An ANN-Based Power System Emergency Control Scheme in the Presence of High Wind Power Penetration (original) (raw)

A novel fuzzy system for wind turbines reactive power control

… (FUZZ), 2011 IEEE …, 2011

The paper proposes a new fuzzy controller for variable speed wind turbines (WTs) in order to compensate the variations at the point of common coupling (PCC) by controlling the reactive power generated by WTs. A protection system is used to disconnect the WTs from the grid when the controller is unable to compensate the voltage variations. Simulations carried out on a real 37-bus Italian weak distribution network demonstrated that the controller allows compensating voltage variations during voltage sags.

A New Adaptive Neuro-Fuzzy Inference System (ANFIS) Controller to Control the Power System equipped by Wind Turbine

ITM Web of Conferences, 2022

This study proposes a new Adaptive Neuro-Fuzzy Inference System (ANFIS) controller to control the power system tuned by a wind turbine. The purpose of design is to improve the dynamical response of power systems after fault which the voltage controller has been improved. The effectiveness of the proposed approach is studied under different situations of three machines 9 bus power systems which the wind turbine is replaced by wind turbine equipped by ANFIS controller. The simulation results confirm that the tuning method is able to preserve optimal performances over wide range of disturbances. The results have demonstrated the high performances of the proposed technique in terms of low oscillation, ripple, rapidity and accuracy.

Design and implementation of a fuzzy controller for wind generators performance optimisation

2007

Actual wind power costs together with incentives and financing options for developing renewable energy facilities make wind energy source competitive with conventional generation sources and it is believed that wind energy will be the most cost effective source of electrical power in the next future. However, the wind power production diffusion involves the development of efficient control systems able to improve wind systems effectiveness. Therefore, a design methodology, able to generate an adaptive fuzzy model for maximum energy extraction from variable speed wind turbines is proposed in this paper. The fuzzy model is designed by using fuzzy clustering combined with genetic algorithms (GA) and recursive leastsquares (LS) optimisation methods. Some simulation results on a doubly-fed induction generator confirmed that the proposed design methodology is able to identify a Takagi-Sugeno-Kang (TSK) fuzzy model exhibiting adaptivity, learning capability, high speed of computation and low memory occupancy.

Performance Assessment of a Wind Turbine using Fuzzy Logic and Artificial Network Controllers

—This paper makes a comparison between two control methods for maximum power point tracking (MPPT) of a wind turbine modules using Permanent Magnet Synchronous Generators(PMSG) under fixed and different wind condition: the Fuzzy Logic (FL) and the Artificial Neural Network control (ANN). Both techniques have been simulated and analyzed by using Matlab/Simulink software. The simulated power transitions and the power tracking time realized by the fuzzy logic controller and the neural network controller has been evaluated in comparison with Tip Speed Ratio controller (TSR).

Protection of DFIG wind turbine using fuzzy logic control

Alexandria Engineering Journal, 2016

In the last 15 years, Double Fed Induction Generator (DFIG) had been widely used as a wind turbine generator, due its various advantages especially low generation cost so it becomes the most important and promising sources of renewable energy. This work focuses on studying of using DFIG as a wind turbine connected to a grid subjected to various types of fault. Crowbar is a kind of protection used for wind turbine generator protection. ANFIS controller is used for protection of DFIG during faults. The fault current under symmetric and asymmetric fault is presented as well as a way to control the increase in rotor current which leads to voltage increase in DC link between wind generator and the grid. ANFIS is used for solving such problem as it is one of the most commonly AI used techniques. Also the current response of DFIG during fault is improved by adapting the parameters of PI controllers of the voltage regulator using fuzzy logics. ANFIS also in this paper is used for detecting and clearing the short circuit on the DC capacitor link during the operation. A simulation study is illustrated using MATLAB/Simulink depending on currents and voltages measurement only for online detection of the faults. The proposed technique shows promising results using the simulation model.

Adaptive Fuzzy Control for Variable Speed Wind Systems with Synchronous Generator and Full Scale Converter

Green Energy and Technology, 2010

Control systems for variable-speed wind turbines (WTs) are continuously evolving toward innovative and more efficient solutions. Among the various techniques, fuzzy logic is gaining reputation due to its simplicity and effectiveness. In this chapter, after a review of fuzzy logic based control applied to wind energy conversion systems, a sensorless peak power tracking control for maximum wind energy extraction and a voltage control allowing compensation of voltage variations at the WT connection point are proposed. Both the controllers are based on fuzzy logic.

Power quality control of an autonomous wind–diesel power system based on hybrid intelligent controller

Wind power generation is gaining popularity as the power industry in the world is moving toward more liberalized trade of energy along with public concerns of more environmentally friendly mode of electricity generation. The weakness of wind power generation is its dependence on nature-the power output varies in quite a wide range due to the change of wind speed, which is difficult to model and predict. The excess fluctuation of power output and voltages can influence negatively the quality of electricity in the distribution system connected to the wind power generation plant. In this paper, the authors propose an intelligent adaptive system to control the output of a wind power generation plant to maintain the quality of electricity in the distribution system. The target wind generator is a costeffective induction generator, while the plant is equipped with a small capacity energy storage based on conventional batteries, heater load for co-generation and braking, and a voltage smoothing device such as a static Var compensator (SVC). Fuzzy logic controller provides a flexible controller covering a wide range of energy/voltage compensation. A neural network inverse model is designed to provide compensating control amount for a system. The system can be optimized to cope with the fluctuating market-based electricity price conditions to lower the cost of electricity consumption or to maximize the power sales opportunities from the wind generation plant.

A New Adaptive Neuro-Fuzzy Inference System (ANFIS) and PI Controller to Voltage Regulation of Power System Equipped by Wind Turbine

European Journal of Electrical Engineering, 2019

Received: 26 January 2019 Accepted: 29 March 2019 In this paper, new Adaptive Neuro-Fuzzy Inference System (ANFIS) and PI controller have been proposed and investigated which the power system is equipped by Static Var Compensator (SVC) and small wind turbine. The SVC is controlled by PI controller optimized by genetic algorithm (GA) to regulate the voltage profile. To demonstrate the efficiency of proposed controller, a Single Machine Infinite Bus (SMIB) has been considered, in which small fluctuation of mechanical damped has been applied to improve the transient stability and has been evaluated using a relative rotor criteria. Obtained results have demonstrated a better performance with ANFIS and PI controller in which both voltage and transient stability have been controlled perfectly.

Power Control of Wind Turbine based on Fuzzy Controllers

Energy Procedia, 2013

In this paper, we develop the overall model of the wind energy conversion system (WECS) structure based on induction generator (IG), and propose a study of the electrical parts (induction machine and static converter). Our study is developed on a wind conversion system in order to produce optimum power and to extract the maximal wind power. The goal of this paper is to control the power generated by the WECS and transmitted to the grid. We propose a new control strategy based on fuzzy logic in order to control the power generated by the WECS. The main drawback is that the WECS is highly nonlinear, and thus a nonlinear control strategy is required. An adaptive fuzzy power controller is proposed to overcome this problem. A simulation study is done to prove the validation of the strategy used in power control.