Earticle

The change in the power demand results in modification of frequency of interrelated power system amongst the dissimilar areas. The load frequency control can be attained by proper regulation of participating producing elements. The Area Control Error (ACE) has to be minimized for the frequency response enhancement and Integral Square Error (ISE) is generally taken as ACE. The aim of Load Frequency Control (LFC) is to diminish the Integral Square Error to Nil with constant variation of claim of dynamic energy so that the entire produced energy of the arrangement and load obligation correctly matches with every element. In this paper, results of multi area interconnected power system under Unilateral Contract are verified with the assistance of conventional controllers.

In this paper, the Superconductor flywheel energy storage system (SFESS) was used for the load frequency control (LFC) of an interconnected 2 area power system. The robust SFESS controller using quantitative feedback theory (QFT) was designed to improve control performance in spite of parameter uncertainty and unexpected disturbances. An overlapping decomposition method was applied to simplify SFESS controller design for the interconnected 2 area power system. The model for simulation of the interconnected 2 area power system included the reheat steam turbine, governor, boiler dynamics and nonlinearity such as governor deadband and generation rate constraint (GRC). To verify robust performance of proposed SFESS controller, dynamic simulation was performed under various disturbances and parameters variation of power system. The results showed that the proposed SFESS controller was more robust than the conventional method

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.

This paper deals with the design of decentralized controller for load-frequency control of interconnected power systems with superconducting magnetic energy storage units and Governor Dead Band Nonlinearity using Multi-Objective Evolutionary Algorithm. The superconducting magnetic energy storage unit exhibits favourable damping effects by suppressing the frequency oscillations as well as stabilizing the inter-area oscillations effectively. The proposed control strategy is mainly based on a compromise between Integral Squared Error and Maximum Stability Margin criteria. Analysis on a two-area interconnected thermal power system reveals that the proposed controller improves the dynamic performance of the system and guarantees good closed-loop stability even in the presence of nonlinearities and with parameter changes.

This paper presents the effect on application of the flywheel energy storage system (FESS) for load frequency control (LFC) of an interconnected 2 area power system. To do this, the control characteristics with the FESS were compared with that of the conventional governor controller. The controller for the FESS control and the governor control used a PID type controller. Both the FESS PID controller and the governor PID controller using genetic algorithm (GA) were designed to optimize the PID parameters. The frequency and generation output characteristics with the only FESS controller and with the only conventional governor controller were compared. To verify robust performance of the FESS controller, the computer simulations were performed under various disturbances. The simulation results showed that the FESS controller provided better dynamic responses in comparison with the conventional governor controller.

This paper proposes various design procedures for computing Power System Ancillary Service Requirement Assessment Indices (PSASRAI) for a Two-Area Thermal Reheat Interconnected Power System (TATRIPS) in a restructured environment. In an interconnected power system, a sudden load perturbation in any area causes the deviation of frequencies of all the areas and also in the tie-line powers. This has to be corrected to ensure the generation and distribution of electric power companies to ensure good quality. A simple Proportional and Integral (PI) controllers have wide usages in controlling the Load Frequency Control (LFC) problems. So the design of the PI controller gains for the restructured power system are obtained using Bacterial Foraging Optimization (BFO) algorithm. From the simulation results, the PSASRAI are calculated based on the settling time and peak over shoot concept of control input deviations of each area for different possible transactions. These Indices are useful for system operator to prepare the power system restoration plans. Moreover, the LFC loop coordinated with Redox Flow Batteries (RFB) has greatly improved the dynamic response and it reduces the control input requirements and to ensure improved PSASRAI, thereby improving the system reliability.

Penetration of renewable energy sources makes the modern interconnected power systems to have more intelligence and flexibility in the control. Hence, it is essential to maintain the system frequency and tie-line power exchange at nominal values using Load Frequency Control (LFC) for efficient, economic and reliable operation of power systems. In this paper, intelligent tuning of the Proportional Integral Derivative (PID) controller for LFC in an interconnected power system is considered as a main objective. The chosen problem is formulated as an optimization problem and the optimal gain parameters of PID controllers are computed with three innovative swarm intelligent algorithms named Particle Swarm Optimization (PSO), Bacterial Foraging Optimization Algorithm (BFOA) and hybrid Bacterial Foraging Particle Swarm Optimization (BFPSO) and a comparative study is made between them. A new objective function designed with necessary time domain specifications using weighted sum approach is also offered in this report and compared with conventional objective functions. All the simulation results clearly reveal that, the hybrid BFPSO tuned PID controller with proposed objective function has better control performances over other optimization methodologies.

This paper focuses on a new optimization technique of a fuzzy logic based proportional integral (FLPI) load frequency controller by the multiple tabu search (MTS) algorithm. Conventionally, the membership functions and control rules of fuzzy logic control are obtained by trial and error method or experiences of designers. To overcome this problem, the MTS algorithm is proposed to simultaneously tune proportional integral gains, the membership functions and control rules of a FLPI load frequency controller in order to minimize the frequency deviations of the interconnected power system against load disturbances. The MTS algorithm introduces additional techniques for improvement of the search process such as initialization, adaptive search, multiple searches, crossover and restart process. Simulation results explicitly show that the performance of the proposed FLPI controller is superior to conventional PI and FLPI controllers in terms of overshoot and settling time. Furthermore, the robustness of the proposed FLPI controller under variation of system parameters and load change are higher than that of conventional PI and FLPI controllers.

