DE for best obtained procedure are tuned by implementing numerous runs of
algorithm for every change in parameter. Multi-area multi-source power system is also discussed
and a HDVC link is also taken in accordance with the current AC tie line for the internal
connection between the areas. The two variables of Integrals which are to be enhanced using tuned
DE algorithm are proportional integral and proportional integral derivative.
Optimal Placement of DG for Loss Reduction and Voltage Sag Mitigation in Radi...IDES Editor
This paper presents the need to operate the power
system economically and with optimum levels of voltages has
further led to an increase in interest in Distributed
Generation. In order to reduce the power losses and to improve
the voltage in the distribution system, distributed generators
(DGs) are connected to load bus. To reduce the total power
losses in the system, the most important process is to identify
the proper location for fixing and sizing of DGs. It presents a
new methodology using a new population based meta heuristic
approach namely Artificial Bee Colony algorithm(ABC) for
the placement of Distributed Generators(DG) in the radial
distribution systems to reduce the real power losses and to
improve the voltage profile, voltage sag mitigation. The power
loss reduction is important factor for utility companies because
it is directly proportional to the company benefits in a
competitive electricity market, while reaching the better power
quality standards is too important as it has vital effect on
customer orientation. In this paper an ABC algorithm is
developed to gain these goals all together. In order to evaluate
sag mitigation capability of the proposed algorithm, voltage
in voltage sensitive buses is investigated. An existing 20KV
network has been chosen as test network and results are
compared with the proposed method in the radial distribution
system.
Design and Performance Analysis of Genetic based PID-PSS with SVC in a Multi-...IDES Editor
Damping of power system oscillations with the help
of proposed optimal Proportional Integral Derivative Power
System Stabilizer (PID-PSS) and Static Var Compensator
(SVC)-based controllers are thoroughly investigated in this
paper. This study presents robust tuning of PID-PSS and
SVC-based controllers using Genetic Algorithms (GA) in
multi machine power systems by considering detailed model
of the generators (model 1.1). The effectiveness of FACTSbased
controllers in general and SVC-based controller in
particular depends upon their proper location. Modal
controllability and observability are used to locate SVC–based
controller. The performance of the proposed controllers is
compared with conventional lead-lag power system stabilizer
(CPSS) and demonstrated on 10 machines, 39 bus New England
test system. Simulation studies show that the proposed genetic
based PID-PSS with SVC based controller provides better
performance.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
This document presents a new control structure using a PID controller for load frequency control of power systems. The control structure places the PID controller in the feedback loop to improve disturbance rejection and robustness against plant parameter uncertainties. A relay feedback method is used to identify lower order transfer function models with time delay from typically higher order power system models. The PID controller parameters are then tuned using Laurent series expansion of the closed loop transfer function to provide improved performance for disturbance rejection while maintaining robustness. Simulation results on single-area and multi-area power system models demonstrate the effectiveness of the proposed control structure and PID controller design method.
Automatic Generation Control of Multi-Area Power System with Generating Rate ...IJAPEJOURNAL
In a large inter-connected system, large and small generating stations are synchronously connected and hence all stations must have the same frequency. The system frequency deviation is the sensitive indicator of real power imbalance. The main objectives of AGC are to maintain constant frequency and tie-line errors with in prescribed limit. This paper presents two new approaches for Automatic Generation Control using i) combined Fuzzy Logic and Artificial Neural Network Controller (FLANNC) and ii) Hybrid Neuro Fuzzy Controller (HNFC) with gauss membership functions. The simulation model is created for four-area interconnected power system. In this four area system, three areas consist of steam turbines and one area consists of hydro turbine. The components of ACE, frequency deviation (F) and tie line error (Ptie) are obtained through simulation model and used to produce the required control action to achieve AGC using i) FLANNC and ii) HNFC with gauss membership functions. The simulation results show that the proposed controllers overcome the drawbacks associated with conventional integral controller, Fuzzy Logic Controller (FLC), Artificial Neural Network controller (ANNC) and HNFC with gbell membership functionsv
Automatic load frequency control of two area power system with conventional a...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Current predictive controller for high frequency resonant inverter in inducti...IJECEIAES
This document discusses current predictive control for a high frequency resonant inverter used in induction heating applications. It begins with modeling the inductor-load system powered by the inverter. It then discusses generalized predictive control (GPC), including using a prediction model, minimizing a cost function to determine the optimal control signal, and applying the first value of the control signal sequence. Simulation results show the GPC controller provides accurate current tracking with fast response times and no overshoot, even when the reference current amplitude varies. The control is robust to parameter changes in the inductor-load system.
Artificial Intelligence Technique based Reactive Power Planning Incorporating...IDES Editor
This document summarizes a research paper that proposes using artificial intelligence techniques and FACTS controllers for reactive power planning in real-time power transmission systems. The paper formulates the reactive power planning problem and incorporates flexible AC transmission system (FACTS) devices like static VAR compensators (SVC), thyristor controlled series capacitors (TCSC), and unified power flow controllers (UPFC). Evolutionary algorithms like evolutionary programming (EP) and differential evolution (DE) are applied to find the optimal locations and settings of the FACTS controllers to minimize losses and costs. Simulation results on IEEE 30-bus and 72-bus Indian test systems show that UPFC performs best in reducing losses compared to SVC and TCSC.
1. The document discusses various concepts related to power system operation and control including load forecasting, load curves, frequency regulation, and load frequency control.
2. Key terms defined include load factor, plant capacity factor, maximum demand, plant use factor, diversity factor, demand factor, spinning reserve, and area control error.
3. Factors affecting load forecasting are discussed including the need for long term, medium term, and short term forecasting for various power system planning and operation purposes.
Line Losses in the 14-Bus Power System Network using UPFCIDES Editor
Controlling power flow in modern power systems
can be made more flexible by the use of recent developments
in power electronic and computing control technology. The
Unified Power Flow Controller (UPFC) is a Flexible AC
transmission system (FACTS) device that can control all the
three system variables namely line reactance, magnitude and
phase angle difference of voltage across the line. The UPFC
provides a promising means to control power flow in modern
power systems. Essentially the performance depends on proper
control setting achievable through a power flow analysis
program. This paper presents a reliable method to meet the
requirements by developing a Newton-Raphson based load
flow calculation through which control settings of UPFC can
be determined for the pre-specified power flow between the
lines. The proposed method keeps Newton-Raphson Load Flow
(NRLF) algorithm intact and needs (little modification in the
Jacobian matrix). A MATLAB program has been developed to
calculate the control settings of UPFC and the power flow
between the lines after the load flow is converged. Case studies
have been performed on IEEE 5-bus system and 14-bus system
to show that the proposed method is effective. These studies
indicate that the method maintains the basic NRLF properties
such as fast computational speed, high degree of accuracy and
good convergence rate.
