Top PDF Comparison of Transient Stability Response for MMPS using UPFC with PI and Fuzzy Logic Controller

Comparison of Transient Stability Response for MMPS using UPFC with PI and Fuzzy Logic Controller

Comparison of Transient Stability Response for MMPS using UPFC with PI and Fuzzy Logic Controller

The increasing pressure on the power system increases the complexity that is becoming a concern for the stability of the power system and mainly for transitory stability. To operate the system in the event of faults, Flexible AC Transmission System (FACTS) devices are used that provide opportunities to control power and vibrations damping. This paper deals with the two control strategies of the Unified Power Flow Controller (UPFC) to damping the system oscillations stability. The stability of the Multi-Machine Power System (MMPS) was analysed with the presence of UPFC. The first strategy is the traditional PI controller (PI-C) with UPFC, and the second strategy is the proposed Fuzzy Logic controller (FL-C) proposed for UPFC device along with PI controller. The MATLAB R2014a was used in all simulations. Based on the results, FL-C for UPFC device along with the PI controller has proven its superiority by has enhanced response to the system, thus minimized in the transitions overshoot and undershoot, and has lower ripple compared to traditional PI-C, both with and without UPFC.
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Performance Comparison of PI and Fuzzy-PI Logic Speed Control of Induction Motor

Performance Comparison of PI and Fuzzy-PI Logic Speed Control of Induction Motor

A proportional–integral–derivative controller (PI controller) is a generic control loop feedback mechanism widely used in industrial control systems – a PI is the most commonly used feedback controller. A PI controller calculates an "error" value as the difference between a measured process variable and a desired set point. The controller attempts to minimize the error by adjusting the process control inputs. In the absence of knowledge of the underlying process, PI controllers are the best controllers. However, for best performance, the PI parameters used in the calculation must be tuned according to the nature of the system – while the design is generic, the parameters depend on the specific system. The PI controller calculation involves three separate parameters, and is accordingly sometimes called three-term control: the proportional, the integral and derivative values, denoted P, I, and D. The proportional value determines the reaction to the current error, the integral value determines the reaction based on the sum of recent errors, and the derivative value determines the reaction based on the rate at which the error has been changing. The weighted sum of these three actions is used to adjust the process via a control element such as the position of a control valve or the power supply of a heating element. Heuristically, these values can be interpreted in terms of time: P depends on the present error, I on the accumulation of past errors, and D is a prediction of future errors, based on current rate of change. By tuning the three constants in the PI controller algorithm, the controller can provide control action designed for specific process requirements. The response of the controller can be described in terms of the responsiveness of the controller to an error, the degree to which the controller overshoots the setpoint and the degree of system oscillation. Note that the use of the PID algorithm for control does not guarantee optimal control of the system or system stability. The PID controller is probably the most-used feedback control design. PID is an acronym for Proportional-Integral-Derivative, referring to the three terms operating on the error signal to produce a control signal. If u(t) is the control signal sent to the system, y(t) is the measured output and r(t) is the desired output, and tracking error e(t) = r(t) − y(t), a PID controller has the general form.
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Power System Transient Stability Analysis Based On Interval Type-2 Fuzzy Logic Controller And Genetic Algorithms

Power System Transient Stability Analysis Based On Interval Type-2 Fuzzy Logic Controller And Genetic Algorithms

identified some of the limitation of each of them, such as the steady state error presented by ordinary fuzzy controller. The application of IT2FLC controller is the main focus of this paper. The simulation results for disturbed terminal voltage values and transmission lines faults shows a very sharp reduction in settling time, over shoot, rise time and zero steady state error. It could be observed in study using MATLAB simulation, an excellent response of the IT2FLC controller and with no oscillation, while the AVR response presented a ripple in both studies and some oscillations before reaching the steady state operation point. It is shown that an excellent performance of the IT2FLC control over the conventional AVR one for the excitation control of synchronous machines could be achieved. It has been shown that the genetically evolved interval type-2 FLCs can lead to superior performance in comparison to interval type-1 FLCs and the manually designed interval type-2 FLCs. The results indicate that the genetic evolution of interval type-2 MFs can provide valid and high-performance interval type-2 FLCs without relying on any a priori knowledge such as logged data or a previously existing model, making it suitable for control problems where no such a priori data is available such as in transient stability control in power system. This work will be a step towards overcoming the problem of manually specifying pseudo-optimal MFs for interval type- 2 FLCs, which to date is one of the main obstacles when designing interval type-2 FLCs.
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Governor Controllers of Heavy Duty Gas Turbine Performance Comparison using PI Controller and Fuzzy Logic Controller

