Fuzzy Load Frequency Controller Research Articles

Stability and Stabilization for T–S Fuzzy Load Frequency Control Power System With Energy Storage System

Stability and Stabilization for T–S Fuzzy Load Frequency Control Power System With Energy Storage System

Optimal self-tuning fractional order fuzzy load frequency control considering sustainable energy sources and electric vehicle

Considering uncertainties associated with sustainable energy sources in modern power systems, one of the main obstacles for load frequency control (LFC) is that various publications regard the parameters of FOPID controllers as fixed after optimisation. To tackle this challenge, an adaptive control structure may be a viable option for LFC. In this paper, in a two-zone hybrid power system that includes a thermal power plant, green energy sources, fuel cells, and plug-in electric vehicles, an optimal self-tuning fractional order fuzzy (OSTFOF) controller for LFC is proposed. Pathfinder algorithm (PFA) has been utilised for optimal tuning of parameters of the OSTFOF controller, including the upper bands of output membership functions, the input scaling factors, and the order of integral and derivative operators. In the proposed controller, the values of proportional, integral, and derivative gains are adaptively obtained. In the thermal power plant, non-linear factors, such as governor dead band (GDB) and generation rate constraint (GRC), are considered. Four different scenarios have been considered to evaluate the performance of the proposed OSTFOF controller, and results have been compared with PI, PID, and FOPID controllers. The simulations’ results indicate the excellent performance indices of the suggested OSTFOF controller compared to other controllers.

Sampled Memory-Event-Triggered Fuzzy Load Frequency Control for Wind Power Systems Subject to Outliers and Transmission Delays.

This study is devoted to event-triggered fuzzy load frequency control (LFC) for wind power systems (WPSs) with measurement outliers and transmission delays. Due to the integration of wind turbine (WT) with nonlinearity, the T-S fuzzy model of WPS is established for stability analysis and controller design. To mitigate the network burden, a new sampled memory-event-triggered mechanism (SMETM) related to historical system information is presented. It has the following two merits: 1) the utilization of continuous memory outputs over a given interval is useful to reduce the information loss in the period of samples and the redundant triggering events induced by disturbances and noises and 2) an extra upper constraint is added in the triggering condition to generate a new event only when the error signal belongs to a bounded range, thus, the false events caused by measurement outliers can be differentiated out and then be dropped. By representing the memory signal with transmission delay as a time-varying distributed delay term, a T-S fuzzy time-varying distributed delay system is built up to model the H∞ LFC WPS. With the help of the Lyapunov method and the integral inequality relying on distributed delay, some criteria are derived to solve the triggering matrix and fuzzy controllers. Finally, the merits of the proposed SMETM are tested by simulation results.

Event-Based Distributed Fuzzy Load Frequency Control for Multiarea Nonlinear Power Systems With Switching Topology

This article investigates the event-based distributed fuzzy load frequency control approach for nonlinear interconnected power systems under a switching topology. Specifically, nonlinear factors and uncertain parameters existing in turbine and governor dynamics are modeled and analyzed under the interval type-2 fuzzy method. New memory-based adaptive event-triggered mechanisms, whose directions and threshold parameters are dynamically updated based on the output change trend and relative output error of multiple memories, are proposed to further save network energy. Aiming at communication topology changes in multiarea power systems, a novel switched control system is established by introducing a time-varying communication matrix. Then, the system’s asymptotic stability is ensured by the piecewise Lyapunov–Krasovskii method. Furthermore, to further relax stability conditions, slack matrices are considered with the boundary information of membership functions. Finally, three-area power systems are shown to demonstrate the effectiveness of proposed distributed load frequency control strategies.

Resilient Distributed Fuzzy Load Frequency Regulation for Power Systems Under Cross-Layer Random Denial-of-Service Attacks.