In this paper an application of centralized pitch angle controller for fixed speed wind turbines based wind farm to mitigate load frequency fluctuation is presented. Reference signal for the pitch angle of each wind turbine is calculated by using proposed centralized control system based on wind speed information. The wind farm in the model system is connected to a multi machine power system which is composed of 4 synchronous generators and a load. Simulation analyses have been carried out to investigate the performance of the controller using real wind speed data. It is concluded that the load frequency of the system can be controlled smoothly.

This paper presents the two lossless auxiliary inductors-assisted voltage source type half bridge (single ended push pull: SEPP) series resonant high frequency inverter for induction heated king roller in copy and printing machines. The simple high-frequency inverter treated here can completely achieve stable zero current soft switching (ZCS) commutation for wide its output power regulation ranges and load variations under its constant high frequency pulse density modulation (PDM) scheme. Its transient and steady state operating principle is originally described and discussed for a constant high-frequency PDM control strategy under a stable ZCS operation commutation, together with its output effective power regulation characteristics-based on the high frequency PDM strategy. The experimental operating performances of this voltage source SEPP ZCS-PDM series resonant high frequency inverter using IGBTs are illustrated as compared with computer simulation results and experimental ones. Its power losses analysis and actual efficiency are evaluated and discussed on the basis of simulation and experimental results. The feasible effectiveness of this high frequency inverter appliance implemented here is proved from the practical point of view.

This paper proposes a robust FPID(Fuzzy Proportional Integral Derivative) controller for the LFC(load frequency control) of 2-area power system. The PID gain parameters of the proposed robust FPID controller are self-tuned by PSGM(Product Sum Gravity Method) which is very similiar to human's inference procedures. As the results of simulation, the proposed FPID controller against various load disturbances shows that it is superior to the conventional control techniques such as optimal, PID and fuzzy control in the response characteristics of frequency and tie line power flow.

This paper presents a design technique of self-organizing fuzzy controller using a learning method of fuzzy inference rule by a gradient method for load frequency control of power system. The membership functions in antecedent part and in consequent part of fuzzy inference rules are tuned by the gradient method. The related simulation results show that the proposed fuzzy controller are more powerful than the conventional ones for reduction of undershoot and deviation of load frequency in steady-state, and for minimization of settling time.

This paper presents an optimal Fuzzy Control Technique to control the load frequency control of multiarea power system with a given stepwise load disturbance. The related simulation results show that the optimized fuzzy control technique are more effective than the conventional control technique (TBC, Optimal Control and etc) for reduction of load frequency deviation in transient and stedy-state, and for minimization of settling time.

This paper presents a Fuzzy Control Technique to improve the load frequency control dynamics of a power system for a given load perturbation(step-function waveform). A related simulation results follow and show that the optimized rules by the proposed technique are effective for reduction of overshoot and deviation of load frequency in stedy-state, and for minimization of settling time.

A new robust load-frequency control (LFC) methodology is proposed for nonlinear power systems with the valve position limits of the governor in the presence of parametric uncertainties. The Takagi-Sugeno (TS) fuzzy model is adopted for fuzzy modeling of the nonlinear power system. A sufficient condition of the robust stability is presented in the sense of Lyapunov for the TS fuzzy model with parametric uncertainties. The intelligent digital redesign technique for the uncertain nonlinear power system is also studied. The effectiveness of the proposed robust fuzzy LFC controller design method is demonstrated through a numerical simulation.

In this paper. the robust PID controller using immune algorithm(IA) for load frequency control(LFC) is designed. In proposed method. objective function is represented as antigens. An affinity calculation is embedded within the algorithm for determining the promotion or suppression of antibody. Simulation results show that the proposed robust load frequency controller can achieve good performance even in the presence of generation rate constraints.

The paper presents neural network control techniques for load frequency control of two area power system. Using learning algorithm of error back propagation after learning accept input on the optimal control $e_{i}$, $\dot{e}_{i}$, and $u_{i}$ frequency characteristic and tie-line load flow characteristic investigated dynamic. From result simulation, frequency deviation and tie-line load flow deviation have reduction remarkable.

In this paper, we design an Adaptive Neuro-Fuzzy Inference System(ANFIS) Precompensator for the performance improvement of conventional proportional integral derivative (PID) controller that the governor system of power plant constantly maintains the load frequency of two-area power system. The ANFIS Precompensator is expressed as the membership functions of premise parameters and the linear combination of consequent parameters by Sugeno's fuzzy if-then rules using nonlinear input-output relation for the set point automatic modification maintaining conventional PID controller. The proposed compensation design technique is hoped to be satisfactory method overcome difficulty of exact modelling and arising problems by the complex nonlinearities of power system, and our design shows merit that is easily implemented by adding an ANFIS precompenastor to an existing PID controller without replacement.

This paper presents a fuzzy-neural network controller technique on the load frequency control of two-area power system. Firstly, Fuzzy controller a series of initial selected rules are improved by means of the proposed technique. Secondly, scale factors for error, change rate of error and control input are optimized by the given error back-pagation teaming algorithms. Finally, the related simulation results show that the proposed fuzzy neural network controller technique are more powerful than conventional ones.

This paper has presented a method for self-tuning tile PID controller using a BP method of multilayered NNs. The proposed controller employ input signal as a learning signal of PID control. The proposed controller is applied to load-frequency control of power system and it is investigated a dynamic characteristic. The simulation results shows that proposed NN STPID controller has the good dynamics responses against load disturbances.