Governor Controllers of Heavy Duty Gas Turbine Performance Comparison using PI Controller and Fuzzy Logic Controller

Abstract – In gas turbine system, Governor controller plays an important role in the dynamic behavior of turbine system for automatically regulating the supply of fuel with respect to load and although to limiting the speed. Need of gas turbines and its applications nowadays more prominently increasing due to technology improvement towards their countries development is the main cause for it. So the controller system used in gas turbine system in various applications effective response must be required, for that concern governor system could be model with PI- controller. In which additionally another two methods are used such as Feed-forward and Back-tracing methods to improving the dynamic behavior and response time and also its load rejection response. In order to get better response to improving the stability and load rejection the Fuzzy Logic controller used in the place of PI-controller. So entirely in this paper the comparative response behavior of Heavy-Duty gas turbine system would be observe between PI-controller and Fuzzy Logic controller of governor system model design in MATALAB-SIMULINK platform.
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Transient Stability of A.C Generator Controlled By Using Fuzzy  Logic Controller

Transient Stability of A.C Generator Controlled By Using Fuzzy Logic Controller

Simulated model of the synchronous generator is connected to an AC system with all parameters from experimental setup. The behavior of the fuzzy logic excitation controller is simulated and compared with PI voltage controller for two characteristic operation conditions. In the first simulation voltage reference is changing from 100% to 80% and then back to 100% with 80% of active power. On the fig. 5. Is presented active power response with fuzzy logic stabilizing controller and with classical PI regulator. A modern excitation system contains components like automatic voltage regulators (AVR), Power System stabilizers (PSS), and filters, which help in stabilizing the system and maintaining almost constant terminal voltage. These components can be analog or digital depending on the complexity, viability, and operating conditions. The final aim of the excitation system is to reduce swings due to transient rotor angle instability and to maintain a constant voltage. To do this, it is fed a reference voltage which it has to follow, which is normally a step voltage. The excitation voltage comes from the transmission line itself. The AC voltage is first converted into DC voltage by rectifier units and is fed to the excitation system via its components like the AVR, PSS etc.
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Power System Transient Stability Analysis Based on Evolutionary Interval Type-2 Fuzzy Logic Controller and GA System

Power System Transient Stability Analysis Based on Evolutionary Interval Type-2 Fuzzy Logic Controller and GA System

This paper reviewed the various techniques employed in synchronous generator terminal voltage control. Such techniques are the CAVR, MV, GMV, PP and ordinary fuzzy controller. It identified some of the limitations of each of them, such as the steady state error presented by ordinary fuzzy controller. The application of EIT2FLC controller is the main focus of this paper. The simulation results for disturbed terminal voltage values and transmission lines faults shows a very sharp reduction in settling time, over shoot, rise time and zero steady state error. It could be observed in study using MATLAB simulation, an excellent response of the EIT2FLC controller and with no oscillation, while the AVR response presented a ripple in both studies and some oscillations before reaching the steady state operation point. It is shown that an excellent performance of the EIT2FLC control over the conventional AVR one for the excitation control of synchronous machines could be achieved. It has been shown that the genetically evolved interval type-2 FLCs can lead to superior performance in comparison to interval type-1 FLCs and the manually designed interval type- 2 FLCs. The results indicate that the genetic evolution of interval type-2 MFs can provide valid and high-performance interval type-2 FLCs without relying on any a priori knowledge such as logged data or a previously existing model, making it suitable for control problems where no such a priori data is available such as in transient stability control in power system. This work will be a step towards overcoming the problem of manually specifying pseudo-optimal MFs for interval type-2 FLCs, which to date is one of the main obstacles when designing interval type-2 FLCs.
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Performance Analysis of Speed Control of Induction Motor using Pi, SMC & Fuzzy Logic Controller

Performance Analysis of Speed Control of Induction Motor using Pi, SMC & Fuzzy Logic Controller

Sensor less control of induction motor using vector control technique has been proposed. Sensor less control gives the benefits of vector control without using any shaft encoder. The mathematical model of the drive system has been developed. Vector controlled induction motor by employing the different speed controllers like PI, sliding mode controller and fuzzy logic controllers is presented. The performance of the sliding mode controller and fuzzy logic controller for the indirect vector controlled induction motor drive has been verified and compared with that of conventional PI controller performance. It can be concluded that the fuzzy logic controllers performance is better in comparison with that of PI and SMC in terms of the transient response. The dynamic performance of SMC is found to be the best out of the three controllers. The robustness of the SMC and Fuzzy logic controller during sudden changes in load has been seen but SMC gives better performance than fuzzy logic controller with load conditions. PI controller is very simple to implement, but its steady state response and dynamic performance are not very satisfactory. Its robustness to load disturbances is also relatively poor.
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Enhancement Transient Stability using UPFC with ANN Controller