Performance Evaluation of GA optimized Shunt Active Power Filter for Constant...ijeei-iaes
Sinusoidal Current Control strategy for extracting reference currents for shunt active power filters have been modified using Genetic Algorithm and its performances have been compared. The acute analysis of Comparison of the compensation capability based on THD and speedwell be done, and recommendations will be given for the choice of technique to be used. The simulated results using MATLAB model are shown, and they will undoubtedly prove the importance of the proposed control technique of aircraft shunt APF.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
The document describes using a Proportional Integral Derivative (PID) controller tuned with Internal Model Control (IMC) technique for Automatic Load Frequency Control (LFC) of a two area power system. It presents the system model of a two area power system and derives the control equations. It then discusses designing an IMC-PID controller for LFC by first designing an IMC controller and transforming it into an equivalent PID structure. Simulation results show the IMC-PID controller provides better stability and dynamic response for LFC compared to a conventional integral controller.
There are three main types of frequency regulation in power grids: flat frequency regulation where individual generators respond to local load changes, parallel frequency regulation where load changes are distributed among multiple generators, and flat-tie line loading where local generators supply local loads while maintaining constant power flow between regions. Frequency in power systems is controlled through generator governors and automatic generation control (AGC) loops. Governor response acts as primary control to instantly adjust generator output to frequency deviations. AGC acts as secondary control to coordinate multiple generators and maintain scheduled interchange power between control areas.
A Review of Analysis and Modeling of Grid Connected Three Phase Multilevel Un...IRJET Journal
This document reviews a five-level multiple-pole structure for a grid connected three phase multilevel unity power rectifier that aims to improve power factor and reduce total harmonic distortion using fewer components. The proposed design is a five-level/multiple-pole multilevel unity power factor rectifier that achieves unity power factor and input current shaping with a reduced number of components. It uses a simple control method based on average current control at a low switching frequency to compensate for grid current harmonics. Simulation results show the design has better dynamic response and tracking under unbalanced grid conditions compared to other existing rectifier topologies.
Fuzzy and predictive control of a photovoltaic pumping system based on three-...journalBEEI
1) The document proposes control schemes for a photovoltaic pumping system based on a three-level boost converter and induction motor. A fuzzy logic controller is used for maximum power point tracking and a phase shift technique balances the voltages across the converter capacitors.
2) A cascaded nonlinear predictive controller is applied to control the induction motor, offering advantages over conventional field-oriented control such as improved torque response and parameter sensitivity.
3) Simulation results show the proposed controllers increase hydraulic power by up to 23% during startup and 10% in steady state compared to conventional controllers.
International Journal of Engineering Inventions (IJEI) provides a multidisciplinary passage for researchers, managers, professionals, practitioners and students around the globe to publish high quality, peer-reviewed articles on all theoretical and empirical aspects of Engineering and Science.
The peer-reviewed International Journal of Engineering Inventions (IJEI) is started with a mission to encourage contribution to research in Science and Technology. Encourage and motivate researchers in challenging areas of Sciences and Technology.
This document presents a study on using a Battery Energy Storage System (BESS) to control load frequency in a two-area interconnected power system. Conventional control methods like integral and PID controllers were unable to adequately control oscillations due to their slow response. The document proposes incorporating a BESS model that can provide fast active power compensation. Simulation results showed that using BESS, load frequency oscillations settled within 0.5-1 seconds after a disturbance, much faster than conventional controllers. This demonstrates that BESS is an effective technique for load frequency control in power systems.
Modeling and Simulation of power system using SMIB with GA based TCSC controllerIOSR Journals
This document summarizes a study that uses genetic algorithms to tune a thyristor-controlled series compensator (TCSC) controller to improve the stability of a single-machine infinite-bus (SMIB) power system model. The study models the SMIB system and implements a TCSC to damp oscillations. Genetic algorithms are used to optimize the TCSC controller parameters. Simulation results show that the genetically-tuned TCSC controller more effectively damps oscillations compared to the system without a TCSC controller.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Comparative Analysis of Different Controllers in Two–Area Hydrothermal Power ...IRJET Journal
This document compares the performance of different controllers for regulating frequency and power interchange in a two-area hydrothermal power system under step load disturbances. It summarizes the system model, describes several conventional controllers (PI, PID) and their tuning using Ziegler-Nichols methods. It also outlines an intelligent fuzzy logic controller with Mamdani fuzzy inference and describes its design and rule base. Simulation results show that the fuzzy logic controller achieves better dynamic response and steady-state error than the conventional controllers.
Differential game approach for the analysis of two area load frequency controlIRJET Journal
This document discusses using a differential game approach for analyzing load frequency control in a two-area power system. It first provides background on load frequency control and describes the traditional proportional-integral controller approach. It then introduces differential games as a tool for solving multi-objective optimization problems and proposes applying a cooperative differential game to control the two areas. The game would derive non-cooperative and cooperative equilibrium solutions to maintain system frequency stability and balance generation and loads across areas. Simulation results would compare this approach to traditional control methods.
Design and Performance Analysis of Genetic based PID-PSS with SVC in a Multi-...IDES Editor
Damping of power system oscillations with the help
of proposed optimal Proportional Integral Derivative Power
System Stabilizer (PID-PSS) and Static Var Compensator
(SVC)-based controllers are thoroughly investigated in this
paper. This study presents robust tuning of PID-PSS and
SVC-based controllers using Genetic Algorithms (GA) in
multi machine power systems by considering detailed model
of the generators (model 1.1). The effectiveness of FACTSbased
controllers in general and SVC-based controller in
particular depends upon their proper location. Modal
controllability and observability are used to locate SVC–based
controller. The performance of the proposed controllers is
compared with conventional lead-lag power system stabilizer
(CPSS) and demonstrated on 10 machines, 39 bus New England
test system. Simulation studies show that the proposed genetic
based PID-PSS with SVC based controller provides better
performance.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
This document presents a new control structure using a PID controller for load frequency control of power systems. The control structure places the PID controller in the feedback loop to improve disturbance rejection and robustness against plant parameter uncertainties. A relay feedback method is used to identify lower order transfer function models with time delay from typically higher order power system models. The PID controller parameters are then tuned using Laurent series expansion of the closed loop transfer function to provide improved performance for disturbance rejection while maintaining robustness. Simulation results on single-area and multi-area power system models demonstrate the effectiveness of the proposed control structure and PID controller design method.
