Impacts of Wind Power Integration on Generation Dispatch in Power Systems

-This paper proposes a new robust decentralized power oscillation dampers (POD) design of doubly-fed induction generator (DFIG) wind turbine for damping of low frequency electromechanical oscillations in an interconnected power system. The POD structure is based on the practical 2 nd -order lead/lag compensator with single input. Without exact mathematical model, the inverse output multiplicative perturbation is applied to represent system uncertainties such as system parameters variation, various loading conditions etc. The parameters optimization of decentralized PODs is carried out so that the stabilizing performance and robust stability margin against system uncertainties are guaranteed. The improved firefly algorithm is applied to tune the optimal POD parameters automatically. Simulation study in two-area four-machine interconnected system shows that the proposed robust POD is much superior to the conventional POD in terms of stabilizing effect and robustness.

Section: Introductionmentioning

confidence: 99%

Power System Oscillations Damping by Robust Decentralized DFIG Wind Turbines

Surinkaew¹,

Ngamroo²

2015

“…However, wind power generation is unsteady and uncontrollable because wind speed inherently depends on natural meteorological conditions. Moreover, the introduction of large amounts of intermittent power to the grid can bring about serious technical challenges such as grid interconnection, power quality, and system reliability [4,5]. Therefore, wind farm (WF) developers need to overcome the intermittent nature of wind power before attempting to dispatch high levels of power to the grid.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Wind Power Dispatch to Minimize Energy Storage System Capacity

Nguyen¹,

Lee²

2014

-By combining a wind turbine with an energy storage system (ESS), we are able to attenuate the intermittent wind power characteristic making the power derived from a wind farm dispatchable. This paper evaluates the influence of the phase delay of the low-pass filter in the conventional smoothing power control on the ESS capacity; longer phase delays require a larger ESS capacity. In order to eliminate the effect of the phase delay, we optimize the power dispatch using a zero-phase low-pass filter that results in a non-delayed response in the power dispatch. The proposed power dispatching method significantly minimizes the ESS capacity. In addition, the zero-phase lowpass filter, which is a symmetrical forward-reverse finite impulse response type, is designed simply with a small number of coefficients. Therefore, the proposed dispatching method is not only optimal, but can also be feasibly applied to real wind farms. The efficacy of the proposed dispatching method is verified by integrating a 3 MW wind turbine into the grid using wind data measured on Jeju Island.

“…It has been demonstrated that the continuing integration of new large WFs into the power systems can influence the stabilities of power systems [3,4].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Multiple MPC for a Wind Farm with DFIG: a Decentralized-Coordinated Approach

Li¹,

Zhang²,

Lin³

et al. 2016

-For low investment and flexible control, doubly fed induction generator (DFIG) is becoming the dominant type that is been used in the wind farms (WFs) today. The report researches about the rotor-side controller of DFIG where all design is based on the single machine infinite bus (SMIB) model. The interactions between the different generators have not been considered in the SMIB model, and the desired performance cannot be obtained by using the controller based on this model. In this situation, an adaptive decentralized-coordinated multiple model predictive control (ADM-MPC) is proposed. First, the interaction measurement method is developed to obtain the interaction measurement model of DFIG, where the interactions between the different generators have been considered. Next, an adaptive multiple MPC based on the obtained interaction measurement method of DFIG is employed to control the rotor-side converter of DFIG. In order to cope with the stochastic disturbance of wind turbine, the augment state structure is employed to improve the tracking control performance. An artificial neural network (ANN) trained online is employed as a weighting controller to cope with the nonlinearities and large operating range of DFIG. A simple, generic renewable power system (RPS) is used to demonstrate contributions. The results of both dominant eigenvalue analysis and time response simulations are represented to illustrate contributions to system damping and transient stability that the DFIG based WF can make with the proposed ADM-MPC controller.