Enhancement Transient Stability using UPFC with ANN Controller

Power transmission networks have become narrower due to the increased demand for power. A result of many stability problems such as overloading some transmission lines after a disturbance. Therefore, the problem of transitory stability after the main defect is a special transmission-limiting factor [1]. Transient stability refers to the capacity of the power system to preserve synchronization when exposed to severe transient disturbances such as sudden change of load and faults [2]. Include system response resulting from large fluctuations in generator speed and rotor angle. Transient stability of the complex power system can be improved using FACTs devices [3]. The FACTs controllers are able to control network condition very quick. This allows the existing network to obtain used efficiently and thus avoid the need for constructing newlines [4]. The optimal tuning and modelling of various FACTs devices for a dynamic stability enhancement of MMPS studied in [5]. UPFC is the most widely deployed device in FACTs that can provide effective control of power system parameters such by way of transmission voltage, line impendence, and phase angle. Moreover, UPFC can provide either positive or negative power injections positive or interactive. Therefore, it can enhance the operation of the system because it allows for extra efficient control of power flow, super-control system, and stability [6]. The PI controller becomes been used in recent years to improve both temporary and fixed performance, as well as to reject disturbances caused by startup events [7], [8], [9].
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PI Controller and Fuzzy Logic Controller based Loss Minimization Techniques for Induction Motor Drives

PI Controller and Fuzzy Logic Controller based Loss Minimization Techniques for Induction Motor Drives

the hysteresis band current controller for pulse width modulation. This transformation results in reduction of output voltage obtained from the three phase voltage source inverter and applied to the stator input terminals of induction motor drive, thus the decomposition into d-q components in the steady-state motor model can be utilized in deriving the reduced motor losses. The drive system is simulated using Matlab/Simulink models and simulation results based on total losses and efficiency are compared with changing load torque.
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Response Based Comparative Analysis of Two Inverter Fed Six Phase PMSM Drive by Using PI and Fuzzy Logic Controller

Response Based Comparative Analysis of Two Inverter Fed Six Phase PMSM Drive by Using PI and Fuzzy Logic Controller

This Paper gives a complete modeling and simulation of a two inverter fed six phase permanent magnet synchronous motor drive system, Then response based comparative analysis is done on starting torque ,settling time, Steady state current at various speed levels and torque levels by changing proportional-integral (PI) controller to Fuzzy logic controller. The PI controller has some disadvantages like, more settling time, sluggish response due to sudden change in load torque etc. So an intelligent controller, based on fuzzy logic is introduced which replaces the PI-controller and its drawbacks. The performance of both the controller has been investigated and studied by comparing the different plots obtained by setting various speed level both incremented and decremented speed, at different load conditions like No- load, fix load and dynamic load through Matlab / Simulink environment. Finally it is concluded from the result that fuzzy logic based controller is robust, reliable gives quick response with high starting torque and more effective than the conventional PI controller. It is also observed that both the proposed model can also run above rated speed significantally.
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Interconnected System for Grid Stability with PI and Fuzzy-PID Controller

Interconnected System for Grid Stability with PI and Fuzzy-PID Controller

Frequency Control is a technical requisite for the appropriate setup of an interconnected power system and it is the precondition for a stable electricity grid and guarantees secure supply at a frequency of 50Hz. An interconnected power system comprises of interconnected control areas. When load changes or abnormal conditions arises like outages of generation and varying system parameters, mismatches in frequency can be began. These incompatibilities can be improved by controlling the frequency. Automatic Generation Control is used to retain the schedule system frequency (1)(2-4)..Next importance is given to the usage of High Voltage DC transmission (HVDC)(1) link in the system instead of high Voltage Alternating Current (HVAC) transmission only. HVDC is a forecast technology due to huge growth of this transmission system and due to its economic, environmental and performance advantages over the other options. Therefore it is planned to have a dc link in parallel with HVAC link interconnecting control areas to get an enhanced system dynamic performance. Those studies are conceded out considering the nominal system parameters. Practically system parameters vary considerably with changing operating conditions. Intelligent controllers can be hired to elucidate this problem. The conventional control technique does not provide control problems including AGC of interconnected power system. Fuzzy logic based controller can be implemented to scrutinize the load frequency control of three area interconnected power system with HVAC and HVDC parallel link taking parameter uncertainties into account. In the system working under deregulated environment, a Wind Turbine Generator(WTG) or other locally generating plants can be replicated using in the to carry out all the planned operations and to control the frequency of the system using AGC and fuzzy Controller with PID(7-9)
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Transient Stability Analysis of Power System With UPFC Using PSAT