Automatic Generation Control of Multi-Area Power System with Generating Rate ...IJAPEJOURNAL
In a large inter-connected system, large and small generating stations are synchronously connected and hence all stations must have the same frequency. The system frequency deviation is the sensitive indicator of real power imbalance. The main objectives of AGC are to maintain constant frequency and tie-line errors with in prescribed limit. This paper presents two new approaches for Automatic Generation Control using i) combined Fuzzy Logic and Artificial Neural Network Controller (FLANNC) and ii) Hybrid Neuro Fuzzy Controller (HNFC) with gauss membership functions. The simulation model is created for four-area interconnected power system. In this four area system, three areas consist of steam turbines and one area consists of hydro turbine. The components of ACE, frequency deviation (F) and tie line error (Ptie) are obtained through simulation model and used to produce the required control action to achieve AGC using i) FLANNC and ii) HNFC with gauss membership functions. The simulation results show that the proposed controllers overcome the drawbacks associated with conventional integral controller, Fuzzy Logic Controller (FLC), Artificial Neural Network controller (ANNC) and HNFC with gbell membership functionsv
Automatic load frequency control of two area power system with conventional a...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Current predictive controller for high frequency resonant inverter in inducti...IJECEIAES
This document discusses current predictive control for a high frequency resonant inverter used in induction heating applications. It begins with modeling the inductor-load system powered by the inverter. It then discusses generalized predictive control (GPC), including using a prediction model, minimizing a cost function to determine the optimal control signal, and applying the first value of the control signal sequence. Simulation results show the GPC controller provides accurate current tracking with fast response times and no overshoot, even when the reference current amplitude varies. The control is robust to parameter changes in the inductor-load system.
Artificial Intelligence Technique based Reactive Power Planning Incorporating...IDES Editor
This document summarizes a research paper that proposes using artificial intelligence techniques and FACTS controllers for reactive power planning in real-time power transmission systems. The paper formulates the reactive power planning problem and incorporates flexible AC transmission system (FACTS) devices like static VAR compensators (SVC), thyristor controlled series capacitors (TCSC), and unified power flow controllers (UPFC). Evolutionary algorithms like evolutionary programming (EP) and differential evolution (DE) are applied to find the optimal locations and settings of the FACTS controllers to minimize losses and costs. Simulation results on IEEE 30-bus and 72-bus Indian test systems show that UPFC performs best in reducing losses compared to SVC and TCSC.
1. The document discusses various concepts related to power system operation and control including load forecasting, load curves, frequency regulation, and load frequency control.
2. Key terms defined include load factor, plant capacity factor, maximum demand, plant use factor, diversity factor, demand factor, spinning reserve, and area control error.
3. Factors affecting load forecasting are discussed including the need for long term, medium term, and short term forecasting for various power system planning and operation purposes.
Line Losses in the 14-Bus Power System Network using UPFCIDES Editor
Controlling power flow in modern power systems
can be made more flexible by the use of recent developments
in power electronic and computing control technology. The
Unified Power Flow Controller (UPFC) is a Flexible AC
transmission system (FACTS) device that can control all the
three system variables namely line reactance, magnitude and
phase angle difference of voltage across the line. The UPFC
provides a promising means to control power flow in modern
power systems. Essentially the performance depends on proper
control setting achievable through a power flow analysis
program. This paper presents a reliable method to meet the
requirements by developing a Newton-Raphson based load
flow calculation through which control settings of UPFC can
be determined for the pre-specified power flow between the
lines. The proposed method keeps Newton-Raphson Load Flow
(NRLF) algorithm intact and needs (little modification in the
Jacobian matrix). A MATLAB program has been developed to
calculate the control settings of UPFC and the power flow
between the lines after the load flow is converged. Case studies
have been performed on IEEE 5-bus system and 14-bus system
to show that the proposed method is effective. These studies
indicate that the method maintains the basic NRLF properties
such as fast computational speed, high degree of accuracy and
good convergence rate.
Performance Evaluation of GA optimized Shunt Active Power Filter for Constant...ijeei-iaes
Sinusoidal Current Control strategy for extracting reference currents for shunt active power filters have been modified using Genetic Algorithm and its performances have been compared. The acute analysis of Comparison of the compensation capability based on THD and speedwell be done, and recommendations will be given for the choice of technique to be used. The simulated results using MATLAB model are shown, and they will undoubtedly prove the importance of the proposed control technique of aircraft shunt APF.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
The document describes using a Proportional Integral Derivative (PID) controller tuned with Internal Model Control (IMC) technique for Automatic Load Frequency Control (LFC) of a two area power system. It presents the system model of a two area power system and derives the control equations. It then discusses designing an IMC-PID controller for LFC by first designing an IMC controller and transforming it into an equivalent PID structure. Simulation results show the IMC-PID controller provides better stability and dynamic response for LFC compared to a conventional integral controller.
There are three main types of frequency regulation in power grids: flat frequency regulation where individual generators respond to local load changes, parallel frequency regulation where load changes are distributed among multiple generators, and flat-tie line loading where local generators supply local loads while maintaining constant power flow between regions. Frequency in power systems is controlled through generator governors and automatic generation control (AGC) loops. Governor response acts as primary control to instantly adjust generator output to frequency deviations. AGC acts as secondary control to coordinate multiple generators and maintain scheduled interchange power between control areas.
A Review of Analysis and Modeling of Grid Connected Three Phase Multilevel Un...IRJET Journal
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International Journal of Engineering Inventions (IJEI) provides a multidisciplinary passage for researchers, managers, professionals, practitioners and students around the globe to publish high quality, peer-reviewed articles on all theoretical and empirical aspects of Engineering and Science.