In this article, a novel distributed fuzzy load frequency control (LFC) approach is investigated for multiarea power systems under cross-layer attacks. The nonlinear factors existing in turbine dynamics and governor dynamics as well as the uncertain parameters therein are modeled and analyzed under the interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy framework. The cross-layer attacks threatening the stability of power systems are considered and modeled as an independent Bernoulli process, including denial-of-service (DoS) attacks in the cyber layer and phasor measurement unit (PMU) attacks in the physical layer. By using the Lyapunov theory, an area-dependent Lyapunov function is proposed and the sufficient conditions guaranteeing the system's asymptotically stability with the area control error (ACE) signals satisfying H∞ performance are deduced. In simulations, we adopt a four-area power system to verify the resiliency enhancement of the presented distributed fuzzy control strategy against random cross-layer DoS attacks. Results show that the designed resilient controller can effectively regulate the load frequency under different cross-layer DoS attack probabilities.

Gain Schedule PI Fuzzy Load Frequency Control for Two-Area Electric Power System

The use of proportional integral (PI) load frequency control (LFC) to ensure the stable and reliable operation of electric power system is practical important. Any imbalance between synchronous generators and consumption loads will cause frequency unstable within the complete power system. The purpose of the load frequency control (LFC) is to keep the power system frequency and the inter-area tie power as near equilibrium point. This article introduces a gain schedule PI fuzzy load frequency control (GLFC) applying to two area electric power system. The GLFC consists of two level control systems, where the PI controller in the conventional form and its parameters are tuned in real time by fuzzy system. A fuzzy rule base is constructed in the form set of IF-THEN that describe how to choose the PI parameters under different operating conditions. The simulation has been conducted in MATLAB Simulink package. The effectiveness of the GLFC is measured by comparison with conventional PI load frequency controller.

Fuzzy Load Frequency Controller in Deregulated Power Environment by Principal Component Analysis

Deregulated Load Frequency Control (DLFC) plays an important role in power systems. The main aim of DLFC is to minimize the deviation in area frequency and tie-line power changes. Conventional PID controller gains are optimally tuned at one operating condition. The main problem of this controller is that it fails to operate under different dynamic operating conditions. To overcome that drawback, fuzzy controllers have very much importance. The design of Fuzzy controller’s mostly depends on the Membership Functions (MF) and rule-base over the input and output ranges controllers. Many methods were proposed to generate and minimize the fuzzy rules-base. The present paper proposes an optimal fuzzy rule base based on Principal component analysis and the designed controller is tested on three area deregulated interconnected thermal power system. The efficacies of the proposed controller are compared with the Fuzzy C-Means controller and Conventional PID controller.

Fuzzy C-means load frequency controller in deregulated power environment

The load frequency control (LFC) problem has been a major subject in the power system design/operation. The evolution of many socialised companies for power generation affects the formulation of LFC problem. In the present paper, a fuzzy load frequency controller with minimum rule-base is proposed. The optimal rule base for the proposed controller is obtained from fuzzy C-means clustering technique. The efficacy of the proposed fuzzy C-means load frequency controller is verified and compared with existing techniques in the literature for a three area interconnected power system in deregulated environment for various operating conditions under different nonlinearities. The proposed controller is tested for practical generation plants (NTTPS, KTPS, and RTPS) in India.

Design Of Observer Based Quasi Decentralized Fuzzy Load Frequency Controller for Inter Connected Power System

Design Of Observer Based Quasi Decentralized Fuzzy Load Frequency Controller for Inter Connected Power System

Optimal fuzzy load frequency controller with simultaneous auto-tuned membership functions and fuzzy control rules

In this paper, an auto-tuned fuzzy load frequency controller (FLFC)-based articial bee colony (ABC) algorithm is developed to quench the deviations in the frequency and tie-line power due to load disturbances in an interconnected power system. Optimal tuning of membership functions (MFs) and fuzzy control rules is very important to improve the design performance and achieve a satisfactory level of robustness for a particular operation. In this work, to reduce the fuzzy system design eort and take large parametric uncertainties into account, a new systematic and simultaneous tuning method is developed for designing MFs and fuzzy rules. For this, the designing problem is restructured as an optimization problem and the ABC algorithm is employed to solve it. This newly developed method provides some advantages such as a exible controller with a simple structure and easy algorithm. For the purpose of the proposed method's evaluation, the designed controller is applied to a 2-area power system with considerations regarding governor saturation and the results are compared to the one obtained by a classic proportional-integral controller. Simulation results show better operation and improved system parameters, such as the settling time and step response rise time, using the proposed approach, in the presence of system parameter variations.