Transient Stability Analysis of Power System With UPFC Using PSAT

One FACTS controller in particular, the Unified Power Flow Controller (UPFC), is capable of concurrently or selectively controlling transmission line power flows, voltage magnitudes and phase angles in a power system. Here in fig.1 given below UPFC is shown with both PWM and Phase Control strategy.

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Enhancement of Transient Stability Using UPFC for 11 Bus Systems

Enhancement of Transient Stability Using UPFC for 11 Bus Systems

Abstract—FACTS devices are available, which can help Power Engineers to deal with problems like Large Signal Stability and economic Factors that gives strong incentives to raise the Stability limit of the System, depending upon the diverse conditions. Among the converter based FACTS devices Static Synchronous Compensator (STATCOM) and Unified Power Flow Controller (UPFC) are the popular FACTS devices. Unified Power Flow Controller (UPFC) is a power electronic based device that has capability of controlling the power flow through the line by controlling appropriate its series and shunt parameter. UPFC is a versatile FACTS controller that can regulate the Power Flow through the Line by controlling its Series and shunt parameters. In shunt it is having STATCOM and in series SSSC are employed can independently control the Line Power Flow. Two Converters improves the flexibility and provide additional degree of freedom in Power System. With the application of UPFC, Transient stability of the system can be improved. This Paper shows that how Transient Stability of the Inter Area system is Improved. In this paper, we analyze the transient stability of simple two area system of 11 bus test system of two area system with and without UPFC by comparing the rotor angles, voltage at buses, and angular frequency plots using the Time Domain feature in PSAT software.
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Improved Step Response of Power System Stabilizer using Fuzzy Logic Controller

Improved Step Response of Power System Stabilizer using Fuzzy Logic Controller

As every power system is constantly being subjected to disturbances, we should see that these disturbances do not make the system unstable. Therefor additional signals derived from speed deviation, excitation deviation and accelerating power are injected into voltage regulators. The device to provide these signals is referred as power system stabilizer. The use of power system stabilizers has become very common in operation of large electric power systems. The conventional PSS which uses lead-lag compensation, where gain settings designed for specific operating conditions, is giving poor performance under different loading conditions. Therefore, it is very difficult to design a stabilizer that could present good performance in all operating points of electric power systems. In an attempt to cover a wide range of operating conditions, Fuzzy logic control has been suggested as a possible solution to overcome this problem. In this paper, a systematic approach to fuzzy logic control design is proposed. The study of fuzzy logic power system stabilizer for stability enhancement of a single machine infinite bus system is presented. In order to accomplish the stability enhancement, speed deviation and acceleration of the rotor synchronous generator are taken as the inputs to the fuzzy logic controller. These variables take significant effects on damping the generator shaft mechanical oscillations. The stabilizing signals were computed using the fuzzy membership function depending on these variables. The performance of the system with fuzzy logic based power system stabilizer is compared with the system having conventional power system stabilizer and system without power system stabilizer
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ENHANCEMENT OF VOLTAGE STABILITY USING BY UPFC (UNIFIED POWER FLOW CONTROLLER)

ENHANCEMENT OF VOLTAGE STABILITY USING BY UPFC (UNIFIED POWER FLOW CONTROLLER)

Abstract—Owing to increase in power demand, many instability problems are experienced by power system in every year. Voltage stability is one of the main problems in power systems that must be treated using suitable mitigation techniques. Under heavy load conditions due to insufficient reactive power causes the voltage drop and under lightly loaded condition due to surplus amount of reactive power causes voltage rise, finally it leads to voltage instability. The enhancement of voltage stability in transmission line is done by Unified Power Flow Controller. In this project voltage stability improvement using UPFC is analyzed. Voltage stability improvement is shown and analyzed using MATLAB/ S imulink.
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Classy Controller Using Fuzzy Logic - Controller for Concert Enhancement