The peer-reviewed International Journal of Engineering Inventions (IJEI) is started with a mission to encourage contribution to research in Science and Technology. Encourage and motivate researchers in challenging areas of Sciences and Technology.
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International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
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IRJET- Load Frequency Control of a Wind Integrated Power System using Convent...IRJET Journal
This document summarizes a research paper that proposes using a fuzzy proportional-integral-derivative (FPID) controller for load frequency control of a power system integrated with wind power. The system being studied is a four-area power system with each area containing wind, hydro, and thermal power plants. Simulation results show that the system with renewable energy sources gives better dynamic response when using an FPID controller compared to using a conventional PID controller. The FPID controller is able to better suppress frequency deviations caused by load and power fluctuations from the renewable energy sources.
Study of PID Controllers to Load Frequency Control Systems with Various Turbi...IJERA Editor
This document discusses the use of PID controllers for load frequency control (LFC) systems with various turbine models. It first provides background on LFC and the objectives of maintaining constant system frequency. It then describes using PID controllers with different tuning methods, including Ziegler-Nichols and Integral Model Controller, for LFC systems with non-reheat, reheat, and hydro turbines. The document presents the transfer functions for these various turbine models. It also discusses designing PID controllers both with and without the droop characteristic to improve damping. The goal is to study PID controller design methods and tuning to improve the performance of LFC systems with different turbine types.
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Optimal design & analysis of load frequency control for two interconnecte...ijctet
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International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Comparison of Soft Computing Techniques applied in High Frequency Aircraft Sy...ijeei-iaes
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A new approach for Tuning of PID Load Frequency Controller of an Interconnect...Editor IJMTER
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International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
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This document presents a novel fuzzy logic controller methodology for load frequency control of a dynamically interconnected electric power system consisting of two areas, one with a hydraulic turbine and one with a thermal turbine. The fuzzy controller utilizes error and change of error as inputs to regulate system performance and account for varying operating conditions. It is proposed to provide robust control compared to a controller with fixed gains. The document describes the modeling of the two-area power system and load frequency control problem, and discusses designing a fuzzy control scheme to minimize frequency and tie-line deviations for the interconnected system.
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Accident detection system project report.pdfKamal Acharya
The Rapid growth of technology and infrastructure has made our lives easier. The
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Many lives could have been saved if emergency service could get accident information and
reach in time. Our project will provide an optimum solution to this draw back. A piezo electric
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signal or if a car rolls over. Then with the help of GSM module and GPS module, the location
will be sent to the emergency contact. Then after conforming the location necessary action will
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life, then the alert message can be terminated by the driver by a switch provided in order to
avoid wasting the valuable time of the medical rescue team.
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Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
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Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
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1. Performance Evaluation of Hybrid Intelligent
Controllers in Load Frequency Control of Multi
Area Interconnected Power Systems
Surya Prakash and Sunil Kumar Sinha
Abstract—This paper deals with the application of artificial
neural network (ANN) and fuzzy based Adaptive Neuro Fuzzy
Inference System(ANFIS) approach to Load Frequency Control
(LFC) of multi unequal area hydro-thermal interconnected power
system. The proposed ANFIS controller combines the advantages of
fuzzy controller as well as quick response and adaptability nature of
ANN. Area-1 and area-2 consists of thermal reheat power plant
whereas area-3 and area-4 consists of hydro power plant with electric
governor. Performance evaluation is carried out by using intelligent
controller like ANFIS, ANN and Fuzzy controllers and conventional
PI and PID control approaches. To enhance the performance of
intelligent and conventional controller sliding surface is included.
The performances of the controllers are simulated using
MATLAB/SIMULINK package. A comparison of ANFIS, ANN,
Fuzzy, PI and PID based approaches shows the superiority of
proposed ANFIS over ANN & fuzzy, PI and PID controller for 1%
step load variation.
Keywords—Load Frequency Control (LFC), ANFIS, ANN &
Fuzzy, PI, PID Controllers, Area Control Error (ACE), Tie-line,
MATLAB / SIMULINK.
I. INTRODUCTION
OAD frequency control is part of Automatic Generation
Control (AGC) which is defined as the regulation of
power out put of controllable generator within prescribed limit
in response to change in system frequency or tie-line loading
or the relation of these two each other. Many developments
have taken place in the structure of power system since its
inception. All over the world, most of the power utilities have
been operating in interconnected fashion due to numerous
economical, technical and environmental considerations. The
power transmission network plays an important role in
transporting electrical power in bulk from one power pool to
other and to distantly located load centers. Main objective of
Automatic
Generation Control (AGC) is to balance the total system
generation against system load losses so that the desired
frequency and power interchange with neighboring system is
Surya Prakash is with Department of Electrical & Electronics Engineering,
Sam Higginbottom Institute of Agriculture, Technology & Sciences-Deemed
University, Allahabad, India. (Email: sprakashgiri0571@yahoo.com).
S K Sinha is with Department of Electrical Engineering, Kamala Nehru
Institute of Technology, Sultanpur-UP, India. (Email:
sinhask98@engineers.com).
maintained. Any mismatch between generation and demand
causes the system frequency to deviate from the nominal
value. This high frequency deviation may lead to system
breakdown. AGC comprises a load frequency control (LFC)
loop and an automatic voltage regulator (AVR) loop
interconnected power systems regulate power flows and
frequency by means of an AGC. LFC system provides
generator load control via frequency zero steady-state errors
of frequency deviations and optimal transient behavior are
objectives of the LFC in a multi-area interconnected power
system [1], [2]-[5].
Literature survey shows that most of earlier work in the
area of LFC pertains to interconnected thermal system and
relatively lesser attention has been devoted to the LFC of
multi area interconnected hydro-thermal system [7]. The PI &
PID controllers are very simple for implementation and gives
better dynamic response, but their performances deteriorate
when the complexity in the system increases due to
disturbances like load variation boiler dynamics [6], [7].