Decentralized Load-Frequency Control of Large-Scale Nonlinear Power Systems: Fuzzy Overlapping Approach

This paper develops a design methodology of a decentralized fuzzy load-frequency controller for a large-scale nonlinear power system with valve position limits on governors. The concerned system is locally exactly modeled in Takagi-Sugeno's form. Sufficient design condition for uniform ultimate boundedness of the closed-loop system is derived based on the overlapping decomposition. Convergence of all incremental frequency deviations to zero is also investigated. A simulation result is provided to visualize the effectiveness of the proposed technique.

Hybrid Fuzzy Load Frequency Controller for a Two Area Interconnected Power System

This work addresses the special requirements of Automatic Generation Control in Modern interconnected Power system. In order to track the system frequency and handling the power system stability issues many control strategies has been suggested by the researchers .A new Hybrid fuzzy approach is introduced here .Fuzzy Logic controller with Mamdani interface having five member ship functions is tested with the Thermal Thermal and hydro thermal system Further hybrid Fuzzy controller is also tested with the same system and results are compared for the both The system Which is having Hybrid Fuzzy concept and thereby the response of frequency and tie line power can be improved substantially following a load change in any area. Further dynamic responses for small perturbation have been observed, considering HFLC and integral controller and the results of both have been compared.

Fuzzy load frequency control in multi area electric power system

Fuzzy load frequency control in multi area electric power system

Fuzzy Load Frequency Control in Multi Area Electric Power System

The Load Frequency Control (LFC) problem is one of the most important subjects in the electric power system operation and control. In practical systems, the conventional PI type controllers are applied for LFC. In order to overcome the drawbacks of the conventional PI controllers, PI and PID Fuzzy controllers are considered for LFC problem. The parameters of the proposed Fuzzy controllers are tuned using Genetic Algorithms (GA). A multi area electric power system with a wide range of parametric uncertainties is given to illustrate proposed method. The simulation results visibly show the validity of proposed controllers in LFC problem.

Multi-stage fuzzy load frequency control using PSO

In this paper, a particle swarm optimization (PSO) based multi-stage fuzzy (PSOMSF) controller is proposed for solution of the load frequency control (LFC) problem in a restructured power system that operate under deregulation based on the bilateral policy scheme. In this strategy the control is tuned on line from the knowledge base and fuzzy inference, which request fewer sources and has two rule base sets. In the proposed method, for achieving the desired level of robust performance, exact tuning of membership functions is very important. Thus, to reduce the design effort and find a better fuzzy system control, membership functions are designed automatically by PSO algorithm, that has a strong ability to find the most optimistic results. The motivation for using the PSO technique is to reduce fuzzy system effort and take large parametric uncertainties into account. This newly developed control strategy combines the advantage of PSO and fuzzy system control techniques and leads to a flexible controller with simple stricture that is easy to implement. The proposed PSO based MSF (PSOMSF) controller is tested on a three-area restructured power system under different operating conditions and contract variations. The results of the proposed PSOMSF controller are compared with genetic algorithm based multi-stage fuzzy (GAMSF) control through some performance indices to illustrate its robust performance for a wide range of system parameters and load changes.

Efficient fuzzy logic load–frequency controller

This paper investigates an application of the fuzzy logic technique for designing the load–frequency control system to damp the frequency and tie line power oscillations due to different load disturbances. The proposed fuzzy load–frequency controller, called a two layered fuzzy controller, consists of two layers. The first one is called the precompensator, which is used to generate and update the reference value of area control error (ACE), while the second one, called feedback fuzzy logic controller, makes the ACE decay to zero at steady state. The simulated power system consists of an integral control, two area load–frequency power system. The proposed two layered fuzzy logic controllers are designed for each area. The studied power system is subjected to a wide range of load disturbances to validate the effectiveness of the proposed controller. Moreover, a comparison between the power system frequency error responses using the conventional integral control system only and the proposed fuzzy controller is reported and obtained. The digital results prove the power of the present two layered fuzzy load–frequency controller over the conventional one in terms of fast response with less overshoot and small settling time.