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This paper presents an output power smoothing method by a simple coordinated control of DC-link voltage and pitch angle of a wind energy conversion system (WECS) with a permanent magnet synchronous generator (PMSG). The WECS adopts an AC-DC-AC converter system with voltage-source converters (VSC). The DC-link voltage command is determined according to output power fluctuations of the PMSG. The output power fluctuationsin low- and high-frequency domains are smoothed by the pitch angle control of the WECS, and the DC-link voltage control, respectively. By using the proposed method, the wind turbine blade stress is mitigated as the pitch action in high-frequency domain is reduced. In addition, the DC-link capacitor size is reduced without the charge/discharge action in low-frequency domain. A chopper circuit is used in the DC-link circuit for stable operation of the WECS under-line fault. Effectiveness of the proposed method is verified by the numerical simulations. [ABSTRACT FROM AUTHOR]

Simulation has become the most important technique used today for evaluation of engineering solutions, and modeling plays a crucial part in the design of intelligent control paradigms for complex dynamic structures. For the analysis of a megawatt-class wind-energy conversion system (WECS), this research adopts the \cal H\infty control theory in designing an advanced control paradigm that accomplishes the dual purpose of energy capture optimization, as well as power train cyclic load alleviation by mitigating against wind-speed fluctuations. This work is presented in two parts: The first details the modeling of the subsystems of WECS and introduces the multiobjective \cal H\infty control concept, and the second deals with the implementation of the control paradigm. Presented herein is a modeling approach of individual subsystems as a basis for devising the unified control strategy for a 2-MW grid-connected pitch-regulated variable-speed WECS that incorporates a doubly fed induction generator. The credibility of the archetype, to establish the argument that the models produce sound insights and comparable results to data from the real system, is ascertained via validation. [ABSTRACT FROM AUTHOR]

The control of wind-energy conversion systems (WECSs) is still a challenging task for design engineers. Despite being ubiquitous in the wind industry, the performance of classical proportional–integral–derivative controllers is not ideal, and they require additional notch filters to handle turbine nonlinearity. This has triggered interest toward advanced control concepts that are multiobjective and multivariable. With optimality, feedback, and robustness being prerequisites in developing control policies that guarantee high-integrity and fault-tolerant control systems, \cal H\infty control theory has become a standard design method of choice over the past two decades and is gaining prominence in industrial (and WECS) control applications. Based on the linear matrix inequality approach, this paper presents a comprehensive and systematic way of applying the \cal H\infty control design algorithm for automatically gain-scheduling the linear-parameter-varying turbine plant along parameter trajectories. Control seeks to regulate both power and voltage via a synthesis of two controllers, namely, pitch and generator torque, respectively, for a megawatt-class WECS. Digital simulations executed in a MATLAB/Simulink environment ascertain that the control paradigm meets the objectives of optimizing power conversion throughout the operating envelope, as well as eliminating power oscillations through system damping. [ABSTRACT FROM AUTHOR]

Recently, smart grids are attracting attention. Already, a smart grid based on an ac grid is proposed. However, no study on research is presented or published on a smart grid based on a dc grid. This paper presents an ac/dc hybrid smart power system. The proposed system has advantages of both dc and ac grids. The proposed power system consists of a wind generator and several controllable loads. The controllable loads have different capacities. Therefore, by applying power consumption control with the droop characteristic, the dc bus voltage is maintained within the acceptable range. As controllable loads, electric water heater and electric vehicle are assumed. Effectiveness of the proposed method is verified by numerical simulation results. [ABSTRACT FROM PUBLISHER]

Strong growth figures prove that wind is now a mainstream option for new power generation. All the successful megawatt-class wind technology developments to date are results of evolutionary design efforts based on the premise that control can significantly improve energy capture and reduce dynamic loads. The main challenge is wind stochasticity that impacts both power quality and drivetrain fatigue life for a wind generating system. In the proposed paradigm, control is exercised through a self-tuning regulator (STR) that incorporates a recursive least-squares algorithm to predict the process parameters and update the states. In above rated regimes, the control strategy incorporating a pitch regulatory system aims to regulate turbine power and maintain stable, closed-loop behavior in the presence of turbulent wind inflow. The control scheme is formulated based on a detailed performability model; the wind speed is generated by a stochastic model, while the drivetrain is modeled as a multiinertia system linked by a non- ideal (Ks ≠ ∞) shaft described by nonlinear equations. Computer simulations reveal that achieving the two objectives of maximizing energy extraction and load reduction by the STR becomes more attractive relative to the classical PID controller design. [ABSTRACT FROM AUTHOR]

Effective utilization of renewable energies such as wind energy instead of fossil fuels is desirable. Wind energy is not constant and windmill output is proportional to the cube of the wind speed, which causes the generated power of wind turbine generators (WTGs) to fluctuate. In order to reduce the output power fluctuation of wind farms, this paper presents an output power leveling control strategy for a wind farm based on both the average wind farm output power and the standard deviation of the wind farm output power, a cooperative control strategy for WTGs, and pitch angle control using a generalized predictive controller (GPC) in all WTG operating regions. Simulation results using an actual detailed model for wind farm systems show the effectiveness of the proposed method. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 158(4): 31– 41, 2007; Published online in Wiley InterScience (www.interscience. wiley.com). DOI 10.1002/eej.20448 [ABSTRACT FROM AUTHOR]

Wind energy is not constant and windmill output is proportional to the cube of wind speed, which causes the generated power of wind turbine generators (WTGs) to fluctuate. In order to reduce fluctuation, different methods are available to control the pitch angle of blades of windmill. In a previous work, we proposed the pitch angle control using minimum variance control, and output power leveling was achieved. However, it is a controlled output power for only rated wind speed region. This paper presents a control strategy based on average wind speed and standard deviation of wind speed and pitch angle control using a generalized predictive control in all operating regions for a WTG. The simulation results by using actual detailed model for wind power system show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: In order to perform maximum power point tracking control of wind generation system, it is necessary to drive windmill at an optimal rotor speed. For that purpose, a rotor position and a wind velocity sensors become indispensable. However, from the aspect of reliability and increase in cost, rotor position sensor and wind velocity sensor are not usually preferred. Hence, wind velocity and position sensorless operating method for wind generation system using observer is proposed in this paper. Moreover, improving the efficiency of the permanent magnet synchronous generator is also performed by optimizing d-axis current using the Powell method. [Copyright &y& Elsevier]