Therefore, there is need of a controller which can overcome
this problem. The Artificial Intelligent controllers like Fuzzy
and Neural control approaches are more suitable in this
respect. Fuzzy system has been applied to the load frequency
control problems with rather promising results. [8], [9], [15],
[16], [19], [20], [25]. The salient feature of these techniques is
that they provide a model- free description of control systems
and do not require model identification when selecting the
specific number of membership function [9], so this has some
limitation to over come this Artificial Neural Network (ANN)
and ANFIS controllers are introduced, those have advance
adaptive control configuration [10], [20], [21]. LFC or AGC is
one of the most important issues in electric power system
design and operation for supplying sufficient and reliable
electric power with good quality. The main aim of LFC for
power system are to ensure zero steady state error for
frequency deviations, to minimize unscheduled tie line power
flows between neighboring control areas and to maintain
acceptable overshoot and settling time on the frequency and
tie line power deviation [22], [23], [24].
L
World Academy of Science, Engineering and Technology
Vol:7 2013-05-26
637 International Science Index Vol:7, No:5, 2013 waset.org/Publication/12180
2. World Academy of Science, Engineering and Technology
Vol:7 2013-05-26
638 International Science Index Vol:7, No:5, 2013 waset.org/Publication/12180
Fig. 1 MATLAB Model of four area hydro-thermal reheat power system
The main objectives of the present paper are the
following:
1. To consider four area hydrothermal system under
perturbation in a single area and simultaneously in all
areas, and then obtain system dynamic responses with
Fuzzy, ANN and ANFIS, PI and PID controllers.
2. To present a systematic and comprehensive approach for
designing ANN, Fuzzy and ANFIS based controller.
3. To compare the results of all five controllers to
investigate the superiority of controller.
4. To compare the ANFIS controller results with already
published result of Swati[26], Sudha[27] and Parmar[28]
and, then analyze the dynamic performance obtained with
the above control strategy, i.e., ANFIS based controller.
II. MULTI AREA POWER SYSTEM INVESTIGATED
The four area power system connected by tie-line is shown
in Fig. 1.
A. Modeling of the Tie-Line
Considering area 1 has surplus power and transfers to area
2.
P12 = Power transferred from area 1 to 2 through tie line.
Then power transfer equation through tie-line is given by
V . V
P 1 2
= δ δ (1)
X . Sin( 1 - 2)
12
12
where
1 δ and 2 δ = Power angles of end voltages V1 and V2
of equivalent machine of the two areas respectively.
X12 = reactance of tie line.
The order of the subscripts indicates that the tie line power
is define positive in direction 1 to 2.
For small deviation in the angles and the tie line power
changes with the amount i.e. small deviation in 1 δ and 2 δ
changes by Δδ1 andΔδ 2,
Power P12 changes to P12 + Δ P12
Therefore, Power transferred from Area 1 to Area 2 as
given in [11] is
T o P s f s f s
π
( ) 2 ( ) ( )
( ) 12 1 2
Δ = Δ −Δ (2)
s
T0 = Torque produced
In this paper, the performance evaluation based on ANN,
Fuzzy and ANFIS control technique for four areas
interconnected thermal-hydro power plant is proposed. The
sliding concept arises due to variable structure concept. The
objective of VSC has been greatly extended from stabilization
to other control functions. The most distinguished feature of
VSC is its ability to result in very robust control systems and
external disturbances [12], [13].
B. Objective of Control Areas
The main objective of the control areas are as follows:
3. World Academy of Science, Engineering and Technology
1. Each control area as for as possible should supply its own
load demand and power transfer through tie line should
be on mutual agreement.
2. Each control areas should controllable to the frequency
control. [11]
In an isolated control area case the incremental power
(ΔPG − ΔPD) was accounted for by the rate of increase of
stored kinetic energy and increase in area load caused by
increase in frequency. The state variable for each of areas are
ΔPi (i = 1,...., 4) and state space equation related to the
variables are different for each areas.
ΔP1(k) = ΔP12(k) + a41ΔP41(k) (3)
ΔP2(k) = ΔP23(k) + a12ΔP12(k) (4)
ΔP3(k) = ΔP34(k) + a23ΔP23(k) (5)
ΔP4(k) = ΔP41(k) + a34ΔP34(k) (6)
Tie-line bias control is used to eliminate steady state error
in frequency in tie-line power flow. This states that the each
control area must contribute their share to frequency control in
addition for taking care of their own net interchange.
12180
Publication/org/Let ACE1 = area control error of area 1
waset.ACE2 = Area control error of area 2
ACE3 = Area control error of area 3
2013 ACE4 = Area control error of area 4
5, In this control, ACE1, ACE2 and ACE3 are made linear
No:combination of frequency and tie line power error [11].
7, Vol:ACE1 = Δ P + b Δ f (7)
12 1 1 Index ACE2 = Δ P + b Δ f (8)
23 2 2 Science ACE3 = Δ P + b Δ f (9)
34 3 3 ACE4 = Δ P + b Δ f (10)
International 41 4 4 Where the constant b1, b2, b3 & b4 are called area frequency
bias of area 1, area 2, area 3 and area 4 respectively.
Now Δ PR , Δ PR , Δ PR and Δ PR are mode integral
1 2 3 4 of ACE1, ACE2, ACE3 and ACE4 respectively.
Control methodology used (FLC & ANN) is mentioned in
the next preceding sections.
III. CONTROL METHODOLOGY
A. Automatic Controller
The task of load frequency controller is to generate a
control signal Ui that maintains system frequency and tie-line
interchange power at predetermined values. The proportional
and integral (PI) control scheme is shown in Fig. 2 [30].
639 Vol:7 2013-05-26
Fig. 2 Conventional PI Controller Installed on ith Area
T
i
T
= − ∫ = − ∫ Δ + Δ (11)
U K ( ACE ) dt K ( P B f )
dt i i i tiei i i
0 0
Taking the derivative of equation (11) yields;
i i ( i ) i ( tie i i i ) U = −K ACE = −K ΔP + B Δf (12)
B. Fuzzy Logic Controller
Fuzzy logic is a thinking process or problem-solving
control methodology incorporated in control system
engineering, to control systems when inputs are either
imprecise or the mathematical models are not present at all.
Fuzzy logic can process a reasonable number of inputs but the
system complexity increases with the increase in the number
of inputs and outputs, therefore distributed processors would
probably be easier to implement. Fuzzification is process of
making a crisp quantity into the fuzzy (Ross, 1995). They
carry considerable uncertainty. If the form of uncertainty
happens to arise because of imprecision, ambiguity, or
vagueness, then the variable is probably fuzzy and can be
represented by a membership function.
