جستجوی مقالات مرتبط با کلیدواژه "کنترل بار فرکانس" در نشریات گروه "برق"

Power system design and controls are done with stability and reliability. Frequency is one of the important variables to stabilize the speed of engine loads. Considering the vital role of gas turbines in producing electricity without harmful effects on the environment, in this paper, utilizing the Rowen model for the frequency power system, the load-frequency control with the secondary control loop has been examined. For this reason, the design is done by the transfer function and state space. To begin with, the conventional PID controller is designed utilizing CHR and CC calculations in order to increase the system speed, eliminate disturbance and reduce the sum of overshoot. At that point, LQR linear optimal controller is utilized. Finally, due to the uncertainty and disturbance, H2/H∞ robust controller has been considered with the three conditions of nominal performance, robust stability, and reduction of disturbance.  The simulation results obtained with/without the presence of disturbance have been checked and compared in MATLAB software. The results of the simulations show the success of the proposed H2/H∞ robust control strategy in terms of convergence rate and fluctuation range among all the control strategies examined.

Restructuring of power systems and integration of different renewable energy sources with complex dynamic behaviors and high structural uncertainties has made the issue of load frequency control more important. For a hybrid power system that includes a thermal power plant taking into account nonlinear limitations such as the governor dead band and generator rate constraints and renewable energy sources including a wind turbine, solar-thermal power plant, electrolyzer, fuel cell, and plug-in electric vehicle, this paper proposes an adaptive wavelet neural network fractional order PID controller (AWNNFOPID) based on self-recursive wavelet neural networks and fractional order PID controller. To compare the performance of the proposed AWNNFOPID controller, four different scenarios are considered and the simulation results are compared with traditional I, PI, and PID controllers as well as with the optimized FOPID controller. The simulation results show that the proposed AWNNFOPID controller has better performances than the other control strategies used for the studied hybrid power system based on performance indicators such as settling time, rise time, maximum overshoot, maximum undershoot, integral time absolute error (ITAE), and integral absolute error (IAE).

The Microgrid is a small-scale controlled power system, which can be used in islanded mode or in a grid-connected one to provide power. In the islanded Microgrid, the system frequency will be affected severely by the smallest disturbance which can happen due to light inertia in the system. In the independent Microgrid, several generation sources such as solar, wind, and so on can be considered. In addition to these power plants, the discussion of energy conversion as a result of temperature changes can be considered as a thermoelectric converter. In the present article, the effort has been made to propose a microgrid model which incorporates a Thermoelectric Generator (TEG) system. In this system, due to the variety of uncertainties and load variations, an advanced controller must be developed to improve the dynamic stability and reliability of the microgrid system. The Improved Fuzzy Fractional-Order PID is the suggested controller. The proposed controller is applied to a sample islanded microgrid to establish a robust evaluation and to be checked under parametric changes, great demands, and disturbances. The offered controller is compared with those of other PID, FOPID and FPID controllers. The results of simulations reveal that the proposed controller has a proper and robust performance.

Load-frequency control in an isolated microgrid is very important.By turbulence the load, the frequency of the microgrid begins to oscillate which must be damped using the load-frequency control system (secondary control). In this paper, we have reduced the number of utilized controllers for the power supplies in the microgrid (less complexity) and we have incorporated the Model Predictive Controller (MPC), whose weight parameters are optimized using the novel Hybrid Craziness based Particle Swarm Optimization-Pattern Search (HCRPSO-PS) algorithm, for controlling the load-frequency in a two-area microgrid. The results of the proposed controller, in a number of different scenarios, are compared with other methods such as the PID controller optimized with the Social Spider Optimization (SSO) algorithm and the model predictive controller whose weight parameters are obtained using the Craziness based Particle Swarm Optimization (CRPSO) algorithm (to demonstrate the efficiency of the novel hybrid algorithm), considering load variations and the distribution of the sources in the microgrid. We have demonstrated the efficiency of the proposed method in terms of response speed, overshoot/undershoot reduction and control complexity(less complex). Simulations are performed using MATLAB software

Load frequency control (LFC) in power systems is one of the most important issues in the field of optimizing power system performance that attracted the attention of many researchers. In this work, a sliding mode based load frequency control is developed on a three-area interconnected power system. The power system contains non-reheat, reheat, and hydraulic turbines which are distributed in these three areas respectively. Both governor dead band and generation rate constraint are included in the model of this power system. Our control goal is to regulate the frequency error, tie-line power error and area control error despite the presences of external load disturbance and system uncertainties. Additionally, an optimization process is proposed for optimal adjustment of the sliding mode control parameters of each of the three areas, aimed at improving integral performance and step response characteristics such as amount of overshoot, steady state error, and sitting time. The optimization was performed using the particle swarm optimization (PSO) algorithm, which is one of the most powerful algorithms for nonlinear problems solving. The sliding mode based load frequency controller is simulated on this three-area interconnected nonlinear power system. The simulation results verify the effectiveness of the sliding mode controller. In addition, the performance of SMC is compared with an optimized PI controller. The comparison study shows the superiority of the SMC to the PI controller in term of control performance. They also demonstrate the robustness of the sliding mode controller against parameter variations and external disturbances.