Classy Controller Using Fuzzy Logic - Controller for Concert Enhancement

Besides the advantages, there are some limitations of Fuzzy Logic Controllers. The tuning of an FLC is a very difficult task. To make the tuning easy and efficient, there are several structures of fuzzy logic controllers are available. This paper considers new structures of fuzzy logic controllers. Two structures, self-tuning FLC and fuzzy supervised conventional controller are considered. In Fuzzy Logic control rules and scaling factors play very important role. In this paper, a self-tuning PI-like FLC is used for the tuning of output scaling factor. In FSPI, we tune the PI controller parameters with FLC. So, it adds the advantages of PID controller and FLC. The design of these controllers is discussed. These are implemented to control three non-linear example systems. The concert of FLC, STFLC and FSPI controller is compared with each other. It is found that STFLC and FSPI controller give better concert than the conventional PI controller or simple FLC.
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Comparative Study of Frequency Control Method of MGP System using Convectional PI and Fuzzy Logic Controller

Comparative Study of Frequency Control Method of MGP System using Convectional PI and Fuzzy Logic Controller

Abstract: The paper here states, the comparative study of frequency control of MGP system with convectional PI and fuzzy logic controller is done. The electrical power generation has done by non renewable energy sources in most parts of the world. The carbon emissions during the production of electricity challenge the environmental issues which lead to pollution. So, there is a necessity for the interconnection of renewable energy sources with grid for the reduction in usage of non renewable energy sources. But, interfacing of renewable sources to the grid is not an easy task. The reduction of inertia in the power system, the frequency instability problems may limit the usage of renewable sources in the interfacing with the grid. The motor generator pair can deal with all the above problems very effectively. The source grid characteristics are analyzed by simulation using convectional PI controller and fuzzy logic controller. The fuzzy logic PI controller gives better results when compared with convectional PI controller. The results were compared by simulation whether the fuzzy PI controller gives best results or convectional PI controller.
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REDUCTION OF HARMONIC DISTORTION FOR THREE PHASE NON LINEAR LOAD USING PI WITH FUZZY LOGIC CONTROLLER

REDUCTION OF HARMONIC DISTORTION FOR THREE PHASE NON LINEAR LOAD USING PI WITH FUZZY LOGIC CONTROLLER

This project presents a non isolated, high boost ratio hybrid dc–dc converter with applications for low-voltage renewable energy sources The system is designed considering solar-PV panels of 750W to feed an average load demand of 250W for a rural household. The system includes series-parallel combination of solar panels, MPPT (maximum power point tracking) controller, a dc-dc SEPIC converter, an energy storage system .A dc-dc converter is providing a constant dc bus voltage and its duty cycle is controlled by the MPPT controller. A P&O approach is utilized for MPPT. In this approach, MPPT controller automatically generates a PWM signal for the dc-dc converter to extract maximum power. To maintain the power quality a feedback control is used. The complete system is designed, and modeled to evaluate its performance. Simulated results are presented to demonstrate the performance of the MPPT controller and designed system for varying atmosphere conditions and load disturbances.
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Induction motor controller using fuzzy logic

Induction motor controller using fuzzy logic

Fuzzy logic approach allows the designer to handle efficiently very complex closed-loop control problems, reducing in many cases, engineering time and cost. It has the ability to distribute gain over a range of inputs in order to avoid the saturation of the control capability. Fuzzy logic shoved very useful to solved nonlinear control problems. It’s also allows a simpler and more robust control solution whose performance can only be matched by a classical controller with adaptive characteristics. The advantages provided by a FLC is it operates in a knowledge – based way and its knowledge relies on a set of linguistic such as if-then rules like a human logic.
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Dc motor speed control and performance analysis between pid  controller, pi controller and fuzzy logic controller

Dc motor speed control and performance analysis between pid controller, pi controller and fuzzy logic controller

The area of DC motor speed control and analysis in very wide, but Proportional-Integral-Derivative (PID) controllers have gained wide popularity in the control of DC motors. Their performances, though require some degree of manual tuning by the operator, are still satisfactory but a means of auto-tuning is desirable. In this paper, the performance of a select dc motor controlled by a proportional-integral-derivative (PID) controller and by a proportional integral (PI) controller is investigated. An overshoot is observed with an accompanied large settling time thereby confirming the behavior of a typical PID controller and PI controller. It is therefore a matter of necessity to tune the PID controller and PI controller in order to obtain the desired performance. On the other hand, a fuzzy logic based controller applied to the dc motor is investigated. With the application of appropriate expert rules, there is no overshoot and the settling time is within the desired value. With fuzzy logic controller, manual tuning is eliminated and intelligent tuning takes the Centre stage with satisfactory performance. Therefore in this paper we are comparing the performance of a select DC motor with the application of PID and PI controller and an auto fuzzy logic controller and observing the best result.
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