Defuzzification is the conversion of a fuzzy quantity to a
crisp quantity, just as fuzzification is the conversion of a
precise quantity to a fuzzy quantity. There are many methods
of defuzzification, out of which smallest of maximum method
is applied in making fuzzy inference system. The Fuzzy logic
control consists of three main stages, namely the fuzzification
interface, the inference rules engine and the defuzzification
interface [15], [16]. For Load Frequency Control the process
operator is assumed to respond to variables error (e) and
change of error (ce). The fuzzy logic controller with error and
change in error is shown in Fig. 3.
4. World Academy of Science, Engineering and Technology
Fig. 3 Model of Fuzzy Logic Controller
The variable error is equal to the real power system
frequency deviation ( Δ f ). The frequency deviation Δ f , is
the difference between the nominal or scheduled power
system frequency (fN) and the real power system frequency (f).
Taking the scaling gains into account, the global function of
the FLC output signal can be written as.
Δ Pc = F [ n c e(k), n ce ce(k)]
(13)
where ne and nce are the error and the change in error scaling
gains, respectively, and F is a fuzzy nonlinear function. FLC
is dependant to its inputs scaling gains (Ha, 1998). A label set
corresponding to linguistic variables of the input control
signals, e(k) and ce(k), with a sampling time of 0.01 sec is
given Attempt has been made to examine with Seven number
of triangular membership function (MFs) namely Negative
Big(NB), Negative Medium(NM), Negative Small (NS),
Zero(ZO), Positive Small(PS), Positive Medium (PM) and
Positive Big(PB) are used. The range on input (error in
frequency deviation and change in frequency deviation) i.e
universe of discourse is -0.25 to 0.25 and -0.01 to 0.01 The
numbers of rules are 49.
TABLE I
FUZZY INFERENCE RULE FOR FUZZY LOGIC CONTROLLER
Input e(k)
ce(k)
NB NM NS ZO PS PM PB
NB PB PB PB PB PM PM PS
NM PB PM PM PM PS PS PS
NS PM PM PS PS PS PS ZO
ZO NS NS NS ZO PS PS PS
PS ZO NS NS NS NS NM NM
PM NS NS NM NM NM NB NB
PB NS NM NB NB NB NB NB
C. Artificial Neural Network (ANN) Controller
ANN is information processing system, in this system the
element called as neurons process the information. The signals
are transmitted by means of connecting links. The links
process an associated weight, which is multiplied along with
the incoming signal (net input) for any typical neural net. The
output signal is obtained by applying activations to the net
input. The field of neural networks covers a very broad area
[17], [18].
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Fig. 4 Neural Network as Function Approximator
Neural network architecture the multilayer perceptron as
unknown function are shown in Fig 5, which is to be
approximated. Parameters of the network are adjusted so that
it produces the same response as the unknown function, if the
same input is applied to both systems. The unknown function
could also represent the inverse of a system being controlled;
in this case the neural network can be used to implement the
controller [17].
D. NARMA-L2 Control
The ANN controller architecture employed here is a Non
linear Auto Regressive Model reference Adoptive Controller.
This controller requires the least computation of the three
architectures. This controller is simply a rearrangement of the
neural network plant model, which is trained offline, in batch
form. It consists of reference, plant out put and control signal.
The controller is adaptively trained to force the plant output to
track a reference model output. The model network is used to
predict the effect of controller changes on plant output, which
allows the updating of controller parameters. In the study, the
frequency deviations, tie-line power deviation and load
perturbation of the area are chosen as the neural network
controller inputs [17]. The outputs of the neural network are
the control signals, which are applied to the governors in the
area. The data required for the ANN controller training is
obtained from the designing the Reference Model Neural
Network and applying to the power system with step response
load disturbance. After a series of trial and error and
modifications, the ANN architecture provides the best
performance. It is a three-layer perceptron with five inputs, 13
neurons in the hidden layer, and one output in the ANN
controller. Also, in the ANN plant model, it is a three-layer
perceptron with four inputs, 10 neurons in the hidden layer,
and one output. The activation function of the networks
neurons is trainlm function.300 training sample has been
taken to train 300 no of epochs. The proposed network has
been trained by using the learning performance. Learning
algorithms causes the adjustment of the weights so that the
controlled system gives the desired response.
E. Hybrid Neuro Fuzzy (HNF) Controller
In recent years, Hybrid Neuro-Fuzzy (HNF) approach has
considerable attention for their useful applications in the fields
like control, pattern recognition, image processing, etc [20],
[26]. In all these applications there are different neuro-fuzzy
applications proposed for different purposes and fields. HNF
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5. World Academy of Science, Engineering and Technology
results are obtained from fusion of neural network and fuzzy
logic.
1. Neuro Fuzzy Modeling
The general algorithm for a fuzzy system designer can be
synthesized as Fuzzification, Fuzzy Inference and
Defuzzification [29]. From the beginning, a fuzzy-style
inference must be accepted and the most popular are
Mamdani-style inference and Sugeno-style Inference [14],
[19], [20].
Fig. 5 Architecture of a Two-Input Sugeno Fuzzy Model with Nine
Rules
The basic steps followed for designing the ANFIS
controller in MATLAB/Simulink is outlined:
1. Draw the Simulink model with fuzzy controller and
simulate it with the given rule base.
2. The first step for designing the ANFIS controller is
collecting the training data while simulating the model
with fuzzy controller.
3. The two inputs, i.e., ACE and d(ACE)/dt and the output
signal gives the training data.
4. Use anfisedit to create the ANFIS .fis file.
5. Load the training data collected in Step 2 and generate the
FIS with gbell MF’s.
6. Train the collected data with generated FIS up to a
particular no. of Epochs.
7. Save the FIS. This FIS file is the neuro-fuzzy enhanced
ANFIS file[29]
2. Training and Checking: ANFIS
The number of epoch is determined according to the above
parameters and to the excepted error measure fixed by the
user. The training and checking data are given below:
Number of nodes: 53, Number of linear parameters: 16,
Number of nonlinear parameters: 24, Total number of epoch:
80, Number of training data pairs: 51, Number of checking
data pairs: 51, Number of fuzzy rules: 16.
The range of error is as below:
1 0.000527979 0.00470353
2 0.000611368 0.00492588
The gbell MFs is taken. The frequency deviationΔf , is the
difference between the nominal or scheduled power system
frequency (fN) and the real power system frequency (f).
