Abstract:This study aims to define an online reactive power control scheme for a wind energy harvesting network such that it regulates the voltage at the transmission level in a manner comparable to a conventional synchronous plant and hence could be integrated in an existing transmission network hierarchical voltage control scheme. For that purpose, all decentralised elements within the network (wind farms and on load tap changing (OLTC) transformers) should be coordinated. In that sense, a central controller needs to… Show more
“…Transformers' coordination should be done in both ambits static and dynamic as has been already intimated. Some analysis of cascade OLTC transformer coordination can be found in [33] and [70] for HNETs.…”
“…For Types B and C also a novel off-line determination of the dynamic settings (dead bands and delays of transformer taps) based on multi-objective particle swarm optimisation techniques is proposed [70,106].…”
Section: Latest Research On Hnet Wind Voltage Controlmentioning
Implementing sophisticated voltage controls of wind farms may provide manifold benefits such as reducing losses of the distribution network (DNET) and harvesting network (HNET), increasing the wind hosting capacity of transmission networks (TNETs) and reducing wind curtailments. However, it represents an enormous challenge since wind energy is dispersed increasing the complexity of the required centralised control systems. This study contains a comprehensive state-of-the-art review of the huge research that is available in the literature in order to foster the participation of onshore wind energy in voltage control. The current situation is described by the actual technological developments of control devices and the regulatory framework of a set of European countries with high wind penetration figures. A classification of key wind voltage control concepts will be proposed in order to understand and organise the available literature references. The state-of-the-art review covers the integration of wind energy through DNETs, smart grids and dedicated HNETs into the TNET, covering research from a steady state and also dynamic perspective. The new requirements of theTransmission system operators tend to suggest that wind farms should have a similar performance compared with conventional plants. Thus, in this study, special attention will be given to the literature review of HNETs since it has been the most promising alternative of integrating wind voltage control into the existing transmission grid hierarchical control schemes. A set of relevant field experiences and international projects will be described, showing some effort to implement academic research into practice.
“…Transformers' coordination should be done in both ambits static and dynamic as has been already intimated. Some analysis of cascade OLTC transformer coordination can be found in [33] and [70] for HNETs.…”
“…For Types B and C also a novel off-line determination of the dynamic settings (dead bands and delays of transformer taps) based on multi-objective particle swarm optimisation techniques is proposed [70,106].…”
Section: Latest Research On Hnet Wind Voltage Controlmentioning
Implementing sophisticated voltage controls of wind farms may provide manifold benefits such as reducing losses of the distribution network (DNET) and harvesting network (HNET), increasing the wind hosting capacity of transmission networks (TNETs) and reducing wind curtailments. However, it represents an enormous challenge since wind energy is dispersed increasing the complexity of the required centralised control systems. This study contains a comprehensive state-of-the-art review of the huge research that is available in the literature in order to foster the participation of onshore wind energy in voltage control. The current situation is described by the actual technological developments of control devices and the regulatory framework of a set of European countries with high wind penetration figures. A classification of key wind voltage control concepts will be proposed in order to understand and organise the available literature references. The state-of-the-art review covers the integration of wind energy through DNETs, smart grids and dedicated HNETs into the TNET, covering research from a steady state and also dynamic perspective. The new requirements of theTransmission system operators tend to suggest that wind farms should have a similar performance compared with conventional plants. Thus, in this study, special attention will be given to the literature review of HNETs since it has been the most promising alternative of integrating wind voltage control into the existing transmission grid hierarchical control schemes. A set of relevant field experiences and international projects will be described, showing some effort to implement academic research into practice.
“…Then, this random number is rescaled to the appropriated valid range [v MIN , v MAX ] to obtain v TURB [n]. This process is illustrated in (14) for the i-th low-frequency interval:…”
Section: Turbulence Componentmentioning
confidence: 99%
“…Besides, as will be shown in Section 5, turbulence component is as well represented by a Beta PDF as it could be by a Normal PDF, and even better in some cases. The standard deviation of v TURB , σ v TURB , because of the linear transformation of (14), is the standard deviation of ξ BETA , σ B , affected by the factor (v MAXv MIN ):…”
A simple model to generate large band wind speed time sequences, especially easy to implement with a very reduced number of parameters, is presented. It is based on the calculation of a low-frequency and a high-frequency components. Low-frequency component with 1 h sample time is obtained from a random process based on a conditional probability density function. Using real data from two different wind farms in two different months of the year, it has been found that Weibull distribution centered in the current hourly mean value seems to represent well the 1 h conditional PDF in all cases, and the standard deviation of this conditional Weibull is more or less in the range 1-1.3 m s À1 independently of the season of the year or the location. Regarding to high-frequency component, low-frequency samples are used as initial and final values and, between them, the turbulence component values are inserted. For that, it has been used a stochastic process based on a Beta probability function and a simple rescaling procedure with two non-linear parameters, calculated in a recursive way. Unlike the usual modelling procedures presented in the literature, spectral power density functions are not used. This simplifies the implementation significantly. Ten second sample-time real speed wind data from two different wind farms have been used to validate the proposed high-frequency model, obtaining excellent results. A thorough revision of the main models found in the literature to produce wind speed time sequences for dynamic analysis is performed in the paper.
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