3. ANFIS (Adaptive Neuro-Fuzzy Inference System)
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This is more complex than Fuzzy inference System (FIS),
but users have some limitations: only zero-order or first-order
Sueno fuzzy models, AND Method: Prod, OR Method: max,
Imlication Method: prod, Aggregation Method: max,
Defuzzification Method: wtaver(weighted average). On the
other hand, users can provide to ANFIS their own number of
MFs(num MFs) both for input and outputs of the fuzzy
controller, the number of training and checking data sets
(numPts), the MF’s type (mfType), the optimization criterion
for reducing the error measure(usually defined by the number
of the squired difference between actual and linearized N
curve) [20], [26].
The great advantage of Neuro-fuzzy design method
comparing with fuzzy design method consists in the small
number of in put and output MFs (usually 2…4), which
implies the same maximum number of rules. Thus, the rule
base and the occupied memory became very small.
IV. SIMULATION AND RESULTS
In this presented work, different models of four area hydro-thermal
reheat interconnected power system have been
developed by using fuzzy logic, ANN and ANFIS and PI, PID
controllers to illustrate the performance of load frequency
control using MATLAB/SIMULINK package. The parameters
used for simulation are given in appendix [12]. Frequency
deviation plots for thermal and hydro cases are obtained
separately for 1% step load change in system frequency and
tie-line power as shown in Fig. 6-26 respectively.
Dynamic responses of four areas power system using PI
controller is are given below:
Time
Change in frequency
Fig. 6 Change in frequency (thermal plant) – with PI controller (Δf)
Time
Change in
Fig. 7 Change in frequency (Hydro plant)- with PI controller(Δf)
641 International Science Index Vol:7, No:5, 2013 waset.org/Publication/12180
6. Time (sec)
Fig. 8 Change in Tie-line power(thermal plant) with PI control
Fig. 9 Change in Tie-line power (hypothermal plant) with PI control
Fig. 10 Change in Tie-line power (thermal-hydro plant) with PI
control
The developed model with PI controller has been simulated
and responses obtained above in Fig. 6-10 reveals that PI
controller reduces the steady state error in frequency deviation
and also maximum peak over shoot. The settling time is
limited to 64 sec. in case of frequency deviation of thermal
plant and 70 sec. for hydro plant. The deviation in the tie-line
power is also limited to 70 sec.
The dynamic responses of four areas power system using
PID controller is are given below:
Time (sec)
Fig. 11 Change in frequency (thermal plant) – with PID controller
(Δf)
Time (sec)
Fig. 12 Change in frequency (hydro plant)- with PID controller (Δf)
Time (sec)
Fig. 13 Change in Tie-line power (thermal plant) with PID control (Δ
P tie)
Fig. 14 Change in Tie-line power (hydro plant) with PID control
(Δ P tie)
The developed model with PID controller has been
simulated and responses obtained above in Fig. 11-14 reveals
that PID controller reduces the steady state error in frequency
deviation and also maximum peak over shoot. The settling
time is limited to 60 sec. in case of frequency deviation of
Time (sec)
Change in Tie-line
Change in frequency
Time (sec)
Time (sec)
Change in Tie-line
Change in Tie-line
Change in frequency
Change in Tie-line Power Change in Tie-line
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7. thermal plant and 60 sec. for hydro plant. The deviation in the
tie-line power is also limited to 60 sec. The Number of
oscillations are also reduced. Dynamic responses of four areas
power system using Fuzzy controller is are given below:
Time (sec)
Fig. 15 Change in frequency (thermal plant) – with Fuzzy
controller
Fig. 16 Change in frequency (hydro plant) – with Fuzzy controller
Fig.17 Change in Tie-line power (thermal plant) with Fuzzy
Controller
Time (sec)
Fig.18 Change in Tie-line power (hydro plant) with Fuzzy Controller
The developed model with Fuzzy controller has been
simulated and responses obtained above in Fig. 15-18 reveal
that fuzzy controller further reduces the steady state error in
frequency deviation and also maximum peak over shoot. The
settling time is limited to 45 sec. in case of frequency
deviation of thermal plant and 48 sec. for hydro plant. The
deviation in the tie-line power is also limited to 45 sec. The
settling time and peak over shoot is much lesser than the PI
and PID controller. Dynamic responses of four areas power
system using ANN controller is are given below:
Time (sec)
Fig. 19 Change in frequency (Thermal plant) with ANN controller
Time
Change in frequency
Fig. 20 Change in frequency (hydro plant) with ANN controller
Time (sec)
Time (sec)
Change in frequency
Change in Tie-line
Change in Tie-line
Change in frequency
Change in frequency
World Academy of Science, Engineering and Technology
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8. Fig. 21 Change in Tie-line power (hydro thermal plant) with ANN
Fig. 22 Change in Tie-line power (thermal hydro plant) with ANN
The developed model with Artificial Neural Network
(ANN) controller has been simulated and responses obtained
above in figure 19-22 reveal that ANN controller further
reduces the steady state error in frequency deviation and also
maximum peak over shoot. The settling time is limited to 40
sec. in case of frequency deviation of thermal plant and hydro
plant as well. The deviation in the tie-line power is also
limited to 30 sec. The settling time and peak over shoot is
much lesser than the PI, PID and Fuzzy controllers.
Dynamic responses of four areas power system using
ANFIS controller is are given below:
Fig. 23 Change in frequency (Thermal plant) with ANFIS controller
Time (sec)
Fig. 24 Change in frequency (Hydro plant) with ANFIS controller
Fig.25 Change in Tie-line power (thermal hydro plant) with
ANFIS
Fig. 26 Change in Tie-line power (thermal hydro plant) with
ANFIS
The developed model with ANFIS controller has been
simulated and responses obtained above in Fig. 23-26 reveal
that ANFIS controller further reduces the steady state error in
frequency deviation and also maximum peak over shoot. The
settling time is limited to 18 sec. in case of frequency
deviation of thermal plant and 17 sec. for hydro plant. The
deviation in the tie-line power is also limited to 15 sec. for
thermal and 27 sec. for hydro plant. The settling time and
peak over shoot is much lesser than the PI, PID, Fuzzy and
ANN controllers.
The above simulation results shows that the proposed
ANFIS based controllers tracks the load changes and achieve
good robust performance than conventional PI, PID and other
intelligent control(Fuzzy & ANN) approach with 1% load
variation in power system. Conventional PI, PID and
Intelligent (Fuzzy and Neuro-Fuzzy) control approach with
inclusion of slider gain provides better dynamic performance
and reduces the steady state error and oscillation of the
frequency deviation and the tie line power flow in each area in
Change in Tie-line Power
Time
Time (sec)
Change in Tie-line Change in
Time (sec)
Time (sec)
Change in Tie-line Power
Change in Tie-line
Time (sec)
Change in
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9. World Academy of Science, Engineering and Technology
hydro-thermal combination of four area interconnected power
system. Settling time and maximum peak overshoot in
transient condition for both change in system frequency and
change in tie-line power are given in table II & III,
respectively.
TABLE II
COMPARATIVE STUDY OF SETTLING TIME
Control
lers
Area
1
(sec)
Area
2
(sec)
Area
3
(sec)
Area
4
(sec)
Therma
l-thermal
(sec)
Hydro-thermal
(sec)
PI 64 64 70 65 65 70
PID 60 60 60 50 62 60
Fuzzy 45 45 45 48 40 45
ANN 40 40 40 40 30 35
ANFIS 18 18 17 17 15 27
TABLE III
COMPARATIVE STUDY OF PEAK OVERSHOOTS
Control
lers
Δf
Area 1
(pu)
Δf
Area 2
(pu)
Δf
Area 3
(pu)
Δf
Area 4
(pu)
ΔP tie
Thermal-thermal
(pu)
ΔP tie
Hydro-thermal
(pu)
PI -0.055 -0.055 -0.067 0.066 -0.0145 -0.05
PID -0.049 -0.049 -0.057 -0.062 0.005 -0.0042
Fuzzy -0.059 -0.06 -0.068 -0.065 0.005 -0.012
ANN -0.038 -0.038 -0.055 -0.051 -0.006 -0.013
ANFIS -0.061 -0.061 -0.054 -0.054 -0.052 -0.045
By varying 1% step load, the above responses reveals that
the steady state error in dynamic change in frequency and tie-line
power are reduced to zero and settling time and peak
overshoot is plotted and tabulated in Table II and Table III.
ANFIS controller has minimum settling time and peak
overshoot in frequency response than other four proposed
controller.
V. CONCLUSIONS
In this paper, automatic generation control of four area
interconnected hydro thermal power system is investigated. In
order to demonstrate the effectiveness of proposed method,
the control strategy based on Neuro-fuzzy, ANN and
conventional PI & PID technique is applied. The performance
of proposed controller is evaluated through the simulation.
The results are tabulated in Table II and III respectively.
Analysis reveals that the proposed technique gives good
results and uses of this method reduce the peak deviation of
frequencies, tie-line power, time error and inadvertent
interchange. It can be concluded that ANFIS controller with
sliding gain provides better settling performance than Fuzzy,
ANN and conventional PI &PID one. Therefore, the
intelligent control approach using Neuro-Fuzzy concept is
more accurate and faster than the fuzzy, ANN, PI and PID
control scheme even for complex dynamical system.
APPENDIX
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Parameters are as follows:
f = 50 Hz, R1 =R2= R3= R4 =2.4 Hz/ per unit MW, Tgi= 0.08
sec, Tpi=20 sec; P tie, max = 200 MW ; Tr = 10 sec ; Kr = 0.5, H1
=H2 =H3= H4 =5 sec ; Pri=2000MW, Tti = 0.3sec ;
Kp1=Kp2=Kp3 = Kp4 = 120 Hz.p.u/MW ;Kd =4.0;
Ki = 5.0 ; Tw = 1.0 sec; Di =8.33 * 10-3 p.u MW/Hz.;
B1=B2=B3=B4=0.425 p.u. MW/hz; ai=0.545;
a=2*pi*T12=2*pi*T23=2*pi*T34=2*pi*T41=0.545,
delPdi= 0.01
Nomenclature
i: Subscript referring to area (i=1,2,3,4)
f : Nominal system frequency
Hi: Inertia constant; Δ P Di : Incremental load change
ΔPgi : Incremental generation change
= P Di
fi
Di
Δ
Δ
; Tr : Reheat time constant
Tg: Steam governor time constant; Kr : Reheat constant,
Tt : Steam turbine time constant; Bi: Frequency bias
constant
Ri : Governor speed regulation parameter
Tpi : 2Hi / f * Di, Kpi: 1/ Di
Kt: Feedback gain of FLC
Tw : Water starting time, ACE : Area control error
P: Power, E : Generated voltage
V: Terminal voltage, δ Angle of the Voltage V
Δδ : Change in angle, ΔP: Change in power
Δf : Change in supply frequency;
ΔPc: Speed changer position
R: Speed regulation of the governor
KH : Gain of speed governor
TH : Time constant of speed governor
Kp : 1/B= Power system gain
Tp: 2H / B f0 = Power system time constant
ACKNOWLEDGMENT
This work is supported by the Department of Electrical
Engineering, Sam Higginbottom Institute of Agriculture,
Technology and Sciences-Deemed University, Allahabad-
India.
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Surya Prakash belongs to Allahabad-India, Received
his Bachelor of Engineering degree from The I E
(India) in 2003, He obtained his M.Tech. in Electrical
Engg.(Power System) from KNIT, Sultanpur-India in
2009. Presently he is Pursuing Ph. D in Electrical
Engg.(Power System)from, SHIATS-DU(Formerly
AAI-DU, Allahabad- India). His field of interest
includes power system operation & control, Artificial
Intelligent Control.
Dr. S. K. Sinha belongs to Varanasi and his date of
birth is 17th Apr 1962. He received the B.Sc. Engg
degree in Electrical from R.I.T. Jamshedpur, Jharkhand,
India, in 1984, the M. Tech. degree in Electrical
Engineering from Institute of Technology, B.H.U,
Varanasi, India in 1987, and the Ph.D. degree from IIT,
Roorkee, India, in 1997. Currently he is working as
Professor in the Department of Electrical Engineering,
Kamla Nehru Institute of Technology, Sultanpur, India.
His fields of interest includes estimation, fuzzy control,
robotics, and AI applications’-
646 International Science Index Vol:7, No:5, 2013 waset.org/